Ecoinformatics Can Reveal Yield Gaps Associated with Crop-Pest Interactions: A Proof-of-Concept

Abstract

Farmers and private consultants execute a vast, decentralized data collection effort with each cropping cycle, as they gather pest density data to make real-time pest management decisions. Here we present a proof of concept for an ecoinformatics approach to pest management research, which attempts to harness these data to answer questions about pest-crop interactions. The impact of herbivory by Lygus hesperus on cotton is explored as a case study. Consultant-derived data satisfied a ‘positive control’ test for data quality by clearly resolving the expected negative relationship between L. hesperus density and retention of flower buds. The enhanced statistical power afforded by the large ecoinformatics dataset revealed an early-season window of crop sensitivity, during which L. hesperus densities as low as 1-2 per sample were associated with yield loss. In contrast, during the mid-season insecticide use by farmers was often unnecessary, as cotton compensated fully for moderate L. hesperus densities. Because the dataset emerged from the commercial production setting, it also revealed the limited degree to which farmers were willing to delay crop harvest to provide opportunities for compensatory fruiting. Observational approaches to pest management research have strengths and weaknesses that complement those of traditional, experimental approaches; combining these methods can contribute to enhanced agricultural productivity.

A data‐driven, machine learning framework for optimal pest management in cotton

“…), experimental studies (Falcon et al. ), and a previous analysis of this data set (that was focused only on estimating yield loss) (Rosenheim and Meisner ) have all provided evidence for increased cotton sensitivity to L. hesperus herbivory early in the growing season.…”

An Observatory Plot System for Grain Production in the Neotropical Savannas

“…Its specific design, however, responds to our interest in identifying management by environment interactions characterizing the potential for site-specific grain agriculture in the region. Our approach is informed by the rapidly growing literature demonstrating the promise of ecoinformatics approaches to streamline agricultural research [13][14][15][16][17][18]. Based on these experiences, we believe our Dataset Paper holds significant potential to facilitate a quantum leap in agricultural research for the development of the Colombian savannas.…”

Towards pesticide-free farming? Sharing needs and knowledge promotes Integrated Pest Management

“…Notably, area-wide pest and biocontrol agent data collected by farmers during the grapevine growing season can be used to develop online databases helping decision-makers to do their IPM choices, predicting pest populations and outbreaks, allowing comparisons between growing sites over time. In addition, from a scientific point of view, these data contribute to the so-called eco-informatics approaches, being developed in several cropping systems (Michener and Jones 2012;Rosenheim and Meisner 2013). Besides, several comparable attempts on how to manage IPM decision in other cropping systems have been recently proposed for various herbaceous crops, including wheat (EuroWheat, www.…”