California Almond Yield Prediction at the Orchard Level With a Machine Learning Approach.

ABSTRACT: California's almond growers face challenges with nitrogen management as new legislatively mandated nitrogen management strategies for almond have been implemented. These regulations require that growers apply nitrogen to meet, but not exceed, the annual N demand for crop and tree growth and nut production. To accurately predict seasonal nitrogen demand, therefore, growers need to estimate block-level almond yield early in the growing season so that timely N management decisions can be made. However, methods to predict almond yield are not currently available. To fill this gap, we have developed statistical models using the Stochastic Gradient Boosting, a machine learning approach, for early season yield projection and mid-season yield update over individual orchard blocks. We collected yie

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC6656960 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature