Dataset Information

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean.

ABSTRACT: Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across three locations. We also measured germination parameter values of the three soybean cultivars from different maturity groups under controlled experiments to parametrize the SIMPLE crop emergence model. This allowed us to assess the prediction quality of the model for emergence rates and to perform simulations. Final emergence rates under field conditions ranged from 62% to 92% and from 51% to 94% for early and conventional sowing, respectively. The model finely predicted emergence courses and final rates (root mean square error of prediction (RMSEP), efficiency (EF), and mean deviation (MD) ranging between 2% to 18%, 0.46% to 0.99%, and -10% to 15%, respectively) across a wide range of the sowing conditions tested. Differences in the final emergence rates were found, not only among cultivars but also among locations for the same cultivar, although no clear trend or consistent ranking was found in this regard. Modeling suggests that seedling mortality rates were dependent on the soil type with up to 35% and 14% of mortality in the silty loam soil, due to a soil surface crust and soil aggregates, respectively. Non-germination was the least important cause of seedling mortality in all soil types (up to 3% of emergence losses), while no seedling mortality due to drought was observed. The average grain yield ranged from 3.1 to 4.0 t ha-1, and it was significantly affected by the irrigation regime (p < 0.001) and year (p < 0.001) but not by locations, sowing date or cultivars. We conclude that early sowing is unlikely to affect soybean emergence in South-West of France and therefore may represent an important agronomic lever to escape summer drought that markedly limit soybean yield in this region.

SUBMITTER: Lamichhane JR

PROVIDER: S-EPMC7493624 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean.

Lamichhane Jay Ram JR Aubertot Jean-Noël JN Champolivier Luc L Debaeke Philippe P Maury Pierre P

Frontiers in plant science 20200902

Soybean emergence and yield may be affected by many factors. A better understanding of the cultivar x sowing date x environment interactions could shed light into the competitiveness of soybean with other crops, notably, to help manage major biotic and abiotic factors that limit soybean production. We conducted a 2-year field experiments to measure emergence dynamics and final rates of three soybean cultivars from different maturity groups, with early and conventional sowing dates and across thr ...[more]

PMID: 32983214

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Project description:Crop yield is a highly complex quantitative trait. Historically, successful breeding for improved grain yield has led to crop plants with improved source capacity, altered plant architecture, and increased resistance to abiotic and biotic stresses. To date, transgenic approaches towards improving crop grain yield have primarily focused on protecting plants from herbicide, insects, or disease. In contrast, we have focused on identifying genes that, when expressed in soybean, improve the intrinsic ability of the plant to yield more. Through the large scale screening of candidate genes in transgenic soybean, we identified an Arabidopsis thaliana B-box domain gene (AtBBX32) that significantly increases soybean grain yield year after year in multiple transgenic events in multi-location field trials. In order to understand the underlying physiological changes that are associated with increased yield in transgenic soybean, we examined phenotypic differences in two AtBBX32-expressing lines and found increases in plant height and node, flower, pod, and seed number. We propose that these phenotypic changes are likely the result of changes in the timing of reproductive development in transgenic soybean that lead to the increased duration of the pod and seed development period. Consistent with the role of BBX32 in A. thaliana in regulating light signaling, we show that the constitutive expression of AtBBX32 in soybean alters the abundance of a subset of gene transcripts in the early morning hours. In particular, AtBBX32 alters transcript levels of the soybean clock genes GmTOC1 and LHY-CCA1-like2 (GmLCL2). We propose that through the expression of AtBBX32 and modulation of the abundance of circadian clock genes during the transition from dark to light, the timing of critical phases of reproductive development are altered. These findings demonstrate a specific role for AtBBX32 in modulating soybean development, and demonstrate the validity of expressing single genes in crops to deliver increased agricultural productivity.

Dataset Information

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean.

Publications

Combining Experimental and Modeling Approaches to Understand Genotype x Sowing Date x Environment Interaction Effects on Emergence Rates and Grain Yield of Soybean.

Similar Datasets

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