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

CONTEXT: Producer-reported data can be used to identify suites of management practices that lead to higher yield and profit. However, a rigorous validation of the approach in relation to its potential impact on farmer yield and profit is lacking. OBJECTIVE: This study aimed to validate a producer-data approach on its capability to guide on-farm evaluation of management practices with greatest potential for increasing producer yield and profit. We show proof of concept using soybean in the North Central US region as a case study. METHODS: We used a combination of regression tree analysis and a spatial framework to determine practices with highest influence on yield for specific climate domains across the region. These practices were used as a basis for designing an ‘improved’ management package for each domain. The impact associated with adoption of the ‘improved’ management package on producer yield, seed constituents, and profit was evaluated against a ‘reference’ treatment that follows farmer management via replicated on-farm trials across 100 sites over two crop seasons. RESULTS AND CONCLUSIONS: Average yield was 278 kg ha-1 higher in the improved versus reference management, equivalent to a closure of the current exploitable yield gap by 40%. In turn, adoption of the improved management led to an average increase of $76 ha-1 in net profit. Sensitivity analysis showed that adoption of the improved management packages should increase farmer profit across a wide range of grain price scenarios, with very small downside risk. Seed protein concentration was negatively associated with the positive yield advantage of the improved management, whereas seed oil concentration tended to increase. SIGNIFICANCE: Analysis of producer data can accelerate discovery, evaluation, and adoption of suites of management practices that consistently lead to higher farmer yield and profit, which, in turn, would help speed up current rates of yield gain

Simple regression models to estimate light interception in wheat crops with Sentinel‐2 and a handheld sensor

Capture of radiation by crop canopies drives growth rate, grain set, and yield. Since the fraction of photosynthetically active radiation absorbed by green area (fAPARg) correlates with normalized difference vegetation index (NDVI), remote sensors have been used to monitor vegetation. With a 10-m spatial resolution and 5-d revisiting time, the recently launched Sentinel-2 satellite is a promising tool for fAPARg monitoring. However, the available algorithm to estimate fAPARg is based on simulations of canopy interception of several vegetation types and was never tested in field crops. Handheld sensors, such as GreenSeeker, are another alternative to estimate fAPARg. Our objectives were (a) to test the ability of indices derived from Sentinel-2 and GreenSeeker NDVI to capture fAPARg of wheat (Triticum aestivum L.) crops, (b) to compare these sensors’ performance against the moderate resolution imaging spectroradiometer (MODIS), and (c) to compare our Sentinel-2 model estimations with the available algorithm. In wheat fields in the southwest Argentinean Pampas, on several sampling dates, we measured fAPARg with a quantum light sensor and NDVI with a GreenSeeker. We regressed fAPARg measurements with vegetation indices from the different sources and selected the best models. Sentinel-2 and GreenSeeker NDVI precisely estimated fAPARg, with a performance similar to MODIS (p <.05; RMSD = 0.09, 0.11, and 0.08; R2 =.89,.88, and.95, respectively). The available algorithm to estimate fAPARg with Sentinel-2 yielded biased estimations, mainly in the lower range of fAPARg. These results suggest that simple models may provide fAPARg estimations with Sentinel-2 and GreenSeeker in wheat crops with an accuracy suitable for agricultural applications.Fil: Pellegrini, Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; ArgentinaFil: Cossani, Cesar Mariano. South Australian Research And Development Institute; Australia. University of Adelaide; AustraliaFil: Di Bella, Carlos Marcelo. Universidad de Buenos Aires; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Piñeiro, Gervasio. Universidad de Buenos Aires; Argentina. Universidad de la Republica; Uruguay. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sadras, Victor Oscar. University of Adelaide; Australia. South Australian Research And Development Institute; Australia. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; ArgentinaFil: Oesterheld, Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentin

Kernel weight responses to the photo-thermal environment in maize dent × flint and flint × flint hybrids

Maize (Zea mays, L.) grain yield is assumed to be source limited during the flowering period but sink limited during grain growth; however, environmental restrictions during active grain filling may strongly affect final kernel weight (KW). In this study we evaluated the effect of natural changes in photo‐thermal conditions during lag phase (LP) and effective grain‐filling period (EGFP) on KW, its physiological determinants, and the post‐flowering source‐sink relationships of flint and semident germplasm. F1 hybrids of flint × flint and dent × flint background were tested during four seasons (Y1, Y2, Y3 and Y4). Across years, the highest KW (286 mg) was obtained under the maximum photo‐thermal quotients during LP (PTQLP: 1.18 MJ m−2 °C−1) and EGFP (PTQEGFP: 1.07 MJ m−2 °C−1) of Y2, whereas the smallest KW (252 mg) and source‐sink ratio during grain filling was obtained under the lowest PTQEGFP (.79 MJ m−2 °C−1) of Y3. Supra‐optimum temperatures during LP of Y3 negatively affected potential KW determination, and hence kernel growth rate (P < .001) as a result of reduced assimilate availability per kernel. Hybrids dent × flint exhibited higher grain yield, kernel number and plant growth around flowering than flint × flint throughout evaluated seasons, but had reduced source‐sink relationship during grain filling (P < .05) and increased KW sensitivity (P < .001) to changes in the photo‐thermal conditions. Results emphasized the importance of the photo‐thermal environment during grain filling on KW determination (particularly for seasons with great photo‐thermal imbalance between filling sub‐phases) as well as the dependency of KW responses on the genetic background.EEA PergaminoFil: Hisse, Ignacio R. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; ArgentinaFil: Hisse, Ignacio R. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: D'Andrea, Karina Elizabeth. Consejo Nacional de Investigaciones, Científicas y Técnicas; ArgentinaFil: D´Andrea, Karina Elizabeth. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; ArgentinaFil: Otegui, María Elena. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Ecofisiología; ArgentinaFil: Otegui, María Elena. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Producción Vegetal; ArgentinaFil: Otegui, María Elena. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Management strategies for early- and late-planted soybean in the north-central United States

It is widely recognized that planting soybean [Glycine max (L.) Merr.] early is critical to maximizing yield, but the influence of changing management factors when soybean planting is delayed is not well understood. The objectives of this research were to (a) identify management decisions that increase seed yield in either early- or late-planted soybean scenarios, and (b) estimate the maximum break-even price of each management factor identified to influence soybean seed yield in early- or late-planted soybean. Producer data on seed yield and management decisions were collected from 5682 fields planted with soybean during 2014−2016 and grouped into 10 technology extrapolation domains (TEDs) based on growing environment. A subsample of 1512 fields was classified into early- and late-planted categories using terciles. Conditional inference trees were created for each TED to evaluate the effect of management decisions within the two planting date timeframes on seed yield. Management strategies that maximized yield and associated maximum break-even prices varied across TEDs and planting date. For early-planted fields, higher yields were associated with artificial drainage, insecticide seed treatment, and lower seeding rates. For late-planted fields, herbicide application timing and tillage intensity were related to higher yields. There was no individual management decision that consistently increased seed yield across all TEDs

Management strategies for early- and late-planted soybean in the north-central United States

It is widely recognized that planting soybean [Glycine max (L.) Merr.] early is critical to maximizing yield, but the influence of changing management factors when soybean planting is delayed is not well understood. The objectives of this research were to (a) identify management decisions that increase seed yield in either early- or late-planted soybean scenarios, and (b) estimate the maximum break-even price of each management factor identified to influence soybean seed yield in early- or late-planted soybean. Producer data on seed yield and management decisions were collected from 5682 fields planted with soybean during 2014−2016 and grouped into 10 technology extrapolation domains (TEDs) based on growing environment. A subsample of 1512 fields was classified into early- and late-planted categories using terciles. Conditional inference trees were created for each TED to evaluate the effect of management decisions within the two planting date timeframes on seed yield. Management strategies that maximized yield and associated maximum break-even prices varied across TEDs and planting date. For early-planted fields, higher yields were associated with artificial drainage, insecticide seed treatment, and lower seeding rates. For late-planted fields, herbicide application timing and tillage intensity were related to higher yields. There was no individual management decision that consistently increased seed yield across all TEDs.This article is published as Matcham, Emma G., Spyridon Mourtzinis, Shawn P. Conley, Juan I. Rattalino Edreira, Patricio Grassini, Adam C. Roth, Shaun N. Casteel et al. "Management strategies for early‐and late‐planted soybean in the north‐central United States." Agronomy Journal 112, no. 4 (2020): 2928-2943. doi:10.1002/agj2.20289. Posted with permission. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made

Management strategies for early‐ and late‐planted soybean in the north‐central United States

It is widely recognized that planting soybean [Glycine max (L.) Merr.] early is critical to maximizing yield, but the influence of changing management factors when soybean planting is delayed is not well understood. The objectives of this research were to (a) identify management decisions that increase seed yield in either early- or late-planted soybean scenarios, and (b) estimate the maximum break-even price of each management factor identified to influence soybean seed yield in early- or late-planted soybean. Producer data on seed yield and management decisions were collected from 5682 fields planted with soybean during 2014−2016 and grouped into 10 technology extrapolation domains (TEDs) based on growing environment. A subsample of 1512 fields was classified into early- and late-planted categories using terciles. Conditional inference trees were created for each TED to evaluate the effect of management decisions within the two planting date timeframes on seed yield. Management strategies that maximized yield and associated maximum break-even prices varied across TEDs and planting date. For early-planted fields, higher yields were associated with artificial drainage, insecticide seed treatment, and lower seeding rates. For late-planted fields, herbicide application timing and tillage intensity were related to higher yields. There was no individual management decision that consistently increased seed yield across all TEDs