Precision agriculture for iceberg lettuce: From spatial sensing to per plant decision making and control

Abstract

Precision agriculture enables growers to sense growth in the field and take actions at a high resolution. In this context, agriculture can be considered a feedback system, and feedback control algorithms are a promising approach for decision-making at a per-plant level. We present a control approach to assign per-plant nitrogen prescriptions for iceberg lettuce, with the objective of reducing variability at harvest and, as a result, increasing yield. The per-plant nitrogen inputs were generated using a proportional consensus-protocol style controller and non-destructive measurements of growth. This resulted in smaller lettuce plants receiving an increased dose of nitrogen and oversized plants receiving a decreased dose. In this paper, we present the results of three in-field trials applying the controller to real plants with manual applications. Our results demonstrated a reduction in the plant mass variance of outdoor crop in two of our three farm trials (32.6% and 19.7% lower variance in comparison to cohorts with a typical approach). This is a promising result, which could be improved in future work by developing a more accurate proxy measurement for crop growth and accounting for soil nitrogen.