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

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. • In iceberg lettuce and other high value crop, variability at harvest reduces yield. • The field can be considered as a multi-agent system where each plant is an agent. • A consensus protocol can generate per-plant nitrogen doses to reduce crop variation. • This is model-free and requires only relative measurements of crop growth.

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Publication Details

Journal
Smart Agricultural Technology
Published
2025-01-22
DOI
https://doi.org/10.1016/j.atech.2025.100797
Citations
2
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
3.43
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article

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

William Rohde, Fulvio Forni
2 citations
Smart Agricultural Technology
Remote Sensing in Agriculture
3.43
article

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

William Rohde, Fulvio Forni
article en
2 citations

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. • In iceberg lettuce and other high value crop, variability at harvest reduces yield. • The field can be considered as a multi-agent system where each plant is an agent. • A consensus protocol can generate per-plant nitrogen doses to reduce crop variation. • This is model-free and requires only relative measurements of crop growth.

Smart Agricultural TechnologyVol. 10
University of Cambridge (GB), Bridge University (SS)
Zero hunger
Openalex Percentile: Top 11%
Remote Sensing in Agriculture
3.43
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Precision agriculture for iceberg lettuce: From spatial sensing to per plant decision making and control — William Rohde, Fulvio Forni · Smart Agricultural Technology (2025) | TGRS Research Map | TGRS