Field validation of a farmer supplied data approach to close soybean yield gaps in the US North Central region

Andrade, José F.; Mourtzinis, Spyridon; Edreira, Juan I. Rattalino; Conley, Shawn P.; Gaska, John; Kandel, Hans; Lindsey, Laura E.; Naeve, Seth L.; Nelson, Scott M.; Singh, Maninder P.; Thompson, Laura J.; Specht, James E.; Grassini, Patricio

doi:10.1016/j.agsy.2022.103434

Cited by 23 publications

(5 citation statements)

References 27 publications

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“…Grain yield gaps averaged 859 kg ha −1 , which is similar to previous reports for this region (de Oliveira Silva et al., 2020, 2021; Jaenisch et al., 2019, 2021, 2022). While the current study considered a general improvement in management through a high‐input practice and a couple of alternative practices restricting either foliar fungicides or nitrogen rates, at the farmer level such a high input may not be justifiable due to economic constraints, and therefore, the refinement of the recommendations should be specific to each production system (Andrade et al., 2022; Jaenisch et al., 2021). Nonetheless, through stability analysis, we showed that yield gaps were larger in higher yielding seasons, suggesting a greater opportunity‐cost of the farmer practice when conditions are favorable.…”

Section: Discussionmentioning

confidence: 99%

Intensive management simultaneously reduces yield gaps and improves milling and baking properties of bread wheat

et al. 2023

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Genotype (G), environment (E), management (M), and their interactions determine grain yield, biochemical composition, and quality of wheat. However, we are not aware of studies evaluating whether intensive management can simultaneously reduce yield gaps and improve wheat milling and baking attributes, which were our main objectives. A factorial experiment of five genotypes × four management intensities (farmer practice, high-input, high-input minus nitrogen, and high-input minus fungicide) was conducted in six Kansas (United States) environments resulting from the combination of four locations and three seasons. Grain yield and 13 parameters characterizing the grain (test weight [TWT], thousand kernel weight [TKW], grain protein [GP]), flour (e.g., ash, protein), dough (e.g., water absorption [WA],dough stability [DS]), and baking qualities (loaf volume [LV]) were measured. For most variables, the primary contributor of the variance was E while M and G were secondary and tertiary contributors, except for LV in which G was a larger moderator. High input practices increased yield (4206 kg ha −1 ) compared to farmer practice (3347 kg ha −1 ) suggesting a yield gap of 859 kg ha −1 . Management intensities receiving foliar fungicides improved grain properties related to milling characteristics (i.e., TKW and TWT), while management intensities receiving more nitrogen improved baking characteristics (e.g., WA and DS). Across sources of variation, yield response to improved management associated positively with the responses of TKW, TWT, and in some cases, GP, and WA. Our results showed the possibility of simultaneously improving grain yield and selected milling and baking attributes of bread wheat genotypes through intensive management.Abbreviations: DDT, dough development time (min); DS, dough stability (min); FA, flour ash (%); FNV, falling number (s); FST, farinograph stability (min); FY, flour yield (%); G, genotype; GP, grain protein (%); GY, grain yield (kg ha −1 ); HWW, hard winter wheat; LV, loaf volume (mL); MTI, mixing tolerance index (BU); TKW, thousand kernel weight (g); TWT, test weight (kg hl −1 ); WA, water absorption.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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Section: Discussionmentioning

confidence: 99%

Intensive management simultaneously reduces yield gaps and improves milling and baking properties of bread wheat

et al. 2023

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“…As described earlier, the vast number of parameters and decisions call for the development and use of tools that go beyond the capabilities of traditional research. Data‐driven knowledge, built upon years of extensive data collection efforts (Rattalino Edreira et al., 2017) and validated in subsequent field trials (Andrade et al., 2022), can be a powerful alternative to traditional randomized trials. Use of machine learning algorithms that can capture complex associations in high‐dimensional data can be a promising approach.…”

Section: Discussionmentioning

confidence: 99%

Corn and soybean planting order decisions impact farm gross revenue

Mourtzinis

Conley

2023

Crop Forage & Turfgrass Mgmt

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The inter‐annual corn‐soybean rotation field is a well‐known management practice that increases the yield of both crops across the midwestern US. Each spring, farmers must decide which crop will be planted first. Prioritizing planting of one crop can delay planting of the other which can result in substantial yield loss and reduced associated revenue. The objective of this work was to assess how gross farm revenue (corn + soybean acres) can be affected by crop planting order (corn first, soybean second and vice versa). The impact of variable planting dates on the yield of each crop was simulated for 310 fields across the US. Gross farm revenue was estimated as a function of crop planting date, order, input costs and crop prices. In a randomly chosen field in south central Wisconsin, 1 out of the 310, delaying planting after May 1st reduced yield of each crop and subsequently suppressed gross farm revenue. Crop planting order determined farm revenue due to a variable loss in per day yield rate within the nominal planting timeframe associated with the two crops. Additionally, the degree to which management was intensified for each crop relative to crop yield potential accruing with earlier planting, varied by state, and further impacted farm revenue. Overall results suggest that to determine planting order US farmers need to be aware of the comparative yield trends associated with delayed planting of corn vs. soybean for their specific farms and cropping systems and should also account for projected crop selling prices.This article is protected by copyright. All rights reserved

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“…Achieving this goal within a reasonable timeframe is possible using available robust approaches 26,44 . Continued closure of existing yield gaps in these intensive, high-yield cropping systems will depend in part on better K nutrition 10 .…”

Section: Discussionmentioning

confidence: 99%

The challenge of alleviating potassium limitation in major cropping systems of Southeast Asia

Grassini,

Rizzo,

Agus

et al. 2023

Preprint

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Potassium (K) has received less attention than nitrogen (N) and phosphorous (P) as a potential yield-limiting factor in cropping systems. Here we investigated the current K limitation in intensive cereal cropping systems of Southeast Asia based on nutrient balances, leaf nutrient status, long- and short-term fertilizer trials, and farmer surveys. We found that soil K alone cannot meet plant requirements and current fertilizer application is insufficient to avoid plant K deficiencies and large negative soil K balances in farmer fields. Removing the K limitation requires improved capacity to predict response to K fertilizer together with long-term, flexible fertilizer and crop straw management strategies. It is likely that similar K limitations have emerged in other world regions as a result of decades of intensive cropping with insufficient replenishment of potassium, which represent headwinds to closing yield gaps on existing farmland.

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Field validation of a farmer supplied data approach to close soybean yield gaps in the US North Central region

Cited by 23 publications

References 27 publications

Intensive management simultaneously reduces yield gaps and improves milling and baking properties of bread wheat

Intensive management simultaneously reduces yield gaps and improves milling and baking properties of bread wheat

Corn and soybean planting order decisions impact farm gross revenue

The challenge of alleviating potassium limitation in major cropping systems of Southeast Asia

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