Assessing approaches for stratifying producer fields based on biophysical attributes for regional yield-gap analysis

Large databases containing producer field-level yield and management records can be used to identify causes of yield gaps. A relevant question is how to account for the diverse biophysical background (i.e., climate and soil) across fields and years, which can confound the effect of a given management practice on yield. Here we evaluated two approaches to group producer fields based on biophysical attributes: (i) a technology extrapolation domain spatial framework (‘TEDs’) that delineates regions with similar (long-term average) annual weather and soil water storage capacity and (ii) clusters based on field-specific soil properties and weather during each crop phase in each year. As a case study, we used yield and management data collected from 3462 rainfed fields sown with soybean across the North Central US (NC-US) during four growing seasons (2014–2017). Following the TED approach, fields were grouped into 18 TEDs based on the TED that corresponded to the geographic location of each field. In the cluster approach, fields were grouped into clusters based on similarity of in-season weather and soil. To evaluate how the number of clusters would affect the results, fields were grouped separately into 5, 10, 18, and 30 clusters. The two stratification approaches (TEDs and clusters) were compared on their ability to explain the observed yield variation and yield response to key management factors (sowing date and foliar fungicide and/or insecticide). Lack of stratification of producer fields based on their biophysical background ignored management by environment (M×E) interactions, leading to spurious relationships and results that are not relevant at local level. In the case of the cluster approach, a fine stratification (18 and 30 clusters) explained a larger portion of the yield variance compared with a coarse stratification (5 and 10 clusters). However, for our case study in the NC-US region, we did not find strong evidence that the data-rich clustering approach outperformed the TEDs on the ability to explain yield variation and identify M×E interactions. Only the stratification into 30 clusters exhibited a small improved ability at explaining yield variation compared with the TEDs. However, the use of the clustering approach had important trade-offs, including large amount of data requirements and difficulties to scale results to different regions and over time. The choice of the stratification method should be based on objectives, data availability, and expected variation in yield due to erratic weather across regions and years

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

Nutrient Applications Reported by Farmers Compared with Performance‐Based Nutrient Management Plans

Bravo-Ureta, B (Bravo-Ureta, Boris)2,3;2. Univ Connecticut, Dep Agr & Resource Econ, Storrs, CT 06269 USA 3. Univ Talca, Dep Agr Econ, Talca, ChileThis study had two main objectives: (i) to evaluate how well farmers implemented nutrient management plans (NMPs) by comparing the farmers' reported practices with the recommended management for manure and fertilizer; and (ii) to evaluate whether the management of manure and fertilizer had significant effects on the nutrient status of soil and corn tissue tests. The analysis relied on data from four dairy farms that had 5 to 7 yr of records at the field level. The farmers chose to apply the recommended amount of fertilizer P from 50 to 100% of the fields. The amount applied was often only 10 to 20 kg P2O5 ha(-1) different from the recommended amount. The farmers applied the recommended amount of fertilizer N from 40 to 71% of the fields when the pre-sidedress soil nitrate test (PSNT) was used for the recommendation, but only 1 to 21% of the fields received the recommended amount when the yield goal method was used. These data suggest that the farmers trusted a fertilizer recommendation developed from a soil test more than they trusted a nonsoil test recommendation. Only a small percentage of fields (3-37%) received the recommended amount of manure N and P. Variability in the amount of residual N available from previous manure applications caused great variation in the PSNT and corn stalk nitrate values (CSNT). This variation in N availability in fields indicates that a number of years of data are needed before the PSNT and the CSNT can be used to objectively evaluate the performance of an NMP

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

Evaluation of fall applied liquid swine manure with encapsulated nitrapyrin

Fall applied liquid swine (Sus scrofa domesticus) manure (LSM) can lead to economic and environmental concerns due to potentially enhanced NO3 loss. Objectives of this study were to evaluate LSM application timing and use of Instinct nitrification inhibitor, and compare to anhydrous ammonia (AA). Treatments were a no-N control, AA (without Instinct), and LSM with three Instinct rates applied each of 3 yr on October 1 (early fall) and November 1 (late fall). The effect of Instinct was inconsistent. Instinct increased soil NH4–N concentrations in fall (only early fall LSM application) and spring sampled LSM injection zones. However, in the late spring Instinct had no effect to minimal positive effect on soil inorganic–N, and the high rate was not more effective than the low rate. Corn (Zea mays L.) canopy normalized difference vegetative index (NDVI) was not influenced by Instinct or different between N source, and greatest with late fall N application. Across years, Instinct increased corn grain yield only when early fall applied with the low rate. However, LSM with Instinct had lower yield compared to AA. Waiting to apply N in late fall provided increased inorganic N retention, and with LSM higher corn yield. Based on this study, AA was a better fall applied N source compared to LSM with or without Instinct. A decision to use Instinct with LSM must weigh cost of the inhibitor against other options, such as delayed fall or spring application, or use of AA