Abstract
Foliar fungicide usage in soybeans in the north-central United States increased steadily over the past two decades. An agronomically-interpretable machine learning framework was used to understand the importance of foliar fungicides relative to other factors associated with realized soybean yields, as reported by growers surveyed from 2014 to 2016. A database of 2738 spatially referenced fields (of which 30% had been sprayed with foliar fungicides) was fit to a random forest model explaining soybean yield. Latitude (a proxy for unmeasured agronomic factors) and sowing date were the two most important factors associated with yield. Foliar fungicides ranked 7th out of 20 factors in terms of relative importance. Pairwise interactions between latitude, sowing date and foliar fungicide use indicated more yield benefit to using foliar fungicides in late-planted fields and in lower latitudes. There was a greater yield response to foliar fungicides in higher-yield environments, but less than a 100 kg/ha yield penalty for not using foliar fungicides in such environments. Except in a few production environments, yield gains due to foliar fungicides sufficiently offset the associated costs of the intervention when soybean prices are near-to-above average but do not negate the importance of disease scouting and fungicide resistance management.
Highlights
The decade from 2005 to 2015 saw the use of foliar fungicides in U.S soybeans double on a per unit area basis (g of product applied per ha), and almost triple in terms of total product applied across all so-treated fields[22]
Together these basic tests were indicative of heterogenous effects concerning foliar fungicides and yield gain, implying other global and local conditions may be involved as factors
In subset 4 (s4), we examined the Shapley φ values associated with fungicide use among all 210 fields in the data matrix which had been sprayed with foliar fungicides but not with foliar insecticides (s4c1), and compared them to the Shapley φ values for foliar fungicide use among another cohort of 210 fields (s4c2) which had been sprayed with both foliar fungicides and insecticides, where the fields of s4c2 were sampled to match the range of reported yields in s4c1
Summary
The decade from 2005 to 2015 saw the use of foliar fungicides in U.S soybeans double on a per unit area basis (g of product applied per ha), and almost triple in terms of total product applied (tonnes) across all so-treated fields[22]. When foliar diseases are absent or at low levels, the consensus from recent field trials is that the yield response to foliar fungicides (including the plant health benefit effect) are not sufficient to offset the interventional c osts[16,17,19,20,21,27,28,29,30]. The format is expandable as more layers or data become a vailable[36] This approach leads to an observational database covering wide and diverse geographies, is broad in scope, and possibly capturing complex, realistic interactions among agronomic, environmental and crop management variables beyond those which may be represented in designed field trials. A ML algorithm was used to fit a yield prediction model to a grower-derived database on soybean production practices in the north‐central U.S The model was queried with the objective of understanding how foliar fungicides fit into overall soybean production practices in the north-central U.S and their contribution to yield from an economic standpoint
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