Globally, flooding is one of the most damaging abiotic stresses, besides drought, that affects 17 million km 2 of land surface annually. Recent research indicates that climate change is resulting in more extreme weather events, such as flooding or soil waterlogging, that negatively affect crop production. Therefore, it is imperative to understand how flooding stress affects crops and to develop improved production practices that make cropping systems more resilient and able to cope with extreme weather events. This review paper summarizes the current state of knowledge on the impacts of flooding or soil waterlogging on crop production losses, nitrogen (N) losses, and provides potential management strategies to reduce these losses. The factors affecting the extent of flooding injury in plants as well as plant adaptations under waterlogging stress are also discussed briefly. For the purpose of this review, "flooding" refers to the situation when all or part of the plant is submerged under water, whereas "soil waterlogging" refers to the situation where soil pores are saturated with water. Soil waterlogging also promotes soil N losses through runoff, leaching, and denitrification. Potential management practices that can be used to mitigate soil waterlogging stress include the use of flood-tolerant varieties, adjusting management practices, improving drainage, and practicing adaptive nutrient management strategies. However, these might be site-or crop-specific management practices and they should be validated for their economic viability before developing future management plans that promote sustainable crop yields from waterlogged soils.Abbreviations: BMP, Best Management Practice; CDSI, controlled drainage and subirrigation; EEF, enhanced efficiency fertilizer; ET, evapotranspiration; Fv/Fm, ratio of variable fluorescence to material fluorescence; GIS, Geographic Information System; NBPT, N-(n-butyl) thiophosphoric triamide; NI, nitrification inhibitor; NUE, nitrogen use efficiency; PCU, polymer-coated urea; UI, urease inhibitors.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Soybean [Glycine max (L.) Merr.] seed composition and yield are a function of genetics (G), environment (E), and management (M) practices, but contribution of each factor to seed composition and yield are not well understood. The goal of this synthesis-analysis was to identify the main effects of G, E, and M factors on seed composition (protein and oil concentration) and yield. The entire dataset (13,574 data points) consisted of 21 studies conducted across the United States (US) between 2002 and 2017 with varying treatments and all reporting seed yield and composition. Environment (E), defined as site-year, was the dominant factor accounting for more than 70% of the variation for both seed composition and yield. Of the crop management factors: (i) delayed planting date decreased oil concentration by 0.007 to 0.06% per delayed week (R2∼0.70) and a 0.01 to 0.04 Mg ha-1 decline in seed yield per week, mainly in northern latitudes (40–45 N); (ii) crop rotation (corn-soybean) resulted in an overall positive impact for both seed composition and yield (1.60 Mg ha-1 positive yield difference relative to continuous soybean); and (iii) other management practices such as no-till, seed treatment, foliar nutrient application, and fungicide showed mixed results. Fertilizer N application in lower quantities (10–50 kg N ha-1) increased both oil and protein concentration, but seed yield was improved with rates above 100 kg N ha-1. At southern latitudes (30–35 N), trends of reduction in oil and increases in protein concentrations with later maturity groups (MG, from 3 to 7) was found. Continuing coordinated research is critical to advance our understanding of G × E × M interactions.

Growing conditions in the U.S. Midsouth allow for large soybean [Glycine max L. (Merr.)] yields under irrigation, but there is limited information on planting dates (PD) and maturity group (MG) choices to aid in cultivar selection. Analysis of variance across eight (2012) and 10 (2013) locations, four PD, and 16 cultivars (MG 3-6), revealed that the genotype by environment (G×E) interaction accounted for 38 to 22% of the total yield variability. Stability-analysis techniques and probability of low yields were used to investigate this interaction. Planting dates were grouped within early-and late-planting systems. Results showed that MG 4 and 5 cultivars in early-planting systems had the largest average yields, whereas for late-planting systems, late MG 3 to late MG 4 cultivars had the largest yields. Least square means by MG within planting systems at each environment showed that MG 4 cultivars had the greatest yields or were not signi cantly di erent from the MG with the greatest yields in 100% of the environments for both early-and late-planting systems. Yields of MG 5 cultivars were similar to those of MG 4 in 100% of the environments with an early planting but only in 20% of the environments with a late planting. e MG 3 cultivars were the best second choice for late plantings, with similar yields to MG 4 cultivars in 55 to 75% of the environments. ese results have profound implications for MG recommendations in irrigated soybean in the U.S. Midsouth and indicate the need to reconsider common MG recommendations.