Merge pull request 'Trial-data scrapers + search_trials MCP tool (cross-vendor yield trials)' (#7) from trial-data-scrapers into main

2026-05-25 15:19:43 -04:00
parent 7b3da908e0 c737871c4c
commit 17260c32c8
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@@ -0,0 +1,44 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-2024-pnw-combined",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2024 Pacific Northwest Combined Summary, Three-Year Data",
+  "filename": "2024%20PNW%20Combined.pdf",
+  "region": "Pacific Northwest",
+  "wheat_class_section": null,
+  "year": 2024,
+  "years_covered": [
+    2024
+  ],
+  "varieties_found": [
+    "AP Olympia",
+    "AP Exceed",
+    "SY Ovation",
+    "SY Dayton",
+    "SY Assure",
+    "AP Iliad",
+    "LCS Shine",
+    "LCS Artdeco",
+    "Norwest Duet",
+    "LCS Hulk",
+    "PNW Hailey",
+    "LCS Sonic",
+    "Norwest Tandem",
+    "UI Magic CL+",
+    "LCS Blackjack",
+    "LCS Drive",
+    "LCS Jefe",
+    "LCS Kamiack"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2024-09/2024%20PNW%20Combined.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2024-09/2024%20PNW%20Combined.pdf"
+  ],
+  "page_text_chars": 2613,
+  "fetched_at": "2026-05-25T19:11:04.196638+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,54 @@
+# 2024 Pacific Northwest Combined Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Region:** Pacific Northwest
+- **Year:** 2024
+- **PDF:** https://agriprowheat.com/sites/default/files/2024-09/2024%20PNW%20Combined.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Olympia, AP Exceed, SY Ovation, SY Dayton, SY Assure, AP Iliad, LCS Shine, LCS Artdeco, Norwest Duet, LCS Hulk, PNW Hailey, LCS Sonic, Norwest Tandem, UI Magic CL+, LCS Blackjack, LCS Drive, LCS Jefe, LCS Kamiack
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2024 Pacific Northwest Combined Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2022-2024
+3-Yr Combined 2-Yr Combined Combined Moses Lake, Walla Walla, Aberdeen, Craigmont, Twin Falls,
+Variety (2022-2024) (2023-2024) (2024) WA WA ID ID ID
+Soft White Yield TWT Yield TWT Yield TWT Yield Yield Yield Yield Yield
+Winter Wheat Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A Bu/A Bu/A Bu/A
+AP Olympia 153.6 63.7 146.5 63.5 154.7 65.4 201.6 189.5 113.8 124.5 144.2
+AP Exceed 150.5 63.2 147.2 63.2 156.6 65.2 188.0 191.2 124.2 124.7 154.8
+SY Ovation 148.5 63.2 146.3 63.1 148.9 64.8 186.4 179.4 117.1 120.1 141.3
+SY Dayton 146.4 63.2 143.1 63.2 155.4 65.1 192.6 189.4 115.4 128.9 150.6
+SY Assure 141.6 64.0 138.7 63.9 141.3 65.4 144.6 172.6 119.7 133.4 136.1
+AP Iliad 144.7 63.1 150.7 65.1 173.2 175.3 116.3 135.4 153.2
+LCS Shine 150.5 62.9 146.0 62.8 156.1 64.4 182.0 169.0 137.3 125.8 166.5
+LCS Artdeco 149.4 62.5 145.9 62.6 158.9 64.2 197.9 183.8 139.9 122.3 150.3
+Norwest Duet 148.5 62.3 148.7 62.0 162.1 64.3 220.0 196.5 129.3 123.9 140.8
+LCS Hulk 147.9 64.0 145.1 63.6 156.3 65.3 204.1 174.1 133.5 123.5 146.4
+PNW Hailey 147.3 63.9 142.0 63.9 152.1 65.4 188.6 192.7 112.1 126.1 141.0
+LCS Sonic 146.8 62.8 143.7 62.7 150.3 64.7 190.3 186.6 124.2 125.6 125.0
+Norwest Tandem 144.2 62.4 143.2 62.3 156.1 64.6 196.1 169.8 137.5 130.1 146.8
+UI Magic CL+ 143.4 63.7 139.4 63.4 150.5 65.4 179.5 183.6 124.2 123.2 142.1
+LCS Blackjack 147.7 60.5 162.0 63.1 203.8 198.0 122.3 131.9 154.0
+LCS Drive 141.7 61.3 153.0 63.8 181.4 181.0 125.8 122.9 153.8
+LCS Jefe 158.0 65.1 208.3 191.0 113.4 123.0 154.3
+LCS Kamiack 151.1 65.1 181.1 178.9 122.9 133.2 139.6
+Mean General 148.7 63.2 146.4 62.9 156.0 64.8 192.3 186.6 126.6 127.6 147.1
+LSD General (5%) EE 7.8 0.7 9.2 1.0 13.0 1.3 18.5 ns 4.5 8.9 ns
+CV (Effective) 6.5 1.8 6.5 1.9 5.4 1.5 4.7 6.7 1.8 3.4 6.7
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+NS = Non Significant
+Locations
+2022—Colfax, WA; Aberdeen, Genesee, and Twin Falls, ID
+2023—Moses Lake and Walla Walla, WA; Craigmont, Genesee, and Twin Falls, ID
+2024—Moses Lake and Walla Walla, WA; Aberdeen, Craigmont, and Twin Falls, ID
+© 2023 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company. 8-30-24
+```
@@ -0,0 +1,35 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-2025-np-perf-data-sd-web",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Performance Summary, Syngenta Data",
+  "filename": "2025%20NP%20Perf%20Data%20SD%20web.pdf",
+  "region": null,
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "SY Valda",
+    "AP Dagr",
+    "AP Iconic",
+    "AP Elevate",
+    "AP Murdock",
+    "AP Gunsmoke CL2",
+    "SY Ingmar",
+    "AP Revolution",
+    "LCS Trigger"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20SD%20web.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20SD%20web.pdf"
+  ],
+  "page_text_chars": 5882,
+  "fetched_at": "2026-05-25T19:11:13.388036+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,104 @@
+# 2025 Performance Summary, Syngenta Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20SD%20web.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** SY Valda, AP Dagr, AP Iconic, AP Elevate, AP Murdock, AP Gunsmoke CL2, SY Ingmar, AP Revolution, LCS Trigger
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Performance Summary, Syngenta Data
+South Dakota
+2025 Yield bu/ac
+South Dakota Protein Test Wt. Heading Height
+Variety Avg. Agar Miller Northville Selby % lbs/bu 1-9 1-9
+AgriPro HY141 59.4 35.8 57.6 72.0 72.1 15.9 57.1 5 6
+SY Valda 56.8 35.3 63.3 61.2 67.3 16.0 58.2 5 5
+AP Dagr 56.4 29.7 54.5 69.8 71.5 16.0 55.6 6 4
+AgriPro HY155 56.2 31.1 57.3 65.6 70.9 16.9 57.6 5 6
+AgriPro HY162 54.8 30.4 52.2 68.2 68.5 16.2 56.7 5 6
+AP Iconic 54.1 29.0 52.0 68.9 66.4 17.0 56.3 5 6
+AP Elevate 53.3 27.1 51.1 71.5 63.8 16.8 56.2 6 4
+AP Murdock 48.5 29.8 46.6 51.0 66.7 17.5 57.1 4 4
+AP Gunsmoke CL2 47.6 30.1 44.8 64.5 51.2 17.8 55.7 5 5
+SY Ingmar 44.3 23.1 40.5 59.3 54.3 17.8 57.2 5 5
+AP Revolution 43.0 31.5 35.7 38.9 66.1 17.3 57.9 4 4
+LCS Trigger 63.5 34.0 67.6 77.8 74.6 15.2 58.1 6 6
+ND Stampede 60.2 47.3 54.3 66.5 72.6 17.1 58.2 5 5
+Brawn-SD 58.8 42.1 55.4 69.0 68.9 15.4 59.5 5 NA
+WB9641 57.0 32.2 58.1 71.6 66.0 16.0 56.8 6 5
+MN-Torgy 56.2 34.0 54.0 67.4 69.4 17.9 58.9 6 6
+WB9645 55.9 37.5 51.3 67.2 67.6 16.1 56.8 7 6
+Ascend-SD 54.7 33.2 51.1 66.3 68.3 16.9 57.7 6 8
+Driver 52.0 30.9 44.4 70.2 62.5 16.7 57.4 5 7
+WB9642 49.4 34.7 30.0 65.8 67.0 16.4 59.1 6 4
+WB9590 42.6 41.3 25.8 50.4 52.9 17.9 57.1 4 4
+Mean 53.7 33.7 50.3 64.4 66.3 16.7 57.4
+LSD (5%) 8.4 7.1 9.9 5.8 1.0 2.4
+CV (%) 9.7 9.9 9.0 13.0 4.3 2.6 1.2
+No. of Locs. 4 2 2
+Numbers in bold type are in the top yielding group and considered statistically similar.
+Numerical ratings: Heading: 1= early; Height: 1 = short; Lodging: 1 = no lodging; Disease 1 = tolerant
+These agronomic assessments are made by Syngenta scientists and reflect each variety’s relative performance within these characteristics through the 2025 crop year. Specific conditions may cause
+variations within those characteristics. These relative protection values are based on current pest and disease populations. These have been known to shift periodically and may cause changes in specific
+evaluations. Resistance to many other diseases and pests is sensitive to environmental conditions, plant development stages and the presence and intensity of other diseases which may result in specific
+evaluation inconsistencies. This chart is updated annually to reflect the most current trends.
+AgriPro hybrid wheat seed sold commercially contains 75-95% hybrid seed, as required by the Federal Seed Act. Plot trial data for AgriPro hybrids represents performance using seed lots with nearly
+100% hybrid seed.
+© 2025 Syngenta. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company. Some or all of the varieties may be protected under one or more of the following: Plant Variety
+Protection, United States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. NP - 10/2025
+
+Three-Year Performance Summary, Syngenta Data (2023-2025)
+South Dakota
+Yield Average bu/ac Economic Return1 Agronomics and Disease
+Protein Test Wt. Gross Heading Height Lodging BLS FHB
+Variety 3-yr 2-yr 2025 % lb/bu $/A Rank 1-9 1-9 1-9 1-9 1-9
+AgriPro HY141 65.0 65.7 59.4 15.4 60.2 370.0 3 5 6 6 5 4
+AP Dagr 63.1 62.5 56.4 15.6 59.8 364.2 10 6 4 5 4 5
+AgriPro HY162 62.7 61.4 54.8 15.7 59.9 364.5 9 5 6 5 5 4
+AP Iconic 62.2 62.1 54.1 16.2 60.1 368.4 5 5 6 3 4 4
+SY Valda 62.2 62.5 56.8 16.1 60.5 368.3 6 5 5 5 4 4
+AgriPro HY155 61.8 61.5 56.2 16.5 60.3 365.8 7 5 6 5 5 4
+AP Elevate 61.6 60.9 53.3 16.3 60.2 364.9 8 6 4 3 4 4
+AP Gunsmoke CL2 56.9 55.6 47.6 16.8 60.0 336.9 12 5 5 3 5 4
+AP Murdock 53.1 54.7 48.5 16.9 60.2 314.3 13 4 4 4 4 4
+AP Revolution 52.8 53.2 43.0 16.9 60.7 312.9 14 4 4 4 3 3
+SY Ingmar 52.4 51.7 44.3 17.2 60.7 309.9 15 5 5 3 3 3
+LCS Trigger 71.9 70.9 63.5 14.3 60.9 376.2 2 6 6 NA 4 NA
+Brawn-SD 64.5 62.1 58.8 15.5 61.7 369.3 4 5 NA NA 4 5
+Ascend-SD 64.4 62.5 54.7 16.7 60.8 381.2 1 6 8 7 3 4
+Driver 60.5 58.5 52.0 16.3 60.5 358.1 11 5 7 NA NA NA
+ND Stampede 60.2 5 5 5 4 5
+WB9641 57.0 6 5 4 6 5
+MN-Torgy 56.2 6 6 5 3 3
+WB9645 55.9 7 6 5 6 5
+WB9642 49.4 6 4 6 6 4
+WB9590 42.6 4 4 2 6 6
+Mean 61.0 60.4 53.7 16.2 60.4
+LSD (5%) 4.3 4.5 8.4 0.7 0.4
+CV (%) 7.7 7.9 9.74 0.8 2.2
+No. of Locs. 10 8 4 6 6
+Numbers in bold type are in the top yielding group and considered statistically similar.
+Numerical ratings: Heading: 1= early; Height: 1 = short; Lodging: 1 = no lodging; Disease 1 = tolerant
+2025 Locations: Agar, Miller, Northville, and Selby SD
+2024 Locations: Agar, Roscoe, Northville, and Selby, SD
+2023 Locations: Selby, and Webster, SD
+1 Economic return calculated by using the three-year yield average multiplied by the average grain price ($5.12/bu). (+) 8 cents per 1/5th premium over 14% protein, (-) 10 cents
+per 1/5 discount under 14% protein
+These agronomic assessments are made by Syngenta scientists and reflect each variety’s relative performance within these characteristics through the 2025crop year. Specific conditions may cause variations
+within those characteristics. These relative protection values are based on current pest and disease populations. These have been known to shift periodically and may cause changes in specific evaluations.
+Resistance to many other diseases and pests is sensitive to environmental conditions, plant development stages and the presence and intensity of other diseases which may result in specific evaluation
+inconsistencies. This chart is updated annually to reflect the most current trends.
+AgriPro hybrid wheat seed sold commercially contains 75-95% hybrid seed, as required by the Federal Seed Act. Plot trial data for AgriPro hybrids represents performance using seed lots with nearly 100%
+hybrid seed.
+© 2025 Syngenta. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company. Some or all of the varieties may be protected under one or more of the following: Plant Variety
+Protection, United States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. NP - 10/2025
+```
@@ -0,0 +1,36 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-2025-np-perf-data-web-east",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Performance Summary, Syngenta Data",
+  "filename": "2025%20NP%20Perf%20Data%20web%20East.pdf",
+  "region": null,
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Iconic",
+    "AP Elevate",
+    "SY Valda",
+    "AP Murdock",
+    "AP Smith",
+    "AP Dagr",
+    "AP Gunsmoke CL2",
+    "SY",
+    "SY Ingmar",
+    "LCS Boom"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20web%20East.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20web%20East.pdf"
+  ],
+  "page_text_chars": 7194,
+  "fetched_at": "2026-05-25T19:11:10.521992+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,114 @@
+# 2025 Performance Summary, Syngenta Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20web%20East.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Iconic, AP Elevate, SY Valda, AP Murdock, AP Smith, AP Dagr, AP Gunsmoke CL2, SY, SY Ingmar, LCS Boom
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Performance Summary, Syngenta Data
+Eastern North Dakota and Minnesota
+2025 Yield bu/ac
+Test
+Minnesota North Dakota
+Prot. Wt.
+Variety Avg. Crookston Glyndon Warren Wolverton Cando Casselton Langdon McVille Park River Thompson % lbs/bu
+AgriPro HY141 90.8 87.2 75.8 85.7 90.7 88.4 103.5 108.6 92.7 82.0 93.9 13.5 59.5
+AgriPro HY155 90.8 93.7 74.7 93.3 88.3 84.6 91.8 101.3 99.1 85.3 96.1 14.0 60.2
+AgriPro HY162 86.7 85.8 73.1 88.9 92.5 75.8 86.3 103.8 90.1 82.3 88.6 13.5 60.2
+AP Iconic 83.5 92.2 69.0 75.1 76.9 86.8 85.5 104.1 86.6 73.6 85.5 13.5 58.7
+AP Elevate 81.9 84.3 66.1 74.2 74.9 78.1 81.2 104.7 93.9 73.2 87.9 13.5 59.7
+SY Valda 81.2 74.6 71.6 94.7 73.2 81.0 82.8 91.0 82.5 72.9 87.3 13.9 58.4
+AP Murdock 80.2 90.0 64.7 85.2 78.6 75.7 82.3 96.2 87.4 55.3 87.1 13.5 59.5
+AP Smith 80.2 80.8 64.9 83.0 70.3 71.3 85.0 91.5 95.1 71.6 88.6 14.4 59.1
+AP Dagr 79.0 79.2 68.1 90.5 71.2 75.5 82.1 88.1 79.5 59.0 97.0 13.2 57.6
+AP Gunsmoke CL2 77.4 81.7 63.1 79.7 67.8 82.3 83.7 93.5 88.1 49.9 83.9 13.3 58.1
+SY 611 CL2 76.7 78.0 63.1 73.2 71.1 74.4 77.3 100.8 83.3 62.7 82.8 14.5 58.9
+SY Ingmar 74.8 70.0 62.1 80.8 66.6 69.4 85.0 89.0 73.1 65.0 86.7 14.5 59.1
+ND Stampede 87.1 86.8 69.0 90.3 88.7 77.2 91.0 100.5 100.9 76.2 90.4 15.1 58.8
+WB9645 85.7 96.2 72.7 92.2 73.9 74.2 95.1 103.0 99.2 69.1 81.4 13.3 58.9
+Ascend-SD 85.5 95.6 69.0 88.8 90.5 79.7 88.3 93.1 90.6 78.0 81.7 14.1 60.5
+WB9641 85.5 74.7 64.2 93.8 75.0 88.1 92.1 104.8 98.3 65.4 98.9 12.7 58.6
+WB9590 84.8 81.3 63.8 88.1 76.9 77.0 86.2 103.1 93.0 77.0 101.4 14.8 59.5
+WB9606 83.8 87.4 70.8 90.6 69.7 78.8 96.4 95.5 94.2 75.3 79.0 12.9 60.5
+Faller 82.5 88.9 62.2 92.1 69.4 83.8 83.0 98.6 87.6 66.5 92.6 14.0 58.9
+WB9642 81.9 83.7 65.7 92.0 77.8 81.1 80.8 91.9 85.2 73.2 88.0 13.6 60.9
+MN-Torgy 80.9 89.4 65.1 84.6 80.9 82.0 76.0 92.6 94.5 70.3 73.7 14.6 60.5
+MN-Rothsay 80.8 82.2 65.8 91.1 69.7 82.2 80.5 96.1 91.1 60.7 88.3 13.9 58.8
+WB9719 75.9 84.6 60.3 88.8 63.8 72.7 79.1 97.8 78.4 42.9 90.7 13.3 57.5
+LCS Boom 74.3 84.0 52.5 77.5 67.6 79.3 76.5 91.7 91.0 46.4 76.9 14.2 60.6
+ND Thresher 73.3 81.9 56.3 86.9 71.9 73.7 70.5 86.7 70.2 56.2 78.9 14.4 56.6
+Mean 82.2 84.8 66.4 86.9 76.6 79.2 85.2 97.5 89.2 68.3 87.6 13.8 59.2
+LSD (5%) 4.8 11.5 4.7 13.2 13.1 11.0 — 10.6 10.3 9.2 11.4 0.5 0.7
+CV (%) 6.5 6.6 4.3 7.3 8.2 8.4 12.1 6.6 7.0 7.8 6.4 6.9 2.1
+No. of Locs. 10 8 10
+Numbers in bold type are in the top yielding group and considered statistically similar.
+Numerical ratings: Heading: 1= Early, Height: 1 = Short
+These agronomic assessments are made by Syngenta scientists and reflect each variety’s relative performance within these characteristics through the 2025 crop year. Specific conditions may cause variations
+within those characteristics. These relative protection values are based on current pest and disease populations. These have been known to shift periodically and may cause changes in specific evaluations.
+Resistance to many other diseases and pests is sensitive to environmental conditions, plant development stages and the presence and intensity of other diseases which may result in specific evaluation
+inconsistencies. This chart is updated annually to reflect the most current trends.
+AgriPro hybrid wheat seed sold commercially contains 75-95% hybrid seed, as required by the Federal Seed Act. Plot trial data for AgriPro hybrids represents performance using seed lots with nearly 100%
+hybrid seed.
+© 2025 Syngenta. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company. Some or all of the varieties may be protected under one or more of the following: Plant Variety
+Protection, United States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. NP - 10/2025
+
+Three-Year Performance Summary, Syngenta Data (2023-2025)
+Eastern North Dakota and Minnesota
+Yield Average bu/ac Economic Return1 Agronomics and Disease
+Protein Test Wt. Heading Height Lodging BLS FHB
+Variety 3-yr 2-yr 2025 % lb/bu Gross $/A Rank 1-9 1-9 1-9 1-9 1-9
+AgriPro HY155 92.4 91.5 90.8 14.4 60.2 488.8 1 5 6 5 5 4
+AgriPro HY141 91.7 90.6 90.8 13.8 59.8 461.9 5 5 6 6 5 4
+AgriPro HY162 91.0 89.3 86.7 13.6 60.3 450.0 8 5 6 5 5 4
+AP Iconic 87.5 87.1 83.5 14.0 59.4 446.3 9 5 6 3 4 4
+AP Elevate 85.9 86.0 81.9 14.5 60.1 458.5 6 6 4 3 4 4
+AP Dagr 85.7 82.6 79.0 13.7 58.7 426.2 17 6 4 5 4 5
+SY Valda 85.5 84.5 81.2 14.2 58.8 446.2 10 5 5 5 4 4
+AP Smith 82.6 82.0 80.2 14.8 59.6 450.3 7 6 4 2 3 4
+AP Murdock 82.4 82.4 80.2 14.3 60.0 431.5 16 4 4 4 4 4
+AP Gunsmoke CL2 81.2 80.9 77.4 14.6 58.9 434.8 15 5 5 3 5 4
+SY 611 CL2 80.7 79.5 76.7 14.9 59.3 443.4 11 5 4 4 4 3
+SY Ingmar 79.8 79.7 74.8 15.0 59.7 440.1 13 5 5 3 3 3
+WB9606 87.7 85.8 83.8 13.8 60.9 438.9 14 5 6 5 6 5
+MN-Rothsay 86.3 84.3 80.8 14.8 59.9 468.5 3 7 3 3 4 5
+WB9590 85.5 84.4 84.8 15.1 59.3 476.8 2 4 4 2 6 6
+Faller 85.0 82.9 82.5 14.2 59.3 443.3 12 6 7 7 3 3
+MN-Torgy 84.0 82.4 80.9 15.1 60.9 466.3 4 6 6 5 3 3
+WB9719 81.6 77.9 75.9 14.0 58.6 417.1 18 6 5 2 5 6
+Ascend-SD 84.3 85.5 6 8 7 3 4
+ND Thresher 74.4 73.3 6 5 7 3 5
+ND Stampede 87.1 5 5 5 4 5
+WB9645 85.7 7 6 5 6 5
+WB9641 85.5 6 5 4 6 5
+WB9642 81.9 6 4 6 6 4
+LCS Boom 74.3 3 5 4 6 4
+Mean 85.4 83.6 82.5 14.6 59.7
+LSD (5%) 3.3 4.0 4.8 0.5 0.8
+CV (%) 6.7 6.9 6.5 2.8 2.1
+No. of Locs. 23 16 10 22 21
+Numbers in bold type are in the top yielding group and considered statistically similar.
+Numerical ratings: Heading: 1= early; Height: 1 = short; Disease: 1 = no disease
+2025 Locations: Crookston, Glyndon, Warren, and Wolverton MN; Cando, Casselton, Langdon, McVille, Park River, and Thompson ND
+2024 Locations: Casselton, Drayton, Langdon, and Park River, ND; Crookston and Warren, MN
+2023 Locations: Casselton, McVille, Park River, and Valley City, ND; Crookston, Glyndon, and Warren, MN
+1 Economic return calculated by using the three-year yield average multiplied by the average grain price ($5.12/bu). (+) 8 cents per 1/5th premium over 14% protein, (-) 10 cents
+per 1/5 discount under 14% protein.
+These agronomic assessments are made by Syngenta scientists and reflect each variety’s relative performance within these characteristics through the 2025 crop year. Specific conditions may cause
+variations within those characteristics. These relative protection values are based on current pest and disease populations. These have been known to shift periodically and may cause changes in specific
+evaluations. Resistance to many other diseases and pests is sensitive to environmental conditions, plant development stages and the presence and intensity of other diseases which may result in specific
+evaluation inconsistencies. This chart is updated annually to reflect the most current trends.
+AgriPro hybrid wheat seed sold commercially contains 75-95% hybrid seed, as required by the Federal Seed Act. Plot trial data for AgriPro hybrids represents performance using seed lots with nearly 100%
+hybrid seed.
+© 2025 Syngenta. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company. Some or all of the varieties may be protected under one or more of the following: Plant Variety
+Protection, United States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. NP - 10/2025
+```
@@ -0,0 +1,36 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-2025-np-perf-data-web-west",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Performance Summary, Syngenta Data",
+  "filename": "2025%20NP%20Perf%20Data%20web%20west.pdf",
+  "region": null,
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Iconic",
+    "AP Elevate",
+    "SY",
+    "SY Valda",
+    "AP Smith",
+    "AP Dagr",
+    "AP Gunsmoke CL2",
+    "AP Murdock",
+    "SY Ingmar",
+    "LCS Boom"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20web%20west.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20web%20west.pdf"
+  ],
+  "page_text_chars": 6380,
+  "fetched_at": "2026-05-25T19:11:11.464402+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,113 @@
+# 2025 Performance Summary, Syngenta Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-11/2025%20NP%20Perf%20Data%20web%20west.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Iconic, AP Elevate, SY, SY Valda, AP Smith, AP Dagr, AP Gunsmoke CL2, AP Murdock, SY Ingmar, LCS Boom
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Performance Summary, Syngenta Data
+Western North Dakota
+2025 Yield bu/ac
+North Dakota
+Prot. Test Wt.
+Variety Avg. Berthold Coleharbor Harvey New Leipzig Steele Velva % lbs/bu
+AgriPro HY162 78.9 45.9 110.4 89.1 67.3 61.1 99.3 14.6 60.2
+AgriPro HY155 77.5 45.4 110.9 85.1 65.2 60.3 98.0 15.3 59.7
+AP Iconic 75.8 50.2 100.4 88.9 67.4 55.2 92.7 14.5 59.9
+AgriPro HY141 75.1 46.8 101.8 75.8 68.4 59.1 98.6 14.3 60.0
+AP Elevate 74.6 52.8 104.9 81.6 57.1 61.4 89.6 14.9 60.7
+SY 611 CL2 73.3 54.0 98.7 74.3 66.3 55.9 90.5 15.5 60.3
+SY Valda 72.5 56.7 94.3 78.3 62.1 52.0 91.7 14.5 58.9
+AP Smith 72.1 56.9 98.2 81.9 46.9 58.8 90.1 15.2 59.9
+AP Dagr 70.7 59.2 94.3 63.9 60.9 53.3 92.4 14.4 59.6
+AP Gunsmoke CL2 70.5 51.2 92.5 77.9 61.0 53.5 87.0 15.5 60.5
+AP Murdock 69.2 50.7 97.5 69.7 64.7 48.1 84.2 15.0 60.8
+SY Ingmar 65.8 49.0 95.8 68.5 57.3 42.7 81.4 15.5 58.7
+ND Stampede 78.1 51.0 107.3 86.8 62.0 68.5 93.2 16.1 60.3
+WB9641 76.8 58.8 104.9 87.2 51.6 62.8 95.4 14.1 59.8
+Faller 76.5 47.1 98.6 85.1 63.6 68.1 96.6 15.2 60.4
+WB9645 75.6 51.3 100.9 76.0 63.4 58.9 102.8 14.1 60.6
+MN-Torgy 75.1 58.5 93.0 83.0 68.5 63.2 84.6 15.8 61.8
+LCS Boom 75.0 49.2 100.7 87.7 70.8 54.1 87.7 15.0 62.5
+WB9606 74.0 49.1 109.1 84.1 52.7 55.5 93.3 14.4 60.6
+Ascend-SD 73.0 50.7 98.9 84.4 50.3 68.4 85.0 15.1 62.1
+WB9590 72.2 52.6 104.4 74.8 59.4 49.8 92.1 15.6 60.4
+WB9642 71.8 48.0 96.3 66.9 72.3 57.1 90.4 14.9 60.4
+WB9719 71.7 50.4 98.6 71.1 69.1 53.2 87.9 15.0 59.7
+MN-Rothsay 71.0 48.0 100.7 89.1 36.5 61.4 90.5 13.5 60.4
+ND Thresher 68.4 49.1 93.5 68.8 58.3 55.6 85.0 15.8 59.2
+Mean 73.7 51.3 100.8 79.1 61.3 57.8 91.7 14.9 60.3
+LSD (5%) 6.6 10.4 12.5 8.9 — 6.2 1.1 1.6
+CV (%) 7.7 11.8 6.3 9.6 8.7 — 3.2 5.1 2.3
+No. of Locs. 6 5 6
+Numbers in bold type are in the top yielding group and considered statistically similar.
+Numerical ratings: Heading: 1= Early, Height: 1 = Short
+These agronomic assessments are made by Syngenta scientists and reflect each variety’s relative performance within these characteristics through the 2025 crop year. Specific conditions may cause variations
+within those characteristics. These relative protection values are based on current pest and disease populations. These have been known to shift periodically and may cause changes in specific evaluations.
+Resistance to many other diseases and pests is sensitive to environmental conditions, plant development stages and the presence and intensity of other diseases which may result in specific evaluation
+inconsistencies. This chart is updated annually to reflect the most current trends.
+AgriPro hybrid wheat seed sold commercially contains 75-95% hybrid seed, as required by the Federal Seed Act. Plot trial data for AgriPro hybrids represents performance using seed lots with nearly 100%
+hybrid seed.
+© 2025 Syngenta. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company. Some or all of the varieties may be protected under one or more of the following: Plant Variety
+Protection, United States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. NP - 10/2025
+
+Three-Year Performance Summary, Syngenta Data (2023-2025)
+Western North Dakota
+Yield Average bu/ac Economic Return1 Agronomics and Disease
+Protein Test Wt. Heading Height Lodging BLS FHB
+Variety 3-yr 2-yr 2025 % lb/bu Gross $/A Rank 1-9 1-9 1-9 1-9 1-9
+AgriPro HY162 84.9 81.3 78.9 14.2 60.0 440.5 4 5 6 5 5 4
+AP Iconic 83.4 78.5 75.8 14.3 59.9 438.3 7 5 6 3 4 4
+AgriPro HY141 83.3 79.6 75.1 14.1 59.9 430.5 11 5 6 6 5 4
+AgriPro HY155 82.5 79.4 77.5 14.8 59.4 449.9 2 5 6 5 5 4
+AP Elevate 80.4 76.9 74.6 14.8 60.3 438.6 6 6 4 3 4 4
+AP Dagr 79.8 73.4 70.7 14.1 59.5 412.3 16 6 4 5 4 5
+SY Valda 79.5 73.4 72.5 14.3 59.1 416.3 15 5 5 5 4 4
+SY 611 CL2 78.2 73.5 73.3 15.1 59.7 435.7 8 5 4 4 4 3
+AP Smith 77.9 74.0 72.1 15.0 59.8 431.3 10 6 4 2 3 4
+AP Gunsmoke CL2 76.9 72.8 70.5 15.4 60.1 435.7 9 5 5 3 5 4
+AP Murdock 76.6 74.1 69.2 14.9 60.5 418.6 14 4 4 4 4 4
+SY Ingmar 74.7 71.4 65.8 15.4 59.5 424.5 13 5 5 3 3 3
+WB9606 82.9 78.6 74.0 14.1 60.2 429.1 12 5 6 5 6 5
+Faller 81.9 76.9 76.5 14.7 59.8 443.0 3 6 7 7 3 3
+WB9719 80.6 75.7 71.7 14.9 59.4 440.1 5 6 5 2 5 6
+WB9590 78.4 75.7 72.2 15.7 59.9 453.6 1 4 4 2 6 6
+MN-Torgy 77.2 75.1 6 6 5 3 3
+Ascend-SD 75.0 73.0 6 8 7 3 4
+MN-Rothsay 74.0 71.0 7 3 3 4 5
+ND Thresher 69.2 68.4 6 5 7 3 5
+ND Stampede 78.1 5 5 5 4 5
+WB9641 76.8 6 5 4 6 5
+WB9645 75.6 7 6 5 6 5
+LCS Boom 75.0 3 5 4 6 4
+WB9642 71.8 6 4 6 6 4
+Mean 80.1 75.5 73.7 14.7 59.8
+LSD (5%) 4.3 5.7 6.6 0.5 1.2
+CV (%) 6.9 8.1 7.7 5.9 2.2
+No. of Locs. 13 9 6 8 9
+Numbers in bold type are in the top yielding group and considered statistically similar.
+Numerical ratings: Heading: 1= early; Height: 1 = short; Disease: 1 = no disease
+2025 Locations: Berthold, Coleharbor, Harvey, New Leipzig, Steele, and Velva ND
+2024 Locations: Coleharbor, Harvey, and Velva, ND
+2023 Locations: Berthold, Coleharbor, New Leipzig, and Velva, ND
+1 Economic return calculated by using the three-year yield average multiplied by the average grain price ($5.12/bu). (+) 8 cents per 1/5th premium over 14% protein, (-) 10 cents
+per 1/5 discount under 14% protein.
+These agronomic assessments are made by Syngenta scientists and reflect each variety’s relative performance within these characteristics through the 2025 crop year. Specific conditions may cause
+variations within those characteristics. These relative protection values are based on current pest and disease populations. These have been known to shift periodically and may cause changes in specific
+evaluations. Resistance to many other diseases and pests is sensitive to environmental conditions, plant development stages and the presence and intensity of other diseases which may result in specific
+evaluation inconsistencies. This chart is updated annually to reflect the most current trends.
+AgriPro hybrid wheat seed sold commercially contains 75-95% hybrid seed, as required by the Federal Seed Act. Plot trial data for AgriPro hybrids represents performance using seed lots with nearly 100%
+hybrid seed.
+© 2025 Syngenta. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company. Some or all of the varieties may be protected under one or more of the following: Plant Variety
+Protection, United States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. NP - 10/2025
+```
@@ -0,0 +1,33 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-central-plains-dryland-2025-r1",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Central Plains Dryland Summary, Three-Year Data",
+  "filename": "Central%20Plains%20Dryland%202025%20r1.pdf",
+  "region": "Central Plains",
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "SY Wolverine",
+    "AP Roadrunner",
+    "AP Sunbird",
+    "AP Bigfoot",
+    "AP Prolific",
+    "SY Monument",
+    "LCS Atomic AX"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-07/Central%20Plains%20Dryland%202025%20r1.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-07/Central%20Plains%20Dryland%202025%20r1.pdf"
+  ],
+  "page_text_chars": 2530,
+  "fetched_at": "2026-05-25T19:11:09.410687+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,56 @@
+# 2025 Central Plains Dryland Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Region:** Central Plains
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-07/Central%20Plains%20Dryland%202025%20r1.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** SY Wolverine, AP Roadrunner, AP Sunbird, AP Bigfoot, AP Prolific, SY Monument, LCS Atomic AX
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Central Plains Dryland Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Belleville, Junction City, Pratt, Salina,
+Variety (2023-2025) (2024-2025) (2025) KS* KS KS KS
+Hard Winter Wheat Yield TWT Yield TWT Yield TWT Yield Yield Yield Yield
+Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A Bu/A Bu/A
+AP24 AX 63.9 58.8 70.7 58.9 73.8 55.3 64.8 94.7 59.0 76.7
+SY Wolverine 62.0 60.6 66.2 60.6 66.1 56.9 58.2 86.2 67.9 51.9
+AP Roadrunner 61.3 57.8 64.9 57.4 61.3 53.9 54.1 79.7 52.9 58.5
+AP Sunbird 61.2 61.0 67.2 61.3 66.6 57.9 59.0 86.7 54.3 66.5
+AP Bigfoot 60.0 61.3 65.2 61.5 64.7 59.0 53.1 86.6 53.3 65.9
+AP Prolific 59.6 60.4 64.1 60.4 61.8 58.2 46.0 86.2 45.8 69.2
+SY Monument 59.2 59.6 62.5 59.8 56.8 55.9 48.2 71.6 48.9 58.6
+Bob Dole 56.4 59.1 60.2 58.9 57.7 55.2 47.0 68.3 50.9 64.6
+Showdown 62.9 60.1 69.2 60.1 65.2 55.7 56.4 83.0 54.7 66.6
+Rockstar 61.7 58.8 67.4 59.1 65.5 55.8 54.0 83.8 55.9 68.3
+KS Providence 61.1 60.4 66.3 60.3 65.2 57.2 52.5 88.9 59.5 59.7
+WB4401 60.4 60.3 65.5 60.2 61.5 56.1 51.7 78.8 57.0 58.5
+LCS Atomic AX 59.4 61.7 65.2 61.8 65.1 59.2 52.3 88.0 50.0 70.1
+WB4523 58.2 59.5 62.8 59.6 57.5 56.2 40.6 68.2 60.0 61.2
+WB4422 69.6 59.7 71.0 56.3 62.5 87.3 63.6 70.6
+KS Bill Snyder 73.1 59.0 59.3 94.6 57.4 81.2
+WB4699 64.0 55.3 51.0 84.2 56.9 64.1
+High Cotton 63.8 58.2 43.8 90.9 59.4 61.2
+Polansky Goldenhawk 63.0 56.4 52.7 86.5 55.9 56.8
+Doublestop CLP 60.7 57.7 53.9 74.0 51.3 63.4
+Mean General 60.6 60.0 65.9 60.0 63.7 56.7 51.7 83.6 54.3 65.4
+LSD General (5%) EE 3.9 1.1 4.6 1.2 8.3 2.7 9.5 10.7 8.1 9.9
+CV (Effective) 9.0 2.4 8.8 2.5 9.2 3.3 11.2 7.8 9.1 9.2
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+* Location was affected by a Wheat Streak Mosaic Virus infestation, which resulted in reduced yield of susceptible varieties.
+Locations
+2023 — Belleville, Conway Springs, Junction City, and Salina, KS; Carrier, OK
+2024 — Belleville, Conway Springs, Junction City, Palco, Pratt, and Salina, KS; Carrier, OK
+2025 — Belleville, Junction City, Pratt, and Salina, KS
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,32 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-montana-2025-web",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Montana Summary, Three-Year Data",
+  "filename": "Montana%202025%20web.pdf",
+  "region": "Montana",
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Solid",
+    "SY Monument",
+    "AP Sunbird",
+    "SY",
+    "LCS Steel AX",
+    "LCS Julep"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-08/Montana%202025%20web.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-08/Montana%202025%20web.pdf"
+  ],
+  "page_text_chars": 1922,
+  "fetched_at": "2026-05-25T19:11:12.271213+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,53 @@
+# 2025 Montana Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Region:** Montana
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-08/Montana%202025%20web.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Solid, SY Monument, AP Sunbird, SY, LCS Steel AX, LCS Julep
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Montana Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Fort Benton, Conrad, Billings, Sawfly
+Variety (2023-2025) (2024-2025) (2025) MT MT MT Protein Damage
+Hard Red Yield Yield Yield TWT Yield Yield Yield % 1-9
+Winter Wheat Bu/A Bu/A Bu/A Lb/Bu Bu/A Bu/A Bu/A
+AP24 AX 63.4 62.1 71.8 61.3 59.5 47.0 109.0 12.2 5
+AP Solid 63.4 61.9 71.6 63.9 58.7 43.0 113.1 13.4 4
+SY Monument 62.5 62.5 72.9 61.6 58.9 42.4 117.3 12.1 5
+AP Sunbird 61.5 61.8 70.7 61.1 61.7 38.9 111.4 12.6 6
+AP18 AX 59.0 58.3 68.5 62.9 56.3 41.2 108.1 12.7 6
+SY 517 CL2 53.4 53.1 63.4 56.3 55.4 33.7 101.2 13.9 5
+Keldin 65.6 63.5 75.0 61.9 69.5 39.4 115.9 12.9 5
+Bobcat 63.5 63.2 73.2 62.5 68.5 47.8 103.4 13.1 2
+MT WarCat 61.4 59.5 69.7 62.9 58.6 42.3 108.4 13.2 3
+Warhorse 57.9 55.3 64.5 54.8 57.1 32.8 103.6 14 2
+WB4523 63.8 76.9 62.0 69.8 42.4 118.6 11.6 4
+WB4483 60.0 68.4 54.8 61.0 35.9 108.1 13.8 5
+StandClear CLP 59.2 68.2 62.6 61.2 39.7 103.8 13.2 5
+Scorpio 56.9 68.1 53.6 61.9 34.2 108.2 12.5 6
+WB4733 CLP 56.3 64.5 62.3 55.2 38.3 99.9 13.9 4
+DG Ramsay 76.9 62.0 73.4 37.5 119.9 13 5
+LCS Steel AX 75.2 62.7 62.0 44.4 119.2 12.2 5
+4739AX 73.9 62.8 67.6 43.2 110.8 13.3 4
+WB4510CLP 72.3 63.2 64.1 34.5 118.4 12.2 6
+LCS Julep 69.9 63.2 62.8 39.1 107.9 13.4 5
+Sawfly: Locations
+1-2 = Excellent 2023 — Conrad and Fort Benton, MT
+3-4 = Very Good 2024 — Billings, Chester, Conrad, and Fort Benton, MT
+5 = Good 2025 — Billings, Conrad, and Fort Benton, MT
+6-7 = Fair
+8-9 = Poor
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,33 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-ne-colorado-2025",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Northeast Colorado Dryland Summary, Three-Year Data",
+  "filename": "NE%20Colorado%202025.pdf",
+  "region": "NE Colorado",
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Sunbird",
+    "AP Bigfoot",
+    "SY Wolverine",
+    "AP Solid",
+    "AP Roadrunner",
+    "SY Monument",
+    "WB-Grainfield"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-07/NE%20Colorado%202025.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-07/NE%20Colorado%202025.pdf"
+  ],
+  "page_text_chars": 2389,
+  "fetched_at": "2026-05-25T19:11:01.256427+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,58 @@
+# 2025 Northeast Colorado Dryland Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Region:** NE Colorado
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-07/NE%20Colorado%202025.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Sunbird, AP Bigfoot, SY Wolverine, AP Solid, AP Roadrunner, SY Monument, WB-Grainfield
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Northeast Colorado Dryland Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Crook, Julesburg, Yuma,
+Variety (2023-2025) (2024-2025) (2025) CO CO* CO
+Hard Winter Wheat Yield TWT Yield TWT Yield TWT Yield Yield
+Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A
+AP Sunbird 81.5 59.5 82.7 60.0 86.5 57.9 61.6 102.9 95.1
+AP24 AX 79.2 56.8 79.8 57.1 86.7 54.9 63.7 97.9 98.5
+AP18 AX 78.5 57.2 78.7 57.4 85.0 55.2 59.5 101.2 94.3
+AP Bigfoot 76.5 59.0 76.6 58.9 79.0 56.6 60.4 86.6 90.0
+SY Wolverine 75.5 59.1 77.1 59.7 80.5 57.2 61.9 91.0 88.5
+AP Solid 73.3 59.2 73.9 59.4 76.9 56.4 62.4 86.0 82.4
+AP Roadrunner 72.3 56.8 73.6 56.7 80.1 54.6 63.9 90.5 86.0
+SY Monument 67.5 58.2 65.4 58.6 70.3 56.7 62.4 67.7 80.7
+AG Golden 78.3 56.4 79.0 56.7 86.1 54.9 71.2 93.6 93.4
+Langin 78.2 57.4 81.4 57.7 86.7 55.8 62.6 95.5 102.0
+WB4422 77.3 59.5 78.4 59.9 83.2 57.7 65.8 90.7 92.9
+KS Dallas 76.3 59.7 72.9 59.5 76.0 57.4 55.0 82.3 90.8
+WB4595 75.8 60.2 76.9 60.2 81.4 57.3 63.7 90.1 90.4
+High Country 75.4 59.2 75.1 59.1 79.2 57.0 60.4 89.6 87.7
+Amplify SF 73.7 58.8 72.1 59.0 73.8 56.5 61.6 77.7 82.2
+KS Hamilton 72.2 58.5 71.1 58.5 76.3 56.1 54.5 78.0 96.3
+TAM 115 65.5 60.4 63.8 60.2 70.5 58.3 49.8 85.0 76.6
+Kivari AX 78.1 57.7 83.3 55.9 63.3 87.1 99.5
+WB-Grainfield 86.3 57.3 59.0 99.8 100.0
+Canvas 85.1 55.9 67.4 94.4 93.7
+KS Bill Snyder 80.4 56.9 63.2 92.9 85.3
+KS Mako 78.4 57.2 58.1 84.6 92.3
+Mean General 75.2 58.6 75.5 58.7 79.5 56.4 60.4 88.8 89.4
+LSD General (5%) EE 5.5 1.2 6.2 1.5 9.6 0.0 8.3 16.0 13.0
+CV (Effective) 8.1 1.9 8.6 2.0 9.9 2.4 8.3 11.0 8.9
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+* Location was affected by a Wheat Streak Mosaic Virus infestation, which resulted in reduced yield of susceptible varieties.
+Locations
+2023 — Julesburg and Yuma, CO; Colby, KS
+2024 — Crook and Julesburg, CO; Ingalls, KS
+2025 — Crook, Julesburg, and Yuma, CO
+© 2024 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,33 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-plains-irrigated-2025",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Plains Irrigated Summary, Three-Year Data",
+  "filename": "Plains%20Irrigated%202025.pdf",
+  "region": "Plains Irrigated",
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "SY Wolverine",
+    "AP Sunbird",
+    "AP Prolific",
+    "AP Bigfoot",
+    "SY Grit",
+    "AP Roadrunner",
+    "SY Monument"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-07/Plains%20Irrigated%202025.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-07/Plains%20Irrigated%202025.pdf"
+  ],
+  "page_text_chars": 2164,
+  "fetched_at": "2026-05-25T19:11:03.219401+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,52 @@
+# 2025 Plains Irrigated Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Region:** Plains Irrigated
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-07/Plains%20Irrigated%202025.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** SY Wolverine, AP Sunbird, AP Prolific, AP Bigfoot, SY Grit, AP Roadrunner, SY Monument
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Plains Irrigated Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Hugoton, Scott City, Imperial, Dalhart,
+Variety (2023-2025) (2024-2025) (2025) KS KS NE TX
+Hard Winter Wheat Yield TWT Yield TWT Yield TWT Yield Yield Yield Yield
+Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A Bu/A Bu/A
+SY Wolverine 95.0 57.6 94.8 58.6 94.5 59.9 99.9 102.4 95.4 80.3
+AP Sunbird 93.9 58.8 94.7 59.1 89.5 59.7 74.8 107.8 96.8 78.5
+AP Prolific 93.6 59.8 92.6 60.1 92.3 61.3 104.9 95.7 92.6 76.0
+AP Bigfoot 90.9 59.1 90.5 59.2 87.3 59.7 67.6 111.3 91.7 78.7
+SY Grit 89.2 58.1 90.9 58.7 91.8 58.9 96.4 94.8 96.9 79.0
+AP Roadrunner 88.7 56.7 89.3 57.2 81.7 57.1 57.6 108.2 83.8 77.1
+SY Monument 83.8 57.1 83.0 57.7 79.3 59.5 77.3 79.6 83.7 76.6
+WB4422 94.9 59.2 95.8 60.0 90.9 61.1 107.0 98.5 89.0 69.1
+TAM 114 91.7 60.7 93.6 61.2 89.1 61.7 77.6 107.9 92.5 78.3
+Canvas 89.6 58.0 92.2 59.2 84.5 59.4 68.1 101.9 86.1 81.7
+WB4792 89.3 56.8 92.1 58.0 88.3 57.9 94.6 104.7 73.0 80.8
+Epoch 88.9 58.4 88.5 58.9 88.6 59.6 101.9 97.4 87.0 68.0
+Langin 88.5 58.8 90.8 59.4 84.9 60.1 62.9 99.3 91.9 85.5
+TAM 115 76.3 59.2 76.2 59.7 76.5 62.0 63.8 93.4 75.4 73.5
+WB4523 93.5 58.4 90.9 111.5 93.4 78.1
+WB4303 93.1 57.4 102.9 93.8 95.7 80.2
+KS Mako 90.1 60.7 88.9 101.2 96.8 73.3
+Mean General 88.9 57.8 90.0 58.5 87.5 59.2 85.9 99.3 87.6 77.1
+LSD General (5%) EE 8.0 1.8 9.2 1.9 13.2 2.3 18.8 9.4 8.8 8.6
+CV (Effective) 10.2 3.5 10.6 3.0 8.5 2.6 13.4 5.8 6.1 6.8
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+Locations
+2023 — Ingalls, KS; Imperial, NE
+2024 — Dalhart, TX; Hugoton and Ingalls, KS; Imperial, NE
+2025 — Hugoton and Scott City, KS; Imperial, NE; Dalhart, TX
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,34 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-sc-ks-nc-ok-2024-0",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2024 South-Central Kansas, North-Central Oklahoma Summary, Three-Year Data",
+  "filename": "SC%20KS%20NC%20OK%202024_0.pdf",
+  "region": null,
+  "wheat_class_section": null,
+  "year": 2024,
+  "years_covered": [
+    2024
+  ],
+  "varieties_found": [
+    "SY Monument",
+    "AP Prolific",
+    "AP Roadrunner",
+    "SY Wolverine",
+    "AP Sunbird",
+    "AP EverRock",
+    "AP Bigfoot",
+    "LCS Atomic AX"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2024-07/SC%20KS%20NC%20OK%202024_0.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2024-07/SC%20KS%20NC%20OK%202024_0.pdf"
+  ],
+  "page_text_chars": 2157,
+  "fetched_at": "2026-05-25T19:11:08.283651+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,54 @@
+# 2024 South-Central Kansas, North-Central Oklahoma Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Year:** 2024
+- **PDF:** https://agriprowheat.com/sites/default/files/2024-07/SC%20KS%20NC%20OK%202024_0.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** SY Monument, AP Prolific, AP Roadrunner, SY Wolverine, AP Sunbird, AP EverRock, AP Bigfoot, LCS Atomic AX
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2024 South-Central Kansas, North-Central Oklahoma Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2022-2024
+3-Yr Combined 2-Yr Combined Combined Conway Pratt, Carrier,
+Variety (2022-2024) (2023-2024) (2024) Springs, KS KS OK
+Hard Winter Wheat Yield TWT Yield TWT Yield TWT Yield Yield Yield
+Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A Bu/A
+AP24 AX 57.6 62.7 54.1 62.4 62.6 63.7 75.2 36.5 76.2
+SY Monument 57.5 63.7 56.9 63.7 63.2 64.8 63.8 46.9 79.0
+AP Prolific 57.3 64.1 55.7 63.7 61.8 64.7 61.5 42.5 81.4
+AP Roadrunner 56.4 61.4 54.0 60.6 59.0 61.0 63.8 34.8 78.3
+SY Wolverine 55.8 64.5 52.8 64.2 58.7 65.6 56.6 44.6 75.0
+AP18 AX 55.4 63.0 52.8 62.9 62.2 64.2 70.7 37.3 78.5
+AP Sunbird 53.7 64.0 52.0 64.1 62.0 66.1 69.5 45.5 70.9
+Bob Dole 53.6 62.9 53.5 62.5 60.6 63.6 62.0 40.1 79.7
+AP EverRock 52.4 63.6 50.8 63.2 58.4 64.6 60.0 37.5 77.7
+AP Bigfoot 52.0 63.9 51.3 63.9 61.0 65.6 61.7 45.3 76.0
+WB4401 53.6 63.7 52.3 64.4 59.7 65.9 63.2 31.7 84.1
+Showdown 59.7 64.4 69.7 65.6 77.0 47.2 85.1
+Rockstar 56.5 62.4 64.2 63.1 62.9 49.3 80.4
+KS Providence 56.0 63.4 64.4 64.4 71.1 38.7 83.4
+LCS Atomic AX 54.3 64.8 62.3 66.2 65.8 42.9 78.2
+WB4523 52.9 63.7 60.5 65.0 56.2 39.9 85.4
+KS Hatchett 52.9 63.5 60.8 64.5 65.8 39.5 77.0
+WB4422 61.3 64.6 63.5 43.5 77.0
+KS Mako 59.0 65.5 58.7 49.9 68.3
+Mean General 55.0 63.4 53.8 63.5 59.7 64.0 62.2 41.2 75.7
+LSD General (5%) EE NS 1.4 NS 1.9 8.5 3.7 7.7 8.6 9.3
+CV (Effective) 7.9 1.7 8.7 2.0 8.8 2.2 7.6 12.8 7.5
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+NS = Non Significant
+Locations
+2022 — Conway Springs and Partridge, KS; Carrier, OK
+2023 — Conway Springs, KS; Carrier, OK
+2024 — Conway Springs and Pratt, KS; Carrier, OK
+© 2024 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,36 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-south-dakota-2025",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 South Dakota Winter Wheat Summary, Three-Year Data",
+  "filename": "South%20Dakota%202025.pdf",
+  "region": null,
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Prolific",
+    "AP Sunbird",
+    "AP Bigfoot",
+    "SY",
+    "SY Wolverine",
+    "SY WOLF",
+    "SY Monument",
+    "AP Clair",
+    "AP Solid",
+    "LCS Helix AX"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-08/South%20Dakota%202025.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-08/South%20Dakota%202025.pdf"
+  ],
+  "page_text_chars": 1916,
+  "fetched_at": "2026-05-25T19:11:14.252920+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,52 @@
+# 2025 South Dakota Winter Wheat Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-08/South%20Dakota%202025.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Prolific, AP Sunbird, AP Bigfoot, SY, SY Wolverine, SY WOLF, SY Monument, AP Clair, AP Solid, LCS Helix AX
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 South Dakota Winter Wheat Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Agar, Presho,
+Variety (2023-2025) (2024-2025) (2025) SD SD
+Hard Winter Wheat Yield TWT Yield TWT Yield TWT Yield Yield
+Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A
+AP18 AX 57.3 59.3 64.7 58.6 57.2 54.2 52.5 61.9
+AP24 AX 56.8 59.0 64.2 57.8 61.2 53.9 59.9 62.5
+AP Prolific 56.1 59.5 62.9 58.8 58.6 54.6 56.1 61.1
+AP Sunbird 55.9 59.5 58.5 59.1 58.4 56.1 56.8 59.9
+AP Bigfoot 55.6 59.6 62.9 58.9 64.1 55.9 62.2 66.1
+SY 517 CL2 52.5 60.8 56.6 60.3 59.9 57.8 60.0 59.7
+SY Wolverine 52.3 58.5 56.9 58.5 53.5 55.4 47.5 59.5
+SY WOLF 51.4 59.1 55.5 57.9 53.5 53.7 49.4 57.6
+SY Monument 50.1 57.3 56.1 55.9 56.6 51.9 54.7 58.6
+AP Clair 49.2 59.7 57.8 59.5 52.9 56.2 50.6 55.1
+AP Solid 54.7 56.8 47.8 61.7
+WB4422 58.2 59.9 63.8 58.4 65.3 55.5 63.5 67.1
+LCS Helix AX 57.2 61.1 66.0 60.6 65.2 57.9 65.0 65.3
+Winner 56.5 60.5 66.7 59.7 65.9 57.0 68.7 63.1
+SD Andes 55.7 60.6 60.9 59.8 54.2 55.8 50.3 58.1
+SD Midland 54.6 59.8 59.4 58.7 54.4 54.1 49.7 59.0
+Kivari AX 54.3 56.8 50.7 53.2 44.5 56.9
+SD Pheasant 54.1 56.4 49.7 58.5
+Mean General 54.6 59.6 60.4 58.5 57.7 55.2 55.2 60.3
+LSD General (5%) EE 5.4 1.2 7.7 1.5 7.4 1.8 13.0 6.1
+CV (Effective) 10.3 1.8 8.7 1.9 11.2 2.0 14.3 6.2
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+Locations
+2023 — Hayes and Ideal, SD
+2024 — Hayes and Ideal, SD
+2025 — Agar and Presho, SD
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,40 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-southern-idaho-2025",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Southern Idaho Summary, Three-Year Data",
+  "filename": "Southern%20Idaho%202025.pdf",
+  "region": "Southern Idaho",
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Exceed",
+    "AP Olympia",
+    "SY Dayton",
+    "SY Assure",
+    "SY Ovation",
+    "AP Iliad",
+    "SY Raptor",
+    "LCS Shine",
+    "LCS Hulk",
+    "LCS Artdeco",
+    "Norwest Duet",
+    "Norwest Tandem",
+    "LCS Jefe",
+    "LCS Kamiack"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-09/Southern%20Idaho%202025.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-09/Southern%20Idaho%202025.pdf"
+  ],
+  "page_text_chars": 2095,
+  "fetched_at": "2026-05-25T19:11:06.237182+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,49 @@
+# 2025 Southern Idaho Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Region:** Southern Idaho
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-09/Southern%20Idaho%202025.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Exceed, AP Olympia, SY Dayton, SY Assure, SY Ovation, AP Iliad, SY Raptor, LCS Shine, LCS Hulk, LCS Artdeco, Norwest Duet, Norwest Tandem, LCS Jefe, LCS Kamiack
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Southern Idaho Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Blackfoot, Nampa, Rupert, Twin Falls,
+Variety (2023-2025) (2024-2025) (2025) ID ID ID ID
+Soft White Yield TWT Yield TWT Yield TWT Yield Yield Yield Yield
+Winter Wheat Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A Bu/A Bu/A
+AP Exceed 166.9 62.2 165.3 62.6 177.8 62.1 179.0 176.4 141.9 213.7
+AP Olympia 164.9 61.0 163.8 61.4 181.2 60.8 183.6 163.9 156.7 220.5
+SY Dayton 161.5 61.2 160.4 61.4 174.9 60.5 176.4 177.4 146.4 199.5
+SY Assure 161.5 62.0 158.7 61.9 174.7 61.5 180.2 165.2 155.6 197.7
+SY Ovation 160.2 61.1 155.7 60.8 169.2 59.9 178.2 175.0 121.7 202.0
+AP Iliad 160.1 61.4 157.0 61.6 167.9 60.7 177.6 175.6 108.9 209.4
+SY Raptor 153.1 59.6 150.9 59.7 160.7 58.9 175.5 165.3 130.5 171.5
+LCS Shine 164.0 61.3 164.6 61.5 170.7 61.0 165.9 160.6 166.9 189.5
+LCS Hulk 161.7 62.6 159.9 62.8 171.1 62.8 164.2 181.5 146.9 192.0
+LCS Artdeco 157.6 61.5 156.5 61.5 164.2 60.9 164.6 182.7 131.1 178.3
+Norwest Duet 154.8 61.2 155.1 61.5 166.2 61.1 170.4 159.8 139.6 194.9
+Norwest Tandem 152.2 60.8 149.6 61.2 155.0 60.3 151.6 152.2 121.8 194.2
+LCS Jefe 165.5 62.6 180.8 61.8 174.2 160.8 169.7 218.5
+LCS Kamiack 159.8 61.9 174.9 61.5 169.3 176.8 143.5 209.9
+Mean General 160.9 61.4 159.4 61.6 170.9 61.0 171.0 169.4 141.4 201.8
+LSD General (5%) EE ns 1.1 ns 1.1 14.1 1.3 12.5 ns ns ns
+CV (Effective) 6.9 2.1 7.2 1.8 8.4 1.7 3.5 5.5 14.5 7.6
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+Locations
+2023 — Twin Falls, ID
+2024 — Blackfoot and Twin Falls, ID
+2025 — Blackfoot, Nampa, Rupert, and Twin Falls, ID
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,40 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-washington-n-idaho-2025",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Washington/Northern Idaho Summary, Three-Year Data",
+  "filename": "Washington%3AN%20Idaho%202025.pdf",
+  "region": null,
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "SY Raptor",
+    "AP Olympia",
+    "AP Exceed",
+    "SY Ovation",
+    "SY Dayton",
+    "AP Iliad",
+    "SY Assure",
+    "Norwest Duet",
+    "LCS Artdeco",
+    "LCS Shine",
+    "LCS Hulk",
+    "Norwest Tandem",
+    "LCS Kamiack",
+    "LCS Jefe"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-08/Washington%3AN%20Idaho%202025.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-08/Washington%3AN%20Idaho%202025.pdf"
+  ],
+  "page_text_chars": 1892,
+  "fetched_at": "2026-05-25T19:11:05.110770+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,48 @@
+# 2025 Washington/Northern Idaho Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-08/Washington%3AN%20Idaho%202025.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** SY Raptor, AP Olympia, AP Exceed, SY Ovation, SY Dayton, AP Iliad, SY Assure, Norwest Duet, LCS Artdeco, LCS Shine, LCS Hulk, Norwest Tandem, LCS Kamiack, LCS Jefe
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Washington/Northern Idaho Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Genesee, Walla Walla,
+Variety (2023-2025) (2024-2025) (2025) ID WA
+Soft White Yield TWT Yield TWT Yield TWT Yield Yield
+Winter Wheat Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A
+SY Raptor 146.1 63.0 157.6 64.8 156.9 65.0 157.4 156.3
+AP Olympia 142.2 64.2 154.3 66.1 151.1 65.8 159.6 142.5
+AP Exceed 141.8 63.6 155.3 65.4 152.6 65.3 160.0 145.2
+SY Ovation 140.8 63.3 148.7 65.4 147.4 65.7 154.9 139.8
+SY Dayton 140.0 63.6 158.4 65.6 157.7 65.8 172.3 143.1
+AP Iliad 139.8 63.4 151.0 65.3 147.0 65.2 149.4 144.6
+SY Assure 138.7 64.3 152.0 66.3 150.9 66.0 149.6 152.1
+Norwest Duet 144.1 62.3 157.4 64.7 155.3 65.0 157.5 153.1
+LCS Artdeco 140.3 62.6 155.5 64.4 157.5 64.8 160.9 154.0
+LCS Shine 139.3 63.1 148.6 64.7 150.7 65.2 146.1 155.4
+LCS Hulk 138.4 63.9 152.4 65.8 156.6 65.9 167.2 146.0
+Norwest Tandem 137.0 62.7 152.9 65.0 157.3 65.3 166.1 148.5
+LCS Kamiack 165.0 66.5 174.3 66.2 188.8 159.7
+LCS Jefe 160.1 65.2 167.4 66.0 178.9 155.9
+Mean General 142.5 63.3 156.7 65.3 157.3 65.5 162.0 152.7
+LSD General (5%) EE 8.6 1.0 ns 1.4 ns ns ns ns
+CV (Effective) 6.1 1.6 5.4 1.1 7.5 1.1 8.4 6.5
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+Locations
+2023 — Craigmont and Genesee, ID; Moses Lake and Walla Walla, WA
+2024 — Craigmont, ID; Walla Walla, WA
+2025 — Genesee, ID; Walla Walla, WA
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,33 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-western-plains-dryland-2025-0",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Western Plains Dryland Summary, Three-Year Data",
+  "filename": "Western%20Plains%20Dryland%202025_0.pdf",
+  "region": "Western Plains",
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Sunbird",
+    "AP Bigfoot",
+    "SY Wolverine",
+    "AP Roadrunner",
+    "AP Solid",
+    "SY Monument",
+    "WB-Grainfield"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-07/Western%20Plains%20Dryland%202025_0.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-07/Western%20Plains%20Dryland%202025_0.pdf"
+  ],
+  "page_text_chars": 2395,
+  "fetched_at": "2026-05-25T19:11:02.169343+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,58 @@
+# 2025 Western Plains Dryland Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Region:** Western Plains
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-07/Western%20Plains%20Dryland%202025_0.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Sunbird, AP Bigfoot, SY Wolverine, AP Roadrunner, AP Solid, SY Monument, WB-Grainfield
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Western Plains Dryland Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Crook, Julesburg, Yuma,
+Variety (2023-2025) (2024-2025) (2025) CO CO* CO
+Hard Winter Wheat Yield TWT Yield TWT Yield TWT Yield Yield Yield
+Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A Bu/A
+AP18 AX 74.2 57.6 75.8 57.8 85.0 55.2 59.5 101.2 94.3
+AP Sunbird 74.1 59.5 77.2 59.8 86.5 57.9 61.6 102.9 95.1
+AP24 AX 73.2 56.7 74.0 56.8 86.7 54.9 63.7 97.9 98.5
+AP Bigfoot 71.2 58.9 73.0 58.9 79.0 56.6 60.4 86.6 90.0
+SY Wolverine 68.9 59.1 71.4 59.5 80.5 57.2 61.9 91.0 88.5
+AP Roadrunner 67.6 56.0 70.3 55.7 80.1 54.6 63.9 90.5 86.0
+AP Solid 66.4 58.4 67.7 58.4 76.9 56.4 62.4 86.0 82.4
+SY Monument 61.7 57.8 60.1 57.9 70.3 56.7 62.4 67.7 80.7
+Langin 72.9 57.3 77.3 57.6 86.7 55.8 62.6 95.5 102.0
+WB4422 70.6 59.1 73.8 59.4 83.2 57.7 65.8 90.7 92.9
+AG Golden 70.3 55.5 72.3 55.5 86.1 54.9 71.2 93.6 93.4
+High Country 69.4 59.1 72.0 58.9 79.2 57.0 60.4 89.6 87.7
+WB4595 69.2 59.8 72.2 59.6 81.4 57.3 63.7 90.1 90.4
+KS Dallas 68.3 59.1 66.5 58.7 76.0 57.4 55.0 82.3 90.8
+Amplify SF 66.8 57.9 66.4 57.8 73.8 56.5 61.6 77.7 82.2
+KS Hamilton 66.6 58.3 68.5 58.3 76.3 56.1 54.5 78.0 96.3
+TAM 115 60.7 60.1 60.1 59.8 70.5 58.3 49.8 85.0 76.6
+Kivari AX 73.7 57.0 83.3 55.9 63.3 87.1 99.5
+WB-Grainfield 86.3 57.3 59.0 99.8 100.0
+Canvas 85.1 55.9 67.4 94.4 93.7
+KS Bill Snyder 80.4 56.9 63.2 92.9 85.3
+KS Mako 78.4 57.2 58.1 84.6 92.3
+Mean General 69.1 58.3 71.0 58.2 79.5 56.4 60.4 88.8 89.4
+LSD General (5%) EE 5.1 1.4 6.2 1.7 9.6 ns 8.3 16.0 13.0
+CV (Effective) 9.0 2.4 9.4 2.5 9.9 2.4 8.3 11.0 8.9
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+* Location was affected by a Wheat Streak Mosaic Virus infestation, which resulted in reduced yield of susceptible varieties.
+Locations
+2023 — Julesburg and Yuma, CO; Colby, KS
+2024 — Crook and Julesburg, CO; Ingalls, KS
+2025 — Crook, Julesburg, and Yuma, CO
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -0,0 +1,33 @@
+{
+  "source": "agripro_trials",
+  "source_key": "agt-wheat-after-soy-2025",
+  "data_type": "trial",
+  "vendor": "Syngenta",
+  "brand": "AgriPro",
+  "crop": "wheat",
+  "title": "2025 Wheat Following Soybeans Summary, Three-Year Data",
+  "filename": "Wheat%20after%20Soy%202025.pdf",
+  "region": null,
+  "wheat_class_section": null,
+  "year": 2025,
+  "years_covered": [
+    2025
+  ],
+  "varieties_found": [
+    "AP Sunbird",
+    "AP Roadrunner",
+    "SY Wolverine",
+    "AP Bigfoot",
+    "AP Prolific",
+    "SY Monument",
+    "LCS Atomic AX"
+  ],
+  "pdf_url": "https://agriprowheat.com/sites/default/files/2025-07/Wheat%20after%20Soy%202025.pdf",
+  "source_urls": [
+    "https://agriprowheat.com/trials-data",
+    "https://agriprowheat.com/sites/default/files/2025-07/Wheat%20after%20Soy%202025.pdf"
+  ],
+  "page_text_chars": 2367,
+  "fetched_at": "2026-05-25T19:11:07.269403+00:00",
+  "scraper_version": "0.1.0"
+}
@@ -0,0 +1,55 @@
+# 2025 Wheat Following Soybeans Summary, Three-Year Data
+
+- **Source:** AgriPro (Syngenta) regional trial PDF
+- **Vendor:** Syngenta
+- **Brand:** AgriPro
+- **Crop:** Wheat
+- **Data type:** trial
+- **Year:** 2025
+- **PDF:** https://agriprowheat.com/sites/default/files/2025-07/Wheat%20after%20Soy%202025.pdf
+- **Index page:** https://agriprowheat.com/trials-data
+- **Varieties listed:** AP Sunbird, AP Roadrunner, SY Wolverine, AP Bigfoot, AP Prolific, SY Monument, LCS Atomic AX
+
+---
+
+## Trial data (verbatim from PDF)
+
+```
+2025 Wheat Following Soybeans Summary, Three-Year Data
+Syngenta Commercial Variety Wheat Performance Test, 2023-2025
+3-Yr Combined 2-Yr Combined Combined Belleville, Junction City, Salina,
+Variety (2023-2025) (2024-2025) (2025) KS* KS KS
+Hard Winter Wheat Yield TWT Yield TWT Yield TWT Yield Yield Yield
+Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Lb/Bu Bu/A Bu/A Bu/A
+AP24 AX 66.1 58.8 76.6 59.0 78.7 55.3 64.8 94.7 76.7
+AP Sunbird 62.3 61.0 70.7 60.9 70.7 57.7 59.0 86.7 66.5
+AP Roadrunner 62.2 57.5 68.5 56.9 64.1 53.4 54.1 79.7 58.5
+SY Wolverine 61.0 60.3 66.9 60.1 65.4 56.5 58.2 86.2 51.9
+AP Bigfoot 60.3 61.3 67.5 61.2 68.6 58.7 53.1 86.6 65.9
+AP Prolific 59.2 60.0 66.3 60.0 67.2 57.9 46.0 86.2 69.2
+SY Monument 58.4 59.3 63.9 59.8 59.5 56.1 48.2 71.6 58.6
+Bob Dole 56.7 58.5 63.0 58.1 60.0 54.6 47.0 68.3 64.6
+Showdown 62.8 59.6 71.9 59.6 68.7 55.6 56.4 83.0 66.6
+KS Providence 61.9 60.4 70.0 60.4 67.0 56.8 52.5 88.9 59.7
+Rockstar 61.0 58.1 70.0 58.5 68.7 55.6 54.0 83.8 68.3
+WB4401 59.5 59.5 66.7 59.2 63.0 55.1 51.7 78.8 58.5
+LCS Atomic AX 59.1 61.3 67.7 61.2 70.2 58.7 52.3 88.0 70.1
+WB4523 57.4 58.9 63.9 59.0 56.7 55.5 40.6 68.2 61.2
+WB4422 72.5 58.6 73.5 55.2 62.5 87.3 70.6
+KS Bill Snyder 78.4 58.8 59.3 94.6 81.2
+WB4699 66.4 55.2 51.0 84.2 64.1
+Polansky Goldenhawk 65.3 56.1 52.7 86.5 56.8
+High Cotton 65.3 57.4 43.8 90.9 61.2
+Doublestop CLP 63.8 56.9 53.9 74.0 63.4
+Mean General 60.6 59.7 68.4 59.5 66.9 56.3 51.7 83.6 65.4
+LSD General (5%) EE 4.6 1.4 5.6 1.7 9.2 0.0 9.5 10.7 9.9
+CV (Effective) 8.6 2.5 8.3 2.7 9.2 3.8 11.2 7.8 9.2
+Boldfaced numbers are within confidence interval at specific locations and combined years of yield data.
+* Location was affected by a Wheat Streak Mosaic Virus infestation, which resulted in reduced yield of susceptible varieties.
+Locations
+2023 — Belleville, Conway Springs, Junction City, and Salina, KS
+2024 — Belleville, Conway Springs, Junction City, and Salina, KS
+2025 — Belleville, Conway Springs, Junction City, and Salina, KS
+© 2025 Syngenta. All rights reserved. Reproduction expressly prohibited without written permission. Some or all of the varieties may be protected under one or more of the following: Plant Variety Protection, United
+States Plant Patents and/or Utility Patents and may not be propagated or reproduced without authorization. AgriPro® and the Syngenta logo are trademarks of a Syngenta Group Company.
+```
@@ -201,9 +201,15 @@ def _build_where(
    vendor: str | None,
    source: str | None,
    source_key: str | None,
+    *,
+    data_type: str | None = None,
+    state: str | None = None,
+    year: int | None = None,
 ) -> dict | None:
    """Translate filter args into a Chroma `where` clause."""
    conds: list[dict] = []
+    if data_type:
+        conds.append({"data_type": data_type})
    if crop:
        conds.append({"crop": crop.lower()})
    if brand:
@@ -214,6 +220,10 @@ def _build_where(
        conds.append({"source": source})
    if source_key:
        conds.append({"source_key": source_key})
+    if state:
+        conds.append({"state": state.upper() if len(state) <= 3 else state})
+    if year:
+        conds.append({"year": int(year)})
    if not conds:
        return None
    if len(conds) == 1:
@@ -460,7 +470,11 @@ def search_docs(
        "query": query, "crop": crop, "brand": brand,
        "vendor": vendor, "source": source, "k": k,
    }) as _call:
-        where = _build_where(crop, brand, vendor, source, None)
+        # Variety-search default: filter to data_type=variety so trial
+        # documents (yield trials) don't pollute identity-focused
+        # results. To search trials, use search_trials().
+        where = _build_where(crop, brand, vendor, source, None,
+                             data_type="variety")
        pool_size = max(k * 3, RERANK_POOL)

        # Exact-code pre-filter. Variety codes ("DKC62-08RIB", "AG29XF4")
@@ -745,6 +759,233 @@ def lookup_variety(
        return "\n".join(out)


+@mcp.tool()
+def search_trials(
+    query: Annotated[str, Field(description=(
+        "Natural-language query about yield trials. Mention crop, "
+        "region or state, year, soil/conditions, and any specific "
+        "variety codes you want compared. Examples: "
+        "'best corn hybrid 2024 Iowa heavy clay'; "
+        "'AP Iliad yield Idaho stripe rust'; "
+        "'DKC65-20 vs NK1748 head to head Alabama 2023'."
+    ))],
+    crop: Annotated[
+        str | None,
+        Field(description="OPTIONAL: corn, soybeans, silage, or wheat."),
+    ] = None,
+    state: Annotated[
+        str | None,
+        Field(description=(
+            "OPTIONAL state filter. 2-letter abbrev (IA, IL, NE...) "
+            "for Golden Harvest plot reports; full or partial region "
+            "name (e.g. 'Pacific Northwest', 'Montana') for AgriPro "
+            "trial PDFs."
+        )),
+    ] = None,
+    year: Annotated[
+        int | None,
+        Field(description="OPTIONAL year filter (e.g. 2024).", ge=2010, le=2030),
+    ] = None,
+    product: Annotated[
+        str | None,
+        Field(description=(
+            "OPTIONAL variety/hybrid filter — substring match against "
+            "the product field. Example: 'DKC62' surfaces trials "
+            "containing any DKC62-* hybrid."
+        )),
+    ] = None,
+    k: Annotated[int, Field(description="Number of results to return.", ge=1, le=50)] = 10,
+) -> str:
+    """Search yield-trial data — head-to-head results from real field
+    trials. SEPARATE from variety-identity search.
+
+    Use this when the user wants to know HOW PRODUCTS PERFORMED, not
+    what they ARE. Trial data complements `search_docs`:
+
+    * `search_docs` answers: "What's the disease resistance profile
+      of DKC62-08RIB?" (variety identity)
+    * `search_trials` answers: "Which corn hybrid actually won the
+      yield trials in central Iowa in 2024?" (performance data)
+
+    Data sources:
+
+    * **Golden Harvest plot reports** (4,000+ trials) — per-site
+      head-to-head comparing products from MULTIPLE BRANDS at one
+      cooperator's field. NK, DEKALB, Golden Harvest, sometimes
+      others all compete at the same site. Cross-vendor data Bayer
+      itself doesn't publish.
+    * **AgriPro regional trial PDFs** (~14 PDFs) — multi-year
+      multi-location wheat performance for Northern Plains / PNW /
+      Plains regions.
+
+    A typical workflow: call this to identify top performers in a
+    region/year, then call `lookup_variety(source_key=...)` on the
+    leaders to verify identity details (RM, traits, disease ratings).
+    """
+    with TimedCall("search_trials", {
+        "query": query, "crop": crop, "state": state, "year": year,
+        "product": product, "k": k,
+    }) as _call:
+        where = _build_where(
+            crop, None, None, None, None,
+            data_type="trial",
+            state=state,
+            year=year,
+        )
+        pool_size = max(k * 3, RERANK_POOL)
+
+        try:
+            col = _collection()
+        except Exception as exc:  # noqa: BLE001
+            _call.set(error_dense=str(exc), hits_returned=0)
+            return (
+                "_(retrieval unavailable — Chroma collection not found. "
+                "Has the indexer run?  `python -m rag.index --rebuild`.)_"
+            )
+
+        # If a product filter is set, augment the query with the
+        # product code so BM25 + dense both have signal.
+        full_query = query
+        if product:
+            full_query = f"{query} {product}"
+
+        try:
+            dense = col.query(
+                query_texts=[full_query],
+                n_results=pool_size,
+                where=where,
+            )
+        except Exception as exc:  # noqa: BLE001
+            _call.set(error_dense=str(exc), hits_returned=0)
+            return f"_(trial retrieval failed: {exc})_"
+
+        dense_ids: list[str] = (dense.get("ids") or [[]])[0]
+        dense_docs: list[str] = (dense.get("documents") or [[]])[0]
+        dense_metas: list[dict] = (dense.get("metadatas") or [[]])[0]
+        dense_dists: list[float] = (dense.get("distances") or [[]])[0]
+
+        id_to_doc = dict(zip(dense_ids, dense_docs))
+        id_to_meta = dict(zip(dense_ids, dense_metas))
+        id_to_dist = dict(zip(dense_ids, dense_dists))
+
+        used_hybrid = False
+        if HYBRID_SEARCH:
+            bm25 = _bm25_index()
+            if bm25 is not None:
+                bm25_hits = bm25.query(full_query, n=pool_size, where=where)
+                bm25_ids = [h[0] for h in bm25_hits]
+                if bm25_ids:
+                    fused = _rrf_fuse([dense_ids, bm25_ids])
+                    fuzzy_ids = fused
+                    used_hybrid = True
+                else:
+                    fuzzy_ids = dense_ids
+            else:
+                fuzzy_ids = dense_ids
+        else:
+            fuzzy_ids = dense_ids
+
+        # Optional product-substring post-filter: if user supplied
+        # ``product``, require the chunk to actually contain the
+        # token. This re-checks the bytes since BM25 only sees stems.
+        if product:
+            needle = product.lower()
+            def _has_product(cid: str) -> bool:
+                doc = id_to_doc.get(cid, "")
+                if needle in doc.lower():
+                    return True
+                # Not yet fetched — defer; the get-by-id below will fix.
+                return cid not in id_to_doc
+
+            fuzzy_ids = [cid for cid in fuzzy_ids if _has_product(cid)]
+
+        final_ids: list[str] = []
+        seen: set[str] = set()
+        for cid in fuzzy_ids:
+            if cid in seen:
+                continue
+            seen.add(cid)
+            final_ids.append(cid)
+            if len(final_ids) >= k:
+                break
+
+        missing = [i for i in final_ids if i not in id_to_doc]
+        if missing:
+            try:
+                extra = col.get(ids=missing, include=["documents", "metadatas"])
+                for cid, doc, meta in zip(
+                    extra.get("ids") or [],
+                    extra.get("documents") or [],
+                    extra.get("metadatas") or [],
+                ):
+                    id_to_doc[cid] = doc
+                    id_to_meta[cid] = meta
+            except Exception as exc:  # noqa: BLE001
+                log.warning("get-by-id for BM25-only hits failed: %s", exc)
+
+        # Apply product filter once we have docs from the get-by-id pass.
+        if product:
+            needle = product.lower()
+            final_ids = [cid for cid in final_ids if needle in id_to_doc.get(cid, "").lower()]
+
+        _call.set(
+            hits_returned=len(final_ids),
+            hybrid=used_hybrid,
+            pool_size=pool_size,
+            data_type="trial",
+        )
+
+        if not final_ids:
+            return (
+                "_(no trials matched. Try widening — drop the state, "
+                "year, or product filter. `list_versions()` shows "
+                "which trial sources are indexed.)_"
+            )
+
+        blocks: list[str] = []
+        for cid in final_ids:
+            doc = id_to_doc.get(cid, "")
+            meta = id_to_meta.get(cid, {})
+            dist = id_to_dist.get(cid) if not used_hybrid else None
+            blocks.append(_format_trial_hit(doc, meta, dist))
+
+        header = (
+            f"# Trial search results — {len(final_ids)} trial document"
+            f"{'s' if len(final_ids) != 1 else ''}"
+            f"{' (dense + BM25 hybrid)' if used_hybrid else ' (dense only)'}\n"
+            f"_Use `get_page(source=..., source_key=...)` to read the "
+            f"full trial body. Use `lookup_variety(source_key=...)` on "
+            f"any product code to verify its identity (RM, traits, "
+            f"disease ratings)._\n\n---\n\n"
+        )
+        return header + "\n---\n\n".join(blocks)
+
+
+def _format_trial_hit(doc: str, meta: dict, distance: float | None = None) -> str:
+    """Trial-specific result header. Highlights crop/state/year and
+    sources URL (vs variety hits which emphasize brand + product
+    identity)."""
+    src_url = meta.get("source_url") or ""
+    src_key = meta.get("source_key") or ""
+    src = meta.get("source") or ""
+    crop = meta.get("crop") or ""
+    state = meta.get("state") or ""
+    year = meta.get("year") or ""
+    region = meta.get("region") or ""
+
+    title_bits = [b for b in [crop.title(), region or state, str(year) if year else ""] if b]
+    title = " · ".join(title_bits) if title_bits else src_key
+
+    header = (
+        f"### Trial: {title}  \n"
+        f"`{src}::{src_key}` — {meta.get('vendor', '')} / {meta.get('brand', '')}  \n"
+        f"<{src_url}>"
+    )
+    if distance is not None:
+        header += f"  \n_(distance={distance:.4f})_"
+    return f"{header}\n\n{doc.strip()}\n"
+
+
@mcp.tool()
 def crop_seed_api_lessons(
    topic: Annotated[
@@ -42,7 +42,12 @@ DEFAULT_DB_NAME = "crop_seed_docs.db"
 # Columns we expose as filterable metadata. Mirrors what
 # ``docs_mcp.server._build_where`` accepts so the same filter dict
 # works for both Chroma and BM25 without per-retriever translation.
-FILTER_COLUMNS = ("source", "vendor", "brand", "crop", "source_key", "ordinal")
+# data_type / year / state / region are trial-specific facets; variety
+# chunks leave them empty.
+FILTER_COLUMNS = (
+    "source", "vendor", "brand", "crop", "source_key",
+    "data_type", "year", "state", "ordinal",
+)


 # Allowlist tokenizer for free-text queries. FTS5's parser chokes on
@@ -131,8 +136,9 @@ class BM25Index:
            con.executescript(self._schema_sql())
            con.executemany(
                "INSERT INTO chunks_meta "
-                "(id, source, vendor, brand, crop, source_key, ordinal) "
-                "VALUES (?, ?, ?, ?, ?, ?, ?)",
+                "(id, source, vendor, brand, crop, source_key, "
+                " data_type, year, state, ordinal) "
+                "VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
                [
                    (
                        r["id"],
@@ -141,6 +147,9 @@ class BM25Index:
                        r["metadata"].get("brand") or "",
                        r["metadata"].get("crop") or "",
                        r["metadata"].get("source_key") or "",
+                        r["metadata"].get("data_type") or "variety",
+                        int(r["metadata"]["year"]) if isinstance(r["metadata"].get("year"), int) else None,
+                        r["metadata"].get("state") or "",
                        int(r["metadata"].get("ordinal") or 0),
                    )
                    for r in records
@@ -216,12 +225,18 @@ class BM25Index:
            brand      TEXT,
            crop       TEXT,
            source_key TEXT,
+            data_type  TEXT,
+            year       INTEGER,
+            state      TEXT,
            ordinal    INTEGER
        );
        CREATE INDEX idx_meta_source     ON chunks_meta(source);
        CREATE INDEX idx_meta_crop       ON chunks_meta(crop);
        CREATE INDEX idx_meta_brand      ON chunks_meta(brand);
        CREATE INDEX idx_meta_source_key ON chunks_meta(source_key);
+        CREATE INDEX idx_meta_data_type  ON chunks_meta(data_type);
+        CREATE INDEX idx_meta_year       ON chunks_meta(year);
+        CREATE INDEX idx_meta_state      ON chunks_meta(state);

        CREATE VIRTUAL TABLE chunks_fts USING fts5(
            text,
@@ -253,6 +253,7 @@ def _flat_metadata(sidecar: dict) -> dict:
    md: dict = {
        "source": sidecar.get("source") or "",
        "source_key": sidecar.get("source_key") or "",
+        "data_type": "variety",
        "vendor": sidecar.get("vendor") or "",
        "brand": (sidecar.get("brand") or "").upper(),
        "crop": (sidecar.get("crop") or "").lower(),
@@ -304,6 +305,258 @@ def chunks_from_variety(
    }


+# ===========================================================================
+# Trial chunker — for sidecars with data_type="trial"
+# ===========================================================================
+#
+# Trial documents are a different shape from variety identity:
+# - GH plot reports: per-site head-to-head yield comparison across brands
+# - AgriPro trial PDFs: regional multi-year multi-location summary
+#
+# Both produce ONE chunk per document with a preamble that emphasizes
+# the trial's location/year/top performers so the embedder gets clean
+# signal for queries like "best corn for sandy soil Iowa 2024".
+
+
+def _render_gh_plot_chunk(sidecar: dict) -> str:
+    """Render a Golden Harvest plot report (per-site cross-vendor)."""
+    lines: list[str] = []
+    crop = (sidecar.get("crop") or "").lower()
+    crop_label = {"corn": "Corn", "soybeans": "Soybean", "silage": "Silage"}.get(crop, crop.title())
+    state = sidecar.get("state") or sidecar.get("state_abbrev") or ""
+    year = sidecar.get("year") or ""
+    cooperator = sidecar.get("cooperator") or ""
+
+    lines.append(f"# {crop_label} yield trial — {state}, {year}")
+    lines.append("")
+    facts = ["Golden Harvest plot report (cross-vendor)"]
+    if cooperator:
+        facts.append(f"cooperator {cooperator}")
+    if sidecar.get("planted_date"):
+        facts.append(f"planted {sidecar['planted_date']}")
+    if sidecar.get("harvested_date"):
+        facts.append(f"harvested {sidecar['harvested_date']}")
+    if sidecar.get("population_seeds_per_acre"):
+        facts.append(f"population {sidecar['population_seeds_per_acre']:,} seeds/acre")
+    if sidecar.get("row_width_in"):
+        facts.append(f"{sidecar['row_width_in']}\" rows")
+    lines.append(". ".join(facts) + ".")
+    lines.append("")
+
+    results = sidecar.get("results") or []
+    if results:
+        # Pick the primary metric for ranking: corn/soy use "Yield",
+        # silage uses "Ton/Acre". Find the first metric key with a
+        # numeric value in the top result.
+        def _primary(r: dict) -> tuple[str, float | None]:
+            metrics = r.get("metrics") or {}
+            # Back-compat: old sidecars had yield_bu_ac directly.
+            if not metrics and r.get("yield_bu_ac") is not None:
+                return ("Yield", r["yield_bu_ac"])
+            for k in ("Yield", "Ton/Acre", "Tons/Acre"):
+                v = metrics.get(k)
+                if isinstance(v, (int, float)):
+                    return (k, v)
+            for k, v in metrics.items():
+                if isinstance(v, (int, float)):
+                    return (k, v)
+            return ("", None)
+
+        top = results[: min(5, len(results))]
+        primary_label, _ = _primary(top[0]) if top else ("", None)
+        rendered_top_parts: list[str] = []
+        for i, r in enumerate(top):
+            label, val = _primary(r)
+            piece = f"#{r.get('rank') or i+1} {r.get('brand','?')} {r.get('product','?')}"
+            if r.get('traits'):
+                piece += f" {r['traits']}"
+            if val is not None:
+                piece += f" — {val} {label}"
+            rendered_top_parts.append(piece)
+        if rendered_top_parts:
+            lines.append(
+                f"Top {len(top)} ({crop_label}, {state} {year}): "
+                + ", ".join(rendered_top_parts) + "."
+            )
+            lines.append("")
+
+        # Discover the metric column order from the first result with metrics.
+        metric_keys: list[str] = []
+        for r in results:
+            metrics = r.get("metrics") or {}
+            if metrics:
+                metric_keys = list(metrics.keys())
+                break
+        # Back-compat: synthesize from legacy fields if no metrics dict.
+        if not metric_keys and any(
+            r.get("yield_bu_ac") is not None for r in results
+        ):
+            metric_keys = ["Yield", "%MST", "Test Weight", "Gross Revenue"]
+
+        # Full ranking — preserves every datapoint verbatim.
+        col_headers = ["rank", "brand", "product", "traits"] + metric_keys
+        lines.append("Full ranking (" + " | ".join(col_headers) + "):")
+        for r in results:
+            row = [
+                f"#{r.get('rank') or '-'}",
+                r.get("brand") or "-",
+                r.get("product") or "-",
+                r.get("traits") or "-",
+            ]
+            metrics = r.get("metrics") or {}
+            # Back-compat shim
+            if not metrics:
+                metrics = {
+                    "Yield": r.get("yield_bu_ac"),
+                    "%MST": r.get("mst_pct"),
+                    "Test Weight": r.get("test_weight"),
+                    "Gross Revenue": r.get("gross_revenue_dol_ac"),
+                }
+            for k in metric_keys:
+                v = metrics.get(k)
+                if v is None:
+                    row.append("-")
+                elif isinstance(v, (int, float)):
+                    if "Revenue" in k or "$" in k:
+                        row.append(f"${v:.2f}")
+                    else:
+                        row.append(str(v))
+                else:
+                    row.append(str(v))
+            lines.append("  " + " | ".join(row))
+        lines.append("")
+
+    urls = sidecar.get("source_urls") or []
+    if urls:
+        lines.append(f"Source: {urls[0]}")
+    return "\n".join(lines).strip() + "\n"
+
+
+def _render_agripro_trial_chunk(sidecar: dict) -> str:
+    """Render an AgriPro regional trial PDF — preamble + verbatim text."""
+    lines: list[str] = []
+    title = sidecar.get("title") or sidecar.get("filename") or sidecar.get("source_key", "")
+    lines.append(f"# {title}")
+    lines.append("")
+
+    facts = ["AgriPro / Syngenta regional wheat trial"]
+    if sidecar.get("region"):
+        facts.append(f"region {sidecar['region']}")
+    if sidecar.get("wheat_class_section"):
+        facts.append(f"class {sidecar['wheat_class_section']}")
+    if sidecar.get("years_covered") and len(sidecar["years_covered"]) > 1:
+        yc = sidecar["years_covered"]
+        facts.append(f"years {yc[0]}–{yc[-1]}")
+    elif sidecar.get("year"):
+        facts.append(f"year {sidecar['year']}")
+    lines.append(". ".join(facts) + ".")
+    lines.append("")
+
+    varieties = sidecar.get("varieties_found") or []
+    if varieties:
+        lines.append("Varieties listed: " + ", ".join(varieties) + ".")
+        lines.append("")
+
+    # Verbatim trial data — preserves variety + yield numbers adjacent
+    # so BM25/dense can match "AP Iliad Aberdeen Idaho" queries.
+    lines.append("Trial data (verbatim from PDF):")
+    lines.append("")
+    # The actual text was in the .md body but isn't in the sidecar
+    # JSON. We render a brief marker; full text goes in the .md file
+    # that get_page returns. For embedding signal, the title +
+    # varieties + region is usually enough.
+    # If we want the FULL text in the chunk we'd need to either store
+    # it in the sidecar OR read it from the .md path at chunk time.
+    # Read from the .md path:
+    return "\n".join(lines).strip() + "\n"
+
+
+def _render_trial_chunk(sidecar: dict, md_text: str | None = None) -> str:
+    """Dispatch to the right trial renderer by source. Includes the
+    verbatim trial body for sources whose value lives in the body text
+    (currently agripro_trials)."""
+    source = sidecar.get("source")
+    if source == "gh_plot_reports":
+        return _render_gh_plot_chunk(sidecar)
+    if source == "agripro_trials":
+        header = _render_agripro_trial_chunk(sidecar)
+        if md_text:
+            # Strip the markdown frontmatter so the body text is the
+            # actual trial data, not the per-source preamble.
+            body = md_text
+            sep = "## Trial data (verbatim from PDF)"
+            if sep in body:
+                body = body.split(sep, 1)[1].strip()
+                # Strip fence markers
+                body = re.sub(r"```", "", body).strip()
+            return header + "\n" + body + "\n"
+        return header
+    # Fallback: generic trial render
+    return _render_gh_plot_chunk(sidecar)
+
+
+def _flat_trial_metadata(sidecar: dict) -> dict:
+    """Chroma-safe metadata for trial chunks. Mirrors variety metadata
+    plus trial-specific facets (state, year, data_type)."""
+    md: dict = {
+        "source": sidecar.get("source") or "",
+        "source_key": sidecar.get("source_key") or "",
+        "data_type": sidecar.get("data_type") or "trial",
+        "vendor": sidecar.get("vendor") or "",
+        "brand": (sidecar.get("brand") or "").upper(),
+        "crop": (sidecar.get("crop") or "").lower(),
+        "source_url": (sidecar.get("source_urls") or [""])[0],
+    }
+    year = sidecar.get("year")
+    if isinstance(year, int):
+        md["year"] = year
+    state = sidecar.get("state_abbrev") or sidecar.get("state")
+    if state:
+        md["state"] = state.upper() if len(state) <= 3 else state
+        md["state_abbrev"] = (sidecar.get("state_abbrev") or "").upper()
+    if sidecar.get("region"):
+        md["region"] = sidecar["region"]
+    if sidecar.get("wheat_class_section"):
+        md["wheat_class"] = sidecar["wheat_class_section"]
+    if sidecar.get("plot_id"):
+        md["plot_id"] = sidecar["plot_id"]
+    if isinstance(sidecar.get("n_results"), int):
+        md["n_results"] = sidecar["n_results"]
+    return md
+
+
+def chunks_from_trial(
+    sidecar_path: Path | str,
+    *,
+    md_path: Path | str | None = None,
+) -> Iterator[dict]:
+    """Yield chunk dict(s) for one trial document. Emits exactly one
+    chunk per trial.
+
+    Args:
+      sidecar_path: path to the trial's JSON sidecar.
+      md_path:      path to the trial's markdown body (used for
+                    AgriPro PDFs whose value lives in the verbatim
+                    text). If omitted we infer it from sidecar_path.
+    """
+    sc_path = Path(sidecar_path)
+    sidecar = json.loads(sc_path.read_text(encoding="utf-8"))
+
+    md_text: str | None = None
+    md_p = Path(md_path) if md_path else sc_path.with_suffix(".md")
+    if md_p.exists():
+        md_text = md_p.read_text(encoding="utf-8")
+
+    text = _render_trial_chunk(sidecar, md_text=md_text)
+    meta = _flat_trial_metadata(sidecar)
+    chunk_id = f"{meta['source']}::{meta['source_key']}::0"
+    yield {
+        "id": chunk_id,
+        "text": text,
+        "metadata": {**meta, "ordinal": 0},
+    }
+
+
 # ----- Backwards-compat shim for the template's index.py -------------------
 #
 # The template's ``rag.index.page_records`` calls
@@ -12,6 +12,7 @@ Override via the PRODUCT_NAME env var.
 from __future__ import annotations

 import argparse
+import json
 import logging
 import os
 import time
@@ -21,7 +22,7 @@ from typing import Iterator
 import chromadb
 from chromadb.config import Settings

-from .chunk import chunks_from_variety
+from .chunk import chunks_from_variety, chunks_from_trial
 from .embeddings import embedding_function

 log = logging.getLogger(__name__)
@@ -37,7 +38,17 @@ COLLECTION = f"{PRODUCT_NAME}_docs"

 def variety_records() -> Iterator[dict]:
    """Walk ``corpus/<source>/<source_key>.json``, yield one chunk per
-    variety."""
+    document.
+
+    Dispatches by the sidecar's ``data_type`` field:
+      - ``"trial"`` → chunks_from_trial (gh_plot_reports, agripro_trials)
+      - anything else (or absent) → chunks_from_variety (default)
+
+    The output shape (id/text/metadata) is identical for both — only
+    the chunk text composition and metadata keys differ. Chroma + BM25
+    can index both into the same collection; downstream tools filter
+    by the ``data_type`` metadata field.
+    """
    if not CORPUS.exists():
        log.error("corpus/ doesn't exist; run a scraper first")
        return
@@ -45,7 +56,15 @@ def variety_records() -> Iterator[dict]:
        if not source_dir.is_dir() or source_dir.name.startswith("."):
            continue
        for sidecar_path in sorted(source_dir.glob("*.json")):
-            yield from chunks_from_variety(sidecar_path)
+            try:
+                head = json.loads(sidecar_path.read_text(encoding="utf-8"))
+            except (OSError, json.JSONDecodeError) as exc:
+                log.warning("skipping unreadable sidecar %s: %s", sidecar_path, exc)
+                continue
+            if head.get("data_type") == "trial":
+                yield from chunks_from_trial(sidecar_path)
+            else:
+                yield from chunks_from_variety(sidecar_path)


 def upsert_to_chroma(records: list[dict]) -> int:
@@ -0,0 +1,483 @@
+"""AgriPro trial-PDF scraper.
+
+Source: ``agriprowheat.com/trials-data`` — a single page listing
+~38 PDF links to regional wheat trial summary documents. Each PDF
+is a multi-year multi-location performance test comparing AgriPro
+varieties against competitors (LCS, Norwest, PNW, UI, etc.).
+
+Discovery: walk ``/trials-data``, collect every ``href="*.pdf"``.
+
+Per-PDF content (parsed via pdfplumber):
+  - First line: usually the title (e.g.
+    "2024 Pacific Northwest Combined Summary, Three-Year Data")
+  - A multi-column table with one row per variety. Columns vary by
+    PDF but typically include: 3-yr combined yield, 2-yr combined,
+    most-recent-year yield, plus per-location yields with location
+    names in the header.
+  - Footer notes: locations covered, LSD/CV statistical caveats,
+    copyright.
+
+Trial PDFs are stable text-extractable (no charts). We capture the
+full per-page text verbatim in the chunk body — preserving
+variety-name + yield-number adjacency for the embedder — plus
+metadata derived from the title (region, year, crop class). This is
+a deliberate trade-off: perfect table parsing across the PDF
+variants would be brittle; verbatim text preserves every data point
+and the embedder + BM25 between them can match queries like
+"AP Iliad yield Aberdeen Idaho" reliably.
+
+Output:
+  corpus/agripro_trials/<source_key>.md
+  corpus/agripro_trials/<source_key>.json
+
+source_key convention: ``agt-<slugified-filename-stem>`` lowercased,
+e.g. ``agt-2024-pnw-combined``.
+
+CLI:
+  python -m scrape.sources.agripro_trials --limit 5
+  python -m scrape.sources.agripro_trials --force
+"""
+
+from __future__ import annotations
+
+import argparse
+import io
+import json
+import logging
+import os
+import random
+import re
+import sys
+import time
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+import requests
+from bs4 import BeautifulSoup
+import pdfplumber
+
+SCRAPER_VERSION = "0.1.0"
+USER_AGENT = "seed-mcp-scraper/0.1 (+https://drawbar.example/contact)"
+BASE = "https://agriprowheat.com"
+LIST_URL = f"{BASE}/trials-data"
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+CORPUS_ROOT = Path(os.environ.get("CORPUS_ROOT") or REPO_ROOT / "corpus")
+CORPUS_DIR = CORPUS_ROOT / "agripro_trials"
+
+REQ_INTERVAL_SEC = 1.0
+
+log = logging.getLogger("scrape.agripro_trials")
+
+# Region name patterns we recognize in PDF filenames / titles. The
+# value is a human-readable normalized region.
+REGION_PATTERNS = (
+    (re.compile(r"\bPNW\b|Pacific Northwest", re.I), "Pacific Northwest"),
+    (re.compile(r"\bNE Colorado\b|Northeast Colorado", re.I), "NE Colorado"),
+    (re.compile(r"\bSC KS\b|South Central Kansas", re.I), "SC Kansas / N Central OK"),
+    (re.compile(r"\bWestern Plains\b", re.I), "Western Plains"),
+    (re.compile(r"\bCentral Plains\b", re.I), "Central Plains"),
+    (re.compile(r"\bPlains Irrigated\b", re.I), "Plains Irrigated"),
+    (re.compile(r"\bWashington[/:]?N? *Idaho\b", re.I), "WA / N. Idaho"),
+    (re.compile(r"\bSouthern Idaho\b", re.I), "Southern Idaho"),
+    (re.compile(r"\bMontana\b", re.I), "Montana"),
+    (re.compile(r"\bNP Perf Data\b|Northern Plains", re.I), "Northern Plains"),
+    (re.compile(r"\bWheat after Soy\b", re.I), "Wheat-after-Soy rotation"),
+)
+
+
+# --------------------------------------------------------------------- HTTP
+
+
+class RateLimitedSession:
+    def __init__(self, interval: float = REQ_INTERVAL_SEC) -> None:
+        self.s = requests.Session()
+        self.s.headers["User-Agent"] = USER_AGENT
+        self.interval = interval
+        self._last = 0.0
+
+    def _wait(self) -> None:
+        delta = time.monotonic() - self._last
+        if delta < self.interval:
+            time.sleep(self.interval - delta)
+        self._last = time.monotonic()
+
+    def request(
+        self,
+        method: str,
+        url: str,
+        *,
+        max_retries: int = 4,
+        timeout: float = 60.0,
+        **kw: Any,
+    ) -> requests.Response:
+        last_exc: Exception | None = None
+        for attempt in range(max_retries):
+            self._wait()
+            try:
+                resp = self.s.request(method, url, timeout=timeout, **kw)
+            except requests.RequestException as exc:
+                last_exc = exc
+                backoff = min(30.0, (2 ** attempt) + random.random())
+                log.warning("network error on %s %s: %s — retry in %.1fs",
+                            method, url, exc, backoff)
+                time.sleep(backoff)
+                continue
+            if resp.status_code == 429 or 500 <= resp.status_code < 600:
+                ra = resp.headers.get("Retry-After")
+                backoff = float(ra) if (ra and ra.isdigit()) else min(30.0, (2 ** attempt) + random.random())
+                log.warning("HTTP %d on %s %s — retry in %.1fs",
+                            resp.status_code, method, url, backoff)
+                time.sleep(backoff)
+                continue
+            return resp
+        if last_exc:
+            raise last_exc
+        return resp  # type: ignore[return-value]
+
+    def get(self, url: str, **kw: Any) -> requests.Response:
+        return self.request("GET", url, **kw)
+
+
+# --------------------------------------------------------------------- model
+
+
+@dataclass
+class TrialPDF:
+    source_key: str
+    source_url: str
+    pdf_url: str
+    filename: str
+    title: str | None = None
+    year: int | None = None
+    years_covered: list[int] = field(default_factory=list)
+    region: str | None = None
+    wheat_class_section: str | None = None   # e.g. "Soft White Winter Wheat" — derived from PDF text
+    page_text: str = ""
+    varieties_found: list[str] = field(default_factory=list)
+
+
+# --------------------------------------------------------------------- discovery
+
+
+def discover_pdfs(http: RateLimitedSession) -> list[tuple[str, str, str, str]]:
+    """Return ``[(pdf_url, filename, section_heading, section_anchor), ...]``
+    for every PDF on /trials-data.
+
+    De-duplicates by pdf_url — multiple section headings may link to
+    the same PDF (e.g. a multi-state summary).
+    """
+    log.info("fetching trials index %s", LIST_URL)
+    r = http.get(LIST_URL)
+    r.raise_for_status()
+    soup = BeautifulSoup(r.text, "html.parser")
+    seen: dict[str, tuple[str, str, str, str]] = {}
+    for a in soup.find_all("a", href=re.compile(r"\.pdf(?:$|\?)", re.I)):
+        href = a["href"]
+        from urllib.parse import urljoin
+        full = urljoin(LIST_URL, href)
+        fn = href.rsplit("/", 1)[-1]
+        # Section context — closest preceding h2/h3/h4
+        section = ""
+        parent = a.parent
+        for _ in range(10):
+            if parent is None:
+                break
+            head = parent.find_previous(["h2", "h3", "h4"])
+            if head:
+                section = head.get_text(strip=True)
+                break
+            parent = parent.parent
+        if full not in seen:
+            seen[full] = (full, fn, section, href)
+    out = list(seen.values())
+    log.info("trial PDFs found: %d (deduped from %d total links)",
+             len(out),
+             sum(1 for a in soup.find_all("a", href=re.compile(r"\.pdf", re.I))))
+    return out
+
+
+# --------------------------------------------------------------------- helpers
+
+
+def source_key_for(filename: str) -> str:
+    """``2024 PNW Combined.pdf`` → ``agt-2024-pnw-combined``."""
+    from urllib.parse import unquote
+    stem = unquote(filename).rsplit(".", 1)[0]
+    slug = re.sub(r"[^a-zA-Z0-9]+", "-", stem).strip("-").lower()
+    return f"agt-{slug}"
+
+
+def _detect_region(text: str) -> str | None:
+    for pat, label in REGION_PATTERNS:
+        if pat.search(text):
+            return label
+    return None
+
+
+def _detect_years(text: str) -> list[int]:
+    """Return sorted years found in the PDF title / first lines.
+    Filters to 2010-2030 to ignore page numbers / table values."""
+    years = sorted({
+        int(y) for y in re.findall(r"\b(20[1-3]\d)\b", text[:600])
+    })
+    return years
+
+
+def _detect_wheat_class_section(text: str) -> str | None:
+    """The trial PDFs typically have a class label line like
+    'Soft White Winter Wheat' near the top of the table."""
+    for label in (
+        "Hard Red Winter Wheat", "Hard Red Spring Wheat",
+        "Hard White Spring Wheat", "Hard White Winter Wheat",
+        "Soft White Winter Wheat", "Soft White Spring Wheat",
+        "Soft Red Winter Wheat", "Durum",
+    ):
+        if re.search(r"\b" + re.escape(label) + r"\b", text[:1500], re.I):
+            return label
+    return None
+
+
+# Variety name patterns we expect to see in AgriPro trial PDFs.
+# AgriPro varieties = AP <name>, SY <name>; competitors include
+# LCS <name>, UI <name>, PNW <name>, Norwest <name>.
+_VARIETY_LINE_RE = re.compile(
+    r"^(?:AP|SY|LCS|UI|PNW|Norwest|WB|Stine|Pioneer)\b[A-Za-z0-9 \-+]*",
+)
+
+
+def _detect_varieties(text: str) -> list[str]:
+    out: list[str] = []
+    seen: set[str] = set()
+    for line in text.splitlines():
+        line = line.strip()
+        if not line:
+            continue
+        m = _VARIETY_LINE_RE.match(line)
+        if m:
+            # Up to first run of digits / spaces — variety name only
+            name_match = re.match(r"^([A-Za-z][A-Za-z0-9 \-+]*?)\s+\d", line)
+            name = name_match.group(1).strip() if name_match else m.group(0).strip()
+            # Trim trailing single tokens that are clearly stats
+            if name and name not in seen and len(name) <= 40:
+                seen.add(name)
+                out.append(name)
+    return out
+
+
+# --------------------------------------------------------------------- detail
+
+
+def fetch_pdf_detail(
+    http: RateLimitedSession,
+    pdf_url: str,
+    filename: str,
+) -> TrialPDF | None:
+    """Download + parse one trial PDF."""
+    r = http.get(pdf_url)
+    if r.status_code == 404:
+        return None
+    r.raise_for_status()
+    try:
+        with pdfplumber.open(io.BytesIO(r.content)) as pdf:
+            pages_text = []
+            for p in pdf.pages:
+                t = p.extract_text() or ""
+                pages_text.append(t)
+        text = "\n\n".join(pages_text).strip()
+    except Exception as exc:  # noqa: BLE001
+        log.warning("PDF parse failed for %s: %s", pdf_url, exc)
+        return None
+
+    title = ""
+    if text:
+        # First non-empty line is usually the title.
+        for line in text.splitlines():
+            line = line.strip()
+            if line:
+                title = line
+                break
+
+    region = _detect_region(filename) or _detect_region(title or "")
+    years = _detect_years(title + "\n" + filename)
+    wheat_class_section = _detect_wheat_class_section(text)
+    varieties = _detect_varieties(text)
+
+    return TrialPDF(
+        source_key=source_key_for(filename),
+        source_url=LIST_URL,
+        pdf_url=pdf_url,
+        filename=filename,
+        title=title or None,
+        year=years[-1] if years else None,
+        years_covered=years,
+        region=region,
+        wheat_class_section=wheat_class_section,
+        page_text=text,
+        varieties_found=varieties,
+    )
+
+
+# --------------------------------------------------------------------- render
+
+
+def render_markdown(p: TrialPDF) -> str:
+    head: list[str] = [
+        f"# {p.title or p.filename}",
+        "",
+        "- **Source:** AgriPro (Syngenta) regional trial PDF",
+        "- **Vendor:** Syngenta",
+        "- **Brand:** AgriPro",
+        "- **Crop:** Wheat",
+        "- **Data type:** trial",
+    ]
+    if p.region:
+        head.append(f"- **Region:** {p.region}")
+    if p.wheat_class_section:
+        head.append(f"- **Wheat class:** {p.wheat_class_section}")
+    if p.year:
+        head.append(f"- **Year:** {p.year}")
+    if p.years_covered and len(p.years_covered) > 1:
+        head.append(f"- **Years covered:** {p.years_covered[0]}–{p.years_covered[-1]}")
+    head.append(f"- **PDF:** {p.pdf_url}")
+    head.append(f"- **Index page:** {p.source_url}")
+    if p.varieties_found:
+        head.append(
+            f"- **Varieties listed:** {', '.join(p.varieties_found[:30])}"
+            + ("…" if len(p.varieties_found) > 30 else "")
+        )
+    head.append("")
+    head.append("---")
+    head.append("")
+    head.append("## Trial data (verbatim from PDF)")
+    head.append("")
+    head.append("```")
+    head.append(p.page_text)
+    head.append("```")
+    return "\n".join(head)
+
+
+# --------------------------------------------------------------------- write
+
+
+def write_pdf(prod: TrialPDF, body_md: str) -> None:
+    CORPUS_DIR.mkdir(parents=True, exist_ok=True)
+    md_path = CORPUS_DIR / f"{prod.source_key}.md"
+    json_path = CORPUS_DIR / f"{prod.source_key}.json"
+
+    md_path.write_text(body_md, encoding="utf-8")
+    sidecar = {
+        "source": "agripro_trials",
+        "source_key": prod.source_key,
+        "data_type": "trial",
+        "vendor": "Syngenta",
+        "brand": "AgriPro",
+        "crop": "wheat",
+        "title": prod.title,
+        "filename": prod.filename,
+        "region": prod.region,
+        "wheat_class_section": prod.wheat_class_section,
+        "year": prod.year,
+        "years_covered": prod.years_covered,
+        "varieties_found": prod.varieties_found,
+        "pdf_url": prod.pdf_url,
+        "source_urls": [prod.source_url, prod.pdf_url],
+        "page_text_chars": len(prod.page_text),
+        "fetched_at": datetime.now(timezone.utc).isoformat(),
+        "scraper_version": SCRAPER_VERSION,
+    }
+    json_path.write_text(
+        json.dumps(sidecar, indent=2, ensure_ascii=False) + "\n",
+        encoding="utf-8",
+    )
+
+
+# --------------------------------------------------------------------- pipeline
+
+
+def process_pdf(
+    http: RateLimitedSession,
+    *,
+    pdf_url: str,
+    filename: str,
+    force: bool,
+) -> tuple[str, TrialPDF | None]:
+    sk = source_key_for(filename)
+    md_path = CORPUS_DIR / f"{sk}.md"
+    if md_path.exists() and not force:
+        return "skipped", None
+    try:
+        prod = fetch_pdf_detail(http, pdf_url, filename)
+    except Exception as exc:  # noqa: BLE001
+        log.error("PDF fetch/parse failed for %s: %s", pdf_url, exc)
+        return "failed", None
+    if prod is None:
+        return "missing", None
+    body = render_markdown(prod)
+    write_pdf(prod, body)
+    return "written", prod
+
+
+def run(*, limit: int | None, force: bool) -> int:
+    CORPUS_DIR.mkdir(parents=True, exist_ok=True)
+    http = RateLimitedSession()
+    targets = discover_pdfs(http)
+
+    counts = {"written": 0, "skipped": 0, "missing": 0, "failed": 0}
+    processed = 0
+    for pdf_url, filename, _section, _href in targets:
+        if limit is not None and processed >= limit:
+            break
+        processed += 1
+        status, prod = process_pdf(
+            http, pdf_url=pdf_url, filename=filename, force=force,
+        )
+        counts[status] = counts.get(status, 0) + 1
+        log.info(
+            "[%d/%d] %s %s | region=%s year=%s varieties=%d chars=%d",
+            processed, len(targets),
+            source_key_for(filename), status,
+            (prod.region if prod else "-") or "-",
+            prod.year if prod else "-",
+            len(prod.varieties_found) if prod else 0,
+            len(prod.page_text) if prod else 0,
+        )
+
+    log.info(
+        "done: processed=%d written=%d skipped=%d missing=%d failed=%d (of %d PDFs)",
+        processed, counts["written"], counts["skipped"],
+        counts["missing"], counts["failed"], len(targets),
+    )
+    return 0 if counts["failed"] == 0 else 1
+
+
+# --------------------------------------------------------------------- CLI
+
+
+def _build_argparser() -> argparse.ArgumentParser:
+    p = argparse.ArgumentParser(
+        prog="scrape.sources.agripro_trials",
+        description="Scrape AgriPro regional trial PDFs.",
+    )
+    p.add_argument("--limit", type=int, default=None,
+                   help="Stop after processing N PDFs (default: all).")
+    p.add_argument("--force", action="store_true",
+                   help="Re-fetch even if the markdown file already exists.")
+    p.add_argument("--log-level", default=os.environ.get("LOG_LEVEL", "INFO"))
+    return p
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = _build_argparser().parse_args(argv)
+    logging.basicConfig(
+        level=args.log_level.upper(),
+        format="%(asctime)s %(levelname)s %(name)s %(message)s",
+        stream=sys.stderr,
+    )
+    return run(limit=args.limit, force=args.force)
+
+
+if __name__ == "__main__":
+    sys.exit(main())
@@ -0,0 +1,781 @@
+"""Golden Harvest plot-report scraper — cross-vendor yield trials.
+
+This is the FIRST source in the seed-mcp corpus with ``data_type:
+"trial"`` rather than the per-variety identity records all other
+scrapers emit. Each document is one head-to-head yield trial at a
+specific state/year/site, comparing products across brands (NK,
+DEKALB, Golden Harvest, sometimes Pioneer/Channel etc. listed as
+competitor entries) — i.e. **third-party-feeling cross-vendor data
+that Bayer doesn't publish itself**.
+
+Source: ``goldenharvestseeds.com`` — same site as ``golden_harvest``
+variety scraper. ``/sitemap-ghs-hybrids.xml`` (already walked for
+the variety scraper) lists 8,237 plot reports across:
+
+  Year   Corn    Soy   Silage   Total
+  2023  1,832  1,614     173    3,619
+  2024  1,432  1,277     137    2,846
+  2025    973    703      96    1,772
+
+Initial scrape: 2024 + 2025 (4,618 reports). 2023 is older data
+that's still informative but lower priority. Defer 2023 to a later
+backfill pass via ``--include-2023``.
+
+URL shape:
+  /<crop>/plot-report/<state-abbrev>/<year>/<plot-id>
+  e.g. /corn/plot-report/al/2023/2374765
+
+Per-report data (server-rendered HTML):
+  - Cooperator name (h1 area)
+  - State (full name, e.g. "Alabama")
+  - Planted date / Harvested date
+  - Population (seeds/acre), Row Width
+  - One <table> with columns:
+    Rank | Brand | Product | Traits | Yield (BU/Acre) | %MST |
+    Test Weight | Gross Revenue | Entry #
+
+Each row in the results table can be from any seed brand — the
+trial is the test, not the catalog. Brand and product are the join
+keys back to the per-variety corpus (lookup_variety can pull the
+identity record if we have the same brand/product).
+
+Output:
+  corpus/gh_plot_reports/<source_key>.md      LLM-visible body
+  corpus/gh_plot_reports/<source_key>.json    sidecar metadata
+
+source_key convention: ``ghpr-<crop>-<state>-<year>-<plot_id>``
+e.g. ``ghpr-corn-al-2023-2374765``.
+
+CLI:
+  python -m scrape.sources.gh_plot_reports --limit 5
+  python -m scrape.sources.gh_plot_reports --crop corn --state ia --year 2024
+  python -m scrape.sources.gh_plot_reports --include-2023 --force
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import os
+import random
+import re
+import sys
+import time
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+
+import requests
+from bs4 import BeautifulSoup
+
+SCRAPER_VERSION = "0.1.0"
+USER_AGENT = "seed-mcp-scraper/0.1 (+https://drawbar.example/contact)"
+BASE = "https://www.goldenharvestseeds.com"
+SITEMAP_HYBRIDS = f"{BASE}/sitemap-ghs-hybrids.xml"
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+CORPUS_ROOT = Path(os.environ.get("CORPUS_ROOT") or REPO_ROOT / "corpus")
+CORPUS_DIR = CORPUS_ROOT / "gh_plot_reports"
+
+REQ_INTERVAL_SEC = 1.0
+
+log = logging.getLogger("scrape.gh_plot_reports")
+
+# State name normalization: URL gives a 2-letter abbrev; sidecar keeps
+# both forms so search filters can use either.
+STATE_NAMES = {
+    "al": "Alabama", "ak": "Alaska", "az": "Arizona", "ar": "Arkansas",
+    "ca": "California", "co": "Colorado", "ct": "Connecticut",
+    "de": "Delaware", "fl": "Florida", "ga": "Georgia", "hi": "Hawaii",
+    "id": "Idaho", "il": "Illinois", "in": "Indiana", "ia": "Iowa",
+    "ks": "Kansas", "ky": "Kentucky", "la": "Louisiana", "me": "Maine",
+    "md": "Maryland", "ma": "Massachusetts", "mi": "Michigan",
+    "mn": "Minnesota", "ms": "Mississippi", "mo": "Missouri",
+    "mt": "Montana", "ne": "Nebraska", "nv": "Nevada", "nh": "New Hampshire",
+    "nj": "New Jersey", "nm": "New Mexico", "ny": "New York",
+    "nc": "North Carolina", "nd": "North Dakota", "oh": "Ohio",
+    "ok": "Oklahoma", "or": "Oregon", "pa": "Pennsylvania",
+    "ri": "Rhode Island", "sc": "South Carolina", "sd": "South Dakota",
+    "tn": "Tennessee", "tx": "Texas", "ut": "Utah", "vt": "Vermont",
+    "va": "Virginia", "wa": "Washington", "wv": "West Virginia",
+    "wi": "Wisconsin", "wy": "Wyoming",
+}
+
+
+# --------------------------------------------------------------------- HTTP
+
+
+class RateLimitedSession:
+    def __init__(self, interval: float = REQ_INTERVAL_SEC) -> None:
+        self.s = requests.Session()
+        self.s.headers["User-Agent"] = USER_AGENT
+        self.interval = interval
+        self._last = 0.0
+
+    def _wait(self) -> None:
+        delta = time.monotonic() - self._last
+        if delta < self.interval:
+            time.sleep(self.interval - delta)
+        self._last = time.monotonic()
+
+    def request(
+        self,
+        method: str,
+        url: str,
+        *,
+        max_retries: int = 4,
+        timeout: float = 30.0,
+        **kw: Any,
+    ) -> requests.Response:
+        last_exc: Exception | None = None
+        for attempt in range(max_retries):
+            self._wait()
+            try:
+                resp = self.s.request(method, url, timeout=timeout, **kw)
+            except requests.RequestException as exc:
+                last_exc = exc
+                backoff = min(30.0, (2 ** attempt) + random.random())
+                log.warning("network error on %s %s: %s — retry in %.1fs",
+                            method, url, exc, backoff)
+                time.sleep(backoff)
+                continue
+            if resp.status_code == 429 or 500 <= resp.status_code < 600:
+                ra = resp.headers.get("Retry-After")
+                backoff = float(ra) if (ra and ra.isdigit()) else min(30.0, (2 ** attempt) + random.random())
+                log.warning("HTTP %d on %s %s — retry in %.1fs",
+                            resp.status_code, method, url, backoff)
+                time.sleep(backoff)
+                continue
+            return resp
+        if last_exc:
+            raise last_exc
+        return resp  # type: ignore[return-value]
+
+    def get(self, url: str, **kw: Any) -> requests.Response:
+        return self.request("GET", url, **kw)
+
+
+# --------------------------------------------------------------------- model
+
+
+@dataclass
+class TrialResult:
+    rank: int | None = None
+    brand: str = ""
+    product: str = ""
+    traits: str = ""
+    # Generic per-column metrics — keyed by the header from the table
+    # (e.g. "Yield" / "%MST" / "Ton/Acre" / "Milk Per Acre" /
+    # "Beef Per Ton"). Corn + soy use Yield/MST/Test Weight/Gross
+    # Revenue; silage uses Ton/Acre + Milk + Beef columns. Storing as
+    # an open dict keeps the scraper robust across crop types.
+    metrics: dict[str, float | str | None] = field(default_factory=dict)
+    entry_num: int | None = None
+
+    # Convenience accessors — back-compat for the chunker that looks
+    # up these specific keys.
+    @property
+    def yield_bu_ac(self) -> float | None:
+        v = self.metrics.get("Yield")
+        return v if isinstance(v, (int, float)) else None
+
+    @property
+    def mst_pct(self) -> float | None:
+        v = self.metrics.get("%MST")
+        return v if isinstance(v, (int, float)) else None
+
+    @property
+    def test_weight(self) -> float | None:
+        v = self.metrics.get("Test Weight")
+        return v if isinstance(v, (int, float)) else None
+
+    @property
+    def gross_revenue_dol_ac(self) -> float | None:
+        v = self.metrics.get("Gross Revenue")
+        return v if isinstance(v, (int, float)) else None
+
+    @property
+    def primary_metric(self) -> tuple[str, float | None]:
+        """The first numeric metric — used as the canonical 'yield'
+        for ranking in the chunk preamble. Corn/soy: Yield (BU/Ac).
+        Silage: Ton/Acre."""
+        for k in ("Yield", "Ton/Acre", "Tons/Acre"):
+            v = self.metrics.get(k)
+            if isinstance(v, (int, float)):
+                return (k, v)
+        # Fallback to first numeric metric
+        for k, v in self.metrics.items():
+            if isinstance(v, (int, float)):
+                return (k, v)
+        return ("", None)
+
+
+@dataclass
+class PlotReport:
+    source_key: str
+    source_url: str
+    crop: str           # "corn" / "soybeans" / "silage"
+    state_abbrev: str   # "al"
+    state_name: str     # "Alabama"
+    year: int
+    plot_id: str
+
+    cooperator: str | None = None
+    planted_date: str | None = None    # ISO date
+    harvested_date: str | None = None  # ISO date
+    population: int | None = None
+    row_width: int | None = None
+
+    results: list[TrialResult] = field(default_factory=list)
+
+
+# --------------------------------------------------------------------- discovery
+
+
+_PLOT_URL_RE = re.compile(
+    r".*?/(?P<crop>corn|soybean|silage)/plot-report/"
+    r"(?P<state>[a-z]{2})/(?P<year>\d{4})/(?P<plot>\d+)"
+)
+
+
+def discover_plots(
+    http: RateLimitedSession,
+    *,
+    crops: set[str],
+    states: set[str] | None,
+    years: set[int],
+) -> list[tuple[str, str, str, int, str]]:
+    """Walk the hybrids sitemap and return matching plot URLs as
+    ``[(url, crop, state, year, plot_id), ...]`` tuples. ``crop`` is
+    normalized to the schema's terms (soybean → soybeans)."""
+    log.info("fetching sitemap %s", SITEMAP_HYBRIDS)
+    r = http.get(SITEMAP_HYBRIDS)
+    r.raise_for_status()
+    entries = re.findall(r"<loc>([^<]+)</loc>", r.text)
+    log.info("sitemap parsed: %d total locs", len(entries))
+
+    out: list[tuple[str, str, str, int, str]] = []
+    for url in entries:
+        m = _PLOT_URL_RE.match(url)
+        if not m:
+            continue
+        crop_url = m.group("crop")
+        # Normalize "soybean" → "soybeans" to match the rest of the corpus.
+        crop = "soybeans" if crop_url == "soybean" else crop_url
+        state = m.group("state").lower()
+        year = int(m.group("year"))
+        plot = m.group("plot")
+        if crops and crop not in crops:
+            continue
+        if states and state not in states:
+            continue
+        if years and year not in years:
+            continue
+        out.append((url, crop, state, year, plot))
+
+    log.info("after filters: %d plot URLs", len(out))
+    return out
+
+
+# --------------------------------------------------------------------- helpers
+
+
+def source_key_for(crop: str, state: str, year: int, plot_id: str) -> str:
+    return f"ghpr-{crop}-{state}-{year}-{plot_id}"
+
+
+def _parse_date_mdy(s: str) -> str | None:
+    """``04/06/23`` → ``2023-04-06``. Two-digit years are assumed to
+    be 20xx (sane for current-century trial data)."""
+    s = (s or "").strip()
+    m = re.match(r"^(\d{1,2})/(\d{1,2})/(\d{2,4})$", s)
+    if not m:
+        return None
+    mo, dy, yr = m.group(1), m.group(2), m.group(3)
+    if len(yr) == 2:
+        yr = "20" + yr
+    try:
+        return f"{int(yr):04d}-{int(mo):02d}-{int(dy):02d}"
+    except ValueError:
+        return None
+
+
+def _parse_int(s: str | None) -> int | None:
+    if not s:
+        return None
+    s = re.sub(r"[,$]", "", str(s).strip())
+    try:
+        return int(s)
+    except ValueError:
+        return None
+
+
+def _parse_float(s: str | None) -> float | None:
+    if not s:
+        return None
+    s = re.sub(r"[,$]", "", str(s).strip())
+    try:
+        return float(s)
+    except ValueError:
+        return None
+
+
+# --------------------------------------------------------------------- detail
+
+
+def fetch_plot_detail(
+    http: RateLimitedSession,
+    url: str,
+    crop: str,
+    state: str,
+    year: int,
+    plot_id: str,
+) -> PlotReport | None:
+    """Fetch one plot-report page and parse it."""
+    r = http.get(url)
+    if r.status_code == 404:
+        return None
+    r.raise_for_status()
+    soup = BeautifulSoup(r.text, "html.parser")
+
+    prod = PlotReport(
+        source_key=source_key_for(crop, state, year, plot_id),
+        source_url=url,
+        crop=crop,
+        state_abbrev=state,
+        state_name=STATE_NAMES.get(state, state.upper()),
+        year=year,
+        plot_id=plot_id,
+    )
+
+    # Pull metadata from the header area. The page renders cooperator
+    # name + state + key fields as text following the h1.
+    h1 = soup.find("h1")
+    if h1:
+        # Walk up to a parent that includes the metadata strip
+        container = h1.parent
+        while container is not None and not container.find("table"):
+            parent = container.parent
+            if parent is None:
+                break
+            container = parent
+        if container:
+            text = container.get_text(" | ", strip=True)
+            # Cooperator is usually the segment right after the H1.
+            # Pattern: "Corn Plot Results | <Name> | <State> | Planted: | ..."
+            parts = [p.strip() for p in text.split("|") if p.strip()]
+            # Drop the title segment
+            if parts and parts[0].lower().startswith(("corn plot", "soybean plot", "silage plot")):
+                parts = parts[1:]
+            if parts:
+                # First segment that doesn't match a state name is the cooperator
+                cand = parts[0]
+                if cand and cand != prod.state_name and not cand.endswith(":"):
+                    prod.cooperator = cand
+
+    # Walk the page text for known labeled fields.
+    page_text = soup.get_text(" ", strip=True)
+    m = re.search(r"Planted:\s*(\d{1,2}/\d{1,2}/\d{2,4})", page_text)
+    if m:
+        prod.planted_date = _parse_date_mdy(m.group(1))
+    m = re.search(r"Harvested:\s*(\d{1,2}/\d{1,2}/\d{2,4})", page_text)
+    if m:
+        prod.harvested_date = _parse_date_mdy(m.group(1))
+    m = re.search(r"Population:\s*([\d,]+)", page_text)
+    if m:
+        prod.population = _parse_int(m.group(1))
+    m = re.search(r"Row Width:\s*(\d+)", page_text)
+    if m:
+        prod.row_width = _parse_int(m.group(1))
+
+    # Parse the results table. The HTML uses ONE merged cell for
+    # "Brand Product Traits" (despite the header containing all
+    # three labels); subsequent cells are Yield, %MST, Test Weight,
+    # Gross Revenue, Entry #. We split the merged cell using a
+    # known-brand prefix match.
+    table = soup.find("table")
+    if not table:
+        return prod
+    rows = table.find_all("tr")
+    if not rows:
+        return prod
+
+    header_cells = [c.get_text(" ", strip=True) for c in rows[0].find_all(["th", "td"])]
+
+    def col_idx(*names: str) -> int | None:
+        for n in names:
+            for i, h in enumerate(header_cells):
+                if n.lower() in h.lower():
+                    return i
+        return None
+
+    # Position of the merged identity cell, by header containing "Brand".
+    i_identity = col_idx("Brand")
+    i_rank = col_idx("Rank")
+    i_entry = col_idx("Entry")
+
+    # Build a list of (header, index) for the OTHER columns (the
+    # metric columns). Skips Rank, Brand-merge-cell, and Entry #.
+    metric_columns: list[tuple[str, int]] = []
+    skip_idx = {i_identity, i_rank, i_entry}
+    for i, h in enumerate(header_cells):
+        if i in skip_idx:
+            continue
+        h_clean = h.strip()
+        if h_clean:
+            metric_columns.append((h_clean, i))
+
+    for row in rows[1:]:
+        cells = [c.get_text(" ", strip=True) for c in row.find_all(["td", "th"])]
+        if len(cells) < 2:
+            continue
+        def cell(i: int | None) -> str:
+            return cells[i] if i is not None and 0 <= i < len(cells) else ""
+
+        identity = cell(i_identity).strip()
+        if any(k in identity.lower() for k in ("plot average", "trial average", "average")):
+            continue
+
+        brand, product, traits = _split_identity(identity)
+
+        # Collect every metric column verbatim. Numeric where parseable,
+        # else preserve the raw string (e.g. "ns" for not-significant).
+        metrics: dict[str, float | str | None] = {}
+        for h, idx in metric_columns:
+            raw = cell(idx).strip()
+            if not raw or raw == "-":
+                metrics[h] = None
+            else:
+                f = _parse_float(raw)
+                metrics[h] = f if f is not None else raw
+
+        result = TrialResult(
+            rank=_parse_int(cell(i_rank)),
+            brand=brand,
+            product=product,
+            traits=traits,
+            metrics=metrics,
+            entry_num=_parse_int(cell(i_entry)),
+        )
+        has_data = result.brand or result.product or any(
+            v is not None for v in metrics.values()
+        )
+        if has_data:
+            prod.results.append(result)
+
+    return prod
+
+
+# Known seed brands that can appear in plot-report identity cells.
+# Sorted longest-first so multi-word brands match before sub-strings.
+_BRAND_NAMES = (
+    "Golden Harvest", "WestBred", "AgriPro", "DEKALB", "Pioneer",
+    "Channel", "Asgrow", "NK", "Becks", "Beck's", "Brevant",
+    "Stine", "Renk", "Wyffels", "LG Seeds", "Croplan", "FS",
+    "Local Choice", "Mycogen", "AgriGold", "Hoegemeyer",
+)
+_BRAND_RE = re.compile(
+    r"^(?:" + "|".join(re.escape(b) for b in _BRAND_NAMES) + r")\b",
+    re.I,
+)
+
+
+def _split_identity(identity: str) -> tuple[str, str, str]:
+    """Split a plot-report identity cell into ``(brand, product, traits)``.
+
+    The HTML emits one merged cell like "NK NK1748-3110 Agrisure ®"
+    or "Golden Harvest G16Q82-DV DuracadeViptera™" or just
+    "DEKALB DKC65-20". We:
+
+    1. Match the brand against a known-brand list at the start.
+    2. The token immediately after the brand is the product.
+    3. Anything remaining is the trait stack (free text).
+    """
+    if not identity:
+        return "", "", ""
+    s = identity.strip()
+    m = _BRAND_RE.match(s)
+    if not m:
+        # Unknown brand prefix — best-effort: first token is brand,
+        # second is product, rest is traits.
+        parts = s.split(maxsplit=2)
+        if len(parts) == 1:
+            return parts[0], "", ""
+        if len(parts) == 2:
+            return parts[0], parts[1], ""
+        return parts[0], parts[1], parts[2]
+    brand = m.group(0)
+    rest = s[len(brand):].strip()
+    parts = rest.split(maxsplit=1)
+    product = parts[0] if parts else ""
+    traits = parts[1].strip() if len(parts) > 1 else ""
+    return brand, product, traits
+
+
+# --------------------------------------------------------------------- render
+
+
+def render_markdown(p: PlotReport) -> str:
+    crop_label = {
+        "corn": "Corn", "soybeans": "Soybean", "silage": "Silage",
+    }.get(p.crop, p.crop.title())
+
+    head: list[str] = [
+        f"# {crop_label} yield trial — {p.state_name}, {p.year}",
+        "",
+        f"- **Source:** Golden Harvest plot report (cross-vendor head-to-head)",
+        f"- **Crop:** {crop_label}",
+        f"- **State:** {p.state_name} ({p.state_abbrev.upper()})",
+        f"- **Year:** {p.year}",
+        f"- **Plot ID:** {p.plot_id}",
+    ]
+    if p.cooperator:
+        head.append(f"- **Cooperator:** {p.cooperator}")
+    if p.planted_date:
+        head.append(f"- **Planted:** {p.planted_date}")
+    if p.harvested_date:
+        head.append(f"- **Harvested:** {p.harvested_date}")
+    if p.population:
+        head.append(f"- **Population:** {p.population:,} seeds/acre")
+    if p.row_width:
+        head.append(f"- **Row width:** {p.row_width}\"")
+    head.append(f"- **URL:** {p.source_url}")
+    head.append("")
+    head.append("---")
+    head.append("")
+
+    sections: list[str] = []
+    if p.results:
+        # Discover all metric columns present across results, in
+        # first-seen order. This keeps corn (Yield/MST/...) and silage
+        # (Ton/Acre/Milk/Beef) using their own header sets.
+        metric_keys: list[str] = []
+        seen_keys: set[str] = set()
+        for r in p.results:
+            for k in r.metrics.keys():
+                if k not in seen_keys:
+                    seen_keys.add(k)
+                    metric_keys.append(k)
+
+        sections.append("## Results (top-down by rank)")
+        sections.append("")
+        header_cells = ["Rank", "Brand", "Product", "Traits"] + metric_keys
+        sections.append("| " + " | ".join(header_cells) + " |")
+        sections.append("|" + "|".join(["---"] * len(header_cells)) + "|")
+        for r in p.results:
+            row = [
+                str(r.rank) if r.rank is not None else "-",
+                r.brand or "-",
+                r.product or "-",
+                r.traits or "-",
+            ]
+            for k in metric_keys:
+                v = r.metrics.get(k)
+                if v is None:
+                    row.append("-")
+                elif isinstance(v, (int, float)):
+                    # Dollar columns rendered with $ prefix
+                    if "Revenue" in k or "$" in k:
+                        row.append(f"${v:.2f}")
+                    else:
+                        row.append(str(v))
+                else:
+                    row.append(str(v))
+            sections.append("| " + " | ".join(row) + " |")
+        sections.append("")
+
+        # Compact text summary for embedder signal — uses the primary
+        # metric (Yield for corn/soy, Ton/Acre for silage).
+        top = p.results[: min(5, len(p.results))]
+        if top:
+            primary_label, _ = top[0].primary_metric
+            if primary_label:
+                summary = ", ".join(
+                    f"{r.product or '?'} ({r.brand or '?'}) {r.primary_metric[1]}"
+                    for r in top
+                    if r.primary_metric[1] is not None
+                )
+                if summary:
+                    sections.append(f"Top {len(top)} by {primary_label}: {summary}.")
+                    sections.append("")
+
+    return "\n".join(head) + "\n".join(sections)
+
+
+# --------------------------------------------------------------------- write
+
+
+def write_plot(prod: PlotReport, body_md: str) -> None:
+    CORPUS_DIR.mkdir(parents=True, exist_ok=True)
+    md_path = CORPUS_DIR / f"{prod.source_key}.md"
+    json_path = CORPUS_DIR / f"{prod.source_key}.json"
+
+    md_path.write_text(body_md, encoding="utf-8")
+    sidecar = {
+        "source": "gh_plot_reports",
+        "source_key": prod.source_key,
+        "data_type": "trial",
+        "vendor": "Syngenta",     # Golden Harvest publishes the trial
+        "brand": "Golden Harvest",
+        "crop": prod.crop,
+        "state": prod.state_name,
+        "state_abbrev": prod.state_abbrev,
+        "year": prod.year,
+        "plot_id": prod.plot_id,
+        "cooperator": prod.cooperator,
+        "planted_date": prod.planted_date,
+        "harvested_date": prod.harvested_date,
+        "population_seeds_per_acre": prod.population,
+        "row_width_in": prod.row_width,
+        "results": [
+            {
+                "rank": r.rank,
+                "brand": r.brand,
+                "product": r.product,
+                "traits": r.traits,
+                # All per-column metrics verbatim. Corn/soy: Yield,
+                # %MST, Test Weight, Gross Revenue. Silage: Ton/Acre,
+                # Milk Per Acre, Milk Per Ton, Beef Per Acre, Beef Per
+                # Ton. (Plus any other column the source publishes.)
+                "metrics": r.metrics,
+                "entry_num": r.entry_num,
+            }
+            for r in prod.results
+        ],
+        "n_results": len(prod.results),
+        "source_urls": [prod.source_url],
+        "fetched_at": datetime.now(timezone.utc).isoformat(),
+        "scraper_version": SCRAPER_VERSION,
+    }
+    json_path.write_text(
+        json.dumps(sidecar, indent=2, ensure_ascii=False) + "\n",
+        encoding="utf-8",
+    )
+
+
+# --------------------------------------------------------------------- pipeline
+
+
+def process_plot(
+    http: RateLimitedSession,
+    *,
+    url: str,
+    crop: str,
+    state: str,
+    year: int,
+    plot_id: str,
+    force: bool,
+) -> tuple[str, PlotReport | None]:
+    sk = source_key_for(crop, state, year, plot_id)
+    md_path = CORPUS_DIR / f"{sk}.md"
+    if md_path.exists() and not force:
+        return "skipped", None
+    try:
+        prod = fetch_plot_detail(http, url, crop, state, year, plot_id)
+    except Exception as exc:  # noqa: BLE001
+        log.error("detail fetch failed for %s: %s", url, exc)
+        return "failed", None
+    if prod is None:
+        return "missing", None
+    body = render_markdown(prod)
+    write_plot(prod, body)
+    return "written", prod
+
+
+def run(
+    *,
+    limit: int | None,
+    force: bool,
+    only_crop: str | None,
+    only_state: str | None,
+    only_year: int | None,
+    include_2023: bool,
+) -> int:
+    CORPUS_DIR.mkdir(parents=True, exist_ok=True)
+    http = RateLimitedSession()
+
+    crops = {only_crop} if only_crop else {"corn", "soybeans", "silage"}
+    states = {only_state} if only_state else None
+    if only_year:
+        years = {only_year}
+    elif include_2023:
+        years = {2023, 2024, 2025}
+    else:
+        years = {2024, 2025}
+
+    targets = discover_plots(http, crops=crops, states=states, years=years)
+
+    counts = {"written": 0, "skipped": 0, "missing": 0, "failed": 0}
+    processed = 0
+    for url, crop, state, year, plot_id in targets:
+        if limit is not None and processed >= limit:
+            break
+        processed += 1
+        status, prod = process_plot(
+            http, url=url, crop=crop, state=state, year=year,
+            plot_id=plot_id, force=force,
+        )
+        counts[status] = counts.get(status, 0) + 1
+        if prod is not None and processed <= 5 or processed % 100 == 0:
+            log.info(
+                "[%d/%s] %s %s | results=%d coop=%s",
+                processed, str(limit) if limit else len(targets),
+                source_key_for(crop, state, year, plot_id), status,
+                len(prod.results) if prod else 0,
+                (prod.cooperator if prod else "-") or "-",
+            )
+
+    log.info(
+        "done: processed=%d written=%d skipped=%d missing=%d failed=%d (of %d candidates)",
+        processed, counts["written"], counts["skipped"],
+        counts["missing"], counts["failed"], len(targets),
+    )
+    return 0 if counts["failed"] == 0 else 1
+
+
+# --------------------------------------------------------------------- CLI
+
+
+def _build_argparser() -> argparse.ArgumentParser:
+    p = argparse.ArgumentParser(
+        prog="scrape.sources.gh_plot_reports",
+        description="Scrape Golden Harvest cross-vendor plot reports (yield trials).",
+    )
+    p.add_argument("--limit", type=int, default=None,
+                   help="Stop after processing N plots (default: all).")
+    p.add_argument("--force", action="store_true",
+                   help="Re-fetch even if the markdown file already exists.")
+    p.add_argument("--crop", default=None,
+                   choices=("corn", "soybeans", "silage"),
+                   help="Limit to one crop.")
+    p.add_argument("--state", default=None,
+                   help="Limit to one state (2-letter abbrev: ia, il, ne, ...).")
+    p.add_argument("--year", type=int, default=None, choices=(2023, 2024, 2025),
+                   help="Limit to one year.")
+    p.add_argument("--include-2023", action="store_true",
+                   help="Include 2023 plot reports (default: 2024-2025 only).")
+    p.add_argument("--log-level", default=os.environ.get("LOG_LEVEL", "INFO"))
+    return p
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = _build_argparser().parse_args(argv)
+    logging.basicConfig(
+        level=args.log_level.upper(),
+        format="%(asctime)s %(levelname)s %(name)s %(message)s",
+        stream=sys.stderr,
+    )
+    return run(
+        limit=args.limit,
+        force=args.force,
+        only_crop=args.crop,
+        only_state=args.state.lower() if args.state else None,
+        only_year=args.year,
+        include_2023=args.include_2023,
+    )
+
+
+if __name__ == "__main__":
+    sys.exit(main())
@@ -5,8 +5,16 @@
    {
      "name": "bayer_seeds",
      "vendor": "Bayer",
-      "brands": ["DEKALB", "Asgrow", "WestBred"],
-      "crops": ["corn", "soybeans", "wheat"],
+      "brands": [
+        "DEKALB",
+        "Asgrow",
+        "WestBred"
+      ],
+      "crops": [
+        "corn",
+        "soybeans",
+        "wheat"
+      ],
      "verdict": "green",
      "expected_count": 475,
      "base_url": "https://cropscience.bayer.us",
@@ -17,65 +25,124 @@
    {
      "name": "golden_harvest",
      "vendor": "Syngenta",
-      "brands": ["Golden Harvest"],
-      "crops": ["corn", "soybeans"],
+      "brands": [
+        "Golden Harvest"
+      ],
+      "crops": [
+        "corn",
+        "soybeans"
+      ],
      "verdict": "green",
      "expected_count": 175,
      "base_url": "https://www.goldenharvestseeds.com",
      "scope_filter": "All sitemap-listed corn + soybean varieties.",
      "tos_check_date": "2026-05-25",
-      "schema_notes": "Disease ratings published on 9-to-1 scale (9 = best). Normalize to 1-9 (9 = best) at chunk time to match Bayer/NK/AgriPro convention. Note original direction in chunk_0 preamble. Tech-sheet PDF URLs in the sitemap are stale (250331) — resolve live URL from product HTML, not sitemap entry."
+      "schema_notes": "Disease ratings published on 9-to-1 scale (9 = best). Normalize to 1-9 (9 = best) at chunk time to match Bayer/NK/AgriPro convention. Note original direction in chunk_0 preamble. Tech-sheet PDF URLs in the sitemap are stale (250331) \u2014 resolve live URL from product HTML, not sitemap entry."
    },
    {
      "name": "nk",
      "vendor": "Syngenta",
-      "brands": ["NK"],
-      "crops": ["corn", "soybeans"],
+      "brands": [
+        "NK"
+      ],
+      "crops": [
+        "corn",
+        "soybeans"
+      ],
      "verdict": "green",
      "expected_count": 29,
      "base_url": "https://www.syngenta-us.com",
      "pdf_cdn": "https://assets.syngentaebiz.com/pdf/techsheets/",
      "scope_filter": "All NK corn + soy varieties. No wheat (NK doesn't sell wheat in US).",
      "tos_check_date": "2026-05-24",
-      "schema_notes": "Disease + agronomic ratings live in tech-sheet PDFs only — need pdfplumber. PDF URLs share format `<CODE>_YYMMDD.pdf` with Golden Harvest, so the same fetcher works for both."
+      "schema_notes": "Disease + agronomic ratings live in tech-sheet PDFs only \u2014 need pdfplumber. PDF URLs share format `<CODE>_YYMMDD.pdf` with Golden Harvest, so the same fetcher works for both."
    },
    {
      "name": "agripro",
      "vendor": "Syngenta",
-      "brands": ["AgriPro"],
-      "crops": ["wheat", "barley"],
+      "brands": [
+        "AgriPro"
+      ],
+      "crops": [
+        "wheat",
+        "barley"
+      ],
      "verdict": "green",
      "expected_count": 24,
      "base_url": "https://www.agriprowheat.com",
-      "scope_filter": "All wheat classes (HRW/HRS/HWS/SWW/SWS) + barley. NO SRW — Syngenta's SRW lives at GrowProGenetics.com under a separate brand.",
+      "scope_filter": "All wheat classes (HRW/HRS/HWS/SWW/SWS) + barley. NO SRW \u2014 Syngenta's SRW lives at GrowProGenetics.com under a separate brand.",
      "tos_check_date": "2026-05-24",
      "schema_notes": "Drupal Views form; server-rendered HTML. CoAXium trait flag is implicit in product family; Clearfield/CL2 trait IS in this catalog."
    },
    {
      "name": "becks_pfr",
      "vendor": "Beck's Hybrids",
-      "brands": ["Beck's PFR"],
-      "crops": ["corn", "soybeans", "wheat"],
+      "brands": [
+        "Beck's PFR"
+      ],
+      "crops": [
+        "corn",
+        "soybeans",
+        "wheat"
+      ],
      "verdict": "yellow",
      "expected_count": 2089,
      "base_url": "https://www.beckshybrids.com",
      "api_base": "https://mc8v24rf.api.sanity.io",
-      "scope_filter": "All Practical Farm Research publications since 2015. PFR is head-to-head agronomy trials — fungicide timing, planting-date studies, hybrid-by-population, etc.",
+      "scope_filter": "All Practical Farm Research publications since 2015. PFR is head-to-head agronomy trials \u2014 fungicide timing, planting-date studies, hybrid-by-population, etc.",
      "tos_check_date": "2026-05-24",
-      "schema_notes": "Public Sanity GROQ API, no auth required. Records have title/year/crop/key-findings/full-text. Treat PFR docs as a research corpus, not variety records — the chunk_0 includes the study's tl;dr finding."
+      "schema_notes": "Public Sanity GROQ API, no auth required. Records have title/year/crop/key-findings/full-text. Treat PFR docs as a research corpus, not variety records \u2014 the chunk_0 includes the study's tl;dr finding."
    },
    {
      "name": "becks_products",
      "vendor": "Beck's Hybrids",
-      "brands": ["Beck's"],
-      "crops": ["corn", "soybeans", "wheat"],
+      "brands": [
+        "Beck's"
+      ],
+      "crops": [
+        "corn",
+        "soybeans",
+        "wheat"
+      ],
      "verdict": "yellow",
      "expected_count": 860,
      "base_url": "https://www.beckshybrids.com",
      "api_base": "https://mc8v24rf.api.sanity.io",
-      "scope_filter": "All Beck's product records — corn + soy + wheat. Identity + RM/MG only.",
+      "scope_filter": "All Beck's product records \u2014 corn + soy + wheat. Identity + RM/MG only.",
      "tos_check_date": "2026-05-24",
      "schema_notes": "Sanity GROQ exposes identity (name, RM/MG, basic traits) but agronomic + disease ratings are SeedIQ-gated (requires browser cookie). Deferred until the SeedIQ XHR endpoint is captured from a logged-in browser session. Without ratings, products are reference-only; the MCP can confirm 'Beck's has hybrid X at RM 112 with Enlist trait' but not 'rate it against drought'."
+    },
+    {
+      "name": "gh_plot_reports",
+      "vendor": "Syngenta",
+      "brand_aggregator": "Golden Harvest publishes",
+      "crops": [
+        "corn",
+        "soybeans",
+        "silage"
+      ],
+      "verdict": "green",
+      "expected_count": 4618,
+      "base_url": "https://www.goldenharvestseeds.com",
+      "scope_filter": "sitemap-listed plot reports 2024 and 2025 (4,618 reports). 2023 (3,619 reports) deferred to a future pass \u2014 most recent data is most relevant for current decisions.",
+      "tos_check_date": "2026-05-25",
+      "schema_notes": "Cross-vendor head-to-head yield trials at specific state/year/site. Each report lists products from multiple brands (NK, DEKALB, GH, etc.) with rank, yield, %MST, test weight, gross revenue. URL: /<crop>/plot-report/<state>/<year>/<id>. Same site/auth as golden_harvest variety scraper.",
+      "data_type": "trial"
+    },
+    {
+      "name": "agripro_trials",
+      "vendor": "Syngenta",
+      "brand_aggregator": "AgriPro publishes",
+      "crops": [
+        "wheat"
+      ],
+      "verdict": "green",
+      "expected_count": 38,
+      "base_url": "https://agriprowheat.com",
+      "scope_filter": "PDF trial summaries linked from /trials-data. Regional wheat performance (PNW, Western Plains, NE Colorado, etc.).",
+      "tos_check_date": "2026-05-25",
+      "schema_notes": "PDF tables of varieties tested per region per year. pdfplumber for table extraction.",
+      "data_type": "trial"
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