Each year, around April, almond industry experts assess crop conditions to generate an early-season yield estimate. This estimate serves as a tool for improving orchard management and resource use, particularly water and nitrogen. Sebastian Saa, associate director of agricultural research at the Almond Board of California (ABC), emphasized the importance of measurement, noting, “You cannot improve what you don’t measure.”
For 27 years, Terra Nova Trading has provided early crop estimates to fill the information gap between bloom and the USDA’s May forecast. Jerry Magdaleno of Terra Nova said over 500 orchards are assessed within days, with estimators walking up to ten miles daily. Despite careful methods, variables such as weather, crop drop, and human bias can affect accuracy. Magdaleno noted that market trends can influence perception, with bullish markets leading to lower crop size estimates and bearish ones inflating them.
Setton Farms’ Brian Ezzell participates in a team of 16–20 individuals compiling estimates using 24 years of historical data by county. Nut counts from over 100 trees help verify orchard productivity, as appearances can be misleading. Instead of averages, the team uses standard deviations to refine projections, which support budget planning, sales strategies, and equipment readiness.
Patrick Brown, professor of plant sciences at UC Davis, highlighted the value of predicting orchard-level yield to guide marketing, planning, and management. ABC is actively researching yield variation across counties and orchards. A project funded by ABC used a TOL harvester with a yield monitor to collect data at single-tree resolution. Findings identified large-scale variation drivers like orchard age, canopy volume, spring temperatures, and March precipitation. Smaller-scale factors included trunk growth, nutrition, fruit set, and soil type.
In addition to field data, UC Davis professor Yufang Jin is leading a project integrating remote sensing and machine learning to enhance yield prediction. Her team is building models that factor in long-term climate, soil conditions, and short-term weather events. Remote sensing detects tree health and stress not visible to the naked eye and allows for consistent monitoring through repeated imaging. The team’s initial findings pointed to key yield predictors including orchard age, cultivar mix, climate conditions, and canopy characteristics.
Through a combination of manual assessments, historical data, in-field sensors, and AI tools, researchers aim to provide growers with actionable insights. ABC continues to fund projects that enhance these methods and support data-driven decisions for almond orchard management.
For more information:
Almond Board of California
Tel: +1 209 549 8262
Email: [email protected]
www.almonds.com
