The California Strawberry Industry: Current Trends and Future Prospects
Bibliographic record
Abstract
Fruit production, plant production, genetics, technological advancements, food safety practices, and dedication to sustainable practices make California the most important strawberry production area in the world. California grew 16,303 hectares of strawberries in 2023 in three growing districts located along California’s Central Coast: Oxnard, Santa Maria and Watsonville-Salinas. Transplants are grown on approximately 1,627 ha at high and low elevation nurseries located up to a thousand km from fruit growing districts. Almost all fruit production is in open fields with a small amount under high plastic tunnels either in soil or on tabletops. Nursery production is almost all in open fields. In 2022, there were 13 public cultivars grown with the most popular being Monterey, Portola, Fronteras, Cabrillo, and San Andreas grown on 27%, 13%, 11%, 4% and 2% of the planted acres, respectively. All proprietary cultivars combined made up 39% of the planted acres. Fresh market makes up 81% of the harvested fruit with 19% destined for processing into concentrates, individually quick frozen, purees and juice. Most fruit are sold domestically (87%) while 13% is exported, the majority to Canada (62%) and Mexico (25%). The most important diseases are Macrophomina root rot, Fusarium wilt, Verticillium wilt, Phytophthora root rot, Botrytis fruit rot and powdery mildew. The most important arthropod pests are twospotted spider mite and Lygus bug. Current challenges include increased regulation on water quality, fumigants, pesticides, labor and increased urbanization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".