2024 Western Society of Crop Science Meeting Recap
Bibliographic record
Abstract
Attendees of this year’s Western Society of Crop Science (WSCS) meeting gather for a photo during a farm tour in Chualar, CA in July. The Western Society of Crop Science (WSCS) is a CSSA branch that comprises western states, territories, and provinces in Canada, Mexico, and the U.S. The WSCS 2024 meeting was held in Seaside, CA from July 17–18. The theme of the meeting was the same as that of the 2024 ASA, CSSA, and SSSA Annual Meeting, “AI Innovations for a Changing Climate.” The meeting was hosted by Arun Jani, Assistant Professor in the Department of Biology and Chemistry at California State University, Monterey Bay. This meeting is a great opportunity to network with colleagues and students from around the West and exchange scientific information. The meeting was attended by participants from several institutions, including New Mexico State University, University of Nevada (Reno), Utah State University, Montana State University, California State University (Chico and Monterey Bay), University of California (Santa Cruz and Davis), Oregon State University, and USDA (ARS and NRCS). Also attending were students and researchers from Kansas State University (outside of the WSCS region) and industries like Vilmorin-Mikado, Driscoll’s Inc., Wilbur-Ellis, and Wintersteiger. Professional participation increased significantly this year. This year, participants arrived on Tuesday, July 16. Activities started the next day with a welcome from Dr. Jani and WSCS President Sandya Kesoju. The session began with remarks from CSSA President Kim Garland-Campbell and speakers from industry who talked about the latest technology, developments, and sustainable agriculture. This was followed by student oral and poster presentation competitions and professional oral and poster presentations. The second day of the meeting began with agricultural tours organized by Gina Bella Colfer, a pest control adviser and Certified Crop Adviser (CCA) with Wilbur-Ellis. Meeting participants first stopped on a farm in Chualar, CA to learn about automated weeding technologies used in the region (Figure 1). Mr. Sal Espinosa of Stout Technologies demonstrated and discussed automated weeding technologies in specialty crop production like lettuce and explained how the sensor uses computer vision and machine learning to identify weeds. Participants had an opportunity to see the equipment in operation cultivating weeds while leaving lettuce plants alone. The next stop was Taylor Farms, also in Chualar where attendees had an opportunity to learn about cool-season vegetable production and organic farming. They met the 2024 Organic Farmer of the Year, Larry Santos, who shared his experience working with cool-season vegetables and producing them organically. Santos answered questions raised by the participants and showed them fields of broccoli, lettuce, and other vegetables grown organically. Broccoli was harvested and packed in the field (Figure 2). After the tour, professional presentations and the WSCS business meeting took place at the University Center Auditorium. Every year, the WSCS offers the A.K. Dobrenz Student Awards for the student oral and poster presentations. Awards included certificates and monetary prizes. The first-place winner of the oral competition also received a travel stipend to attend the CSSA International Annual Meeting. The 2024 winners of the student oral competition were: first place—McKenna Carnahan (Utah State University); second place—Luis Esquivel-Cervantes (Montana State University); and third place—Brielle Liske (California State University, Monterey Bay). Poster presentation winners were first place—Megan Baker (Utah State University); second place—Curtis Bireley (California State University, Monterey Bay), and third place—Alex Rodriguez (California State University, Monterey Bay). There were no eligible applicants this year for the Emerging Scientist Award. We congratulate the award winners and wish them great success in their future careers. We are grateful to Sarah Paese, Member Experience Coordinator for the Societies, for her efforts to help organize the 2024 meeting. Special thanks are extended to Dr. Kim Garland-Campbell, President of CSSA, for opening remarks and encouragement for students’ success. We would like to extend our thanks to our industry partners for providing financial assistance (Vilmorin-Mikado and Driscoll’s Inc.) for lunch and the banquet dinner and organizing agricultural tours (Wilbur-Ellis). The event wouldn’t have been successful without their support. We are also grateful to Dr. Arun Jani for hosting the meeting at California State University, Monterey Bay; the program section moderators; the student oral and poster competition judges; and all speakers for making this year’s program successful.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".