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Research article - Peer-reviewed, 2020

Assessment of sowing dates and plant densities using CSM-CROPGRO-Soybean for soybean maturity groups in low latitude

Sampaio, L. S.; Battisti, R.; Lana, M. A.; Boote, K. J.

Abstract

Crop models can be used to explain yield variations associated with management practices, environment and genotype. This study aimed to assess the effect of plant densities using CSM-CROPGRO-Soybean for low latitudes. The crop model was calibrated and evaluated using data from field experiments, including plant densities (10, 20, 30 and 40 plants per m(2)), maturity groups (MG 7.7 and 8.8) and sowing dates (calibration: 06 Jan., 19 Jan., 16 Feb. 2018; and evaluation: 19 Jan. 2019). The model simulated phenology with a bias lower than 2 days for calibration and 7 days for evaluation. Relative root mean square error for the maximum leaf area index varied from 12.2 to 31.3%; while that for grain yield varied between 3 and 32%. The calibrated model was used to simulate different management scenarios across six sites located in the low latitude, considering 33 growing seasons. Simulations showed a higher yield for 40 pl per m(2), as expected, but with greater yield gain increments occurring at low plant density going from 10 to 20 pl per m(2). In Santarem, Brazil, MG 8.8 sown on 21 Feb. had a median yield of 2658, 3197, 3442 and 3583 kg/ha, respectively, for 10, 20, 30 and 40 pl per m(2), resulting in a relative increase of 20, 8 and 4% for each additional 10 pl per m(2). Overall, the crop model had adequate performance, indicating a minimum recommended plant density of 20 pl per m(2), while sowing dates and maturity groups showed different yield level and pattern across sites in function of the local climate.

Keywords

Crop management; crop modelling; Glycine max L; late maturity group; potential yield

Published in

Journal of Agricultural Science
2020, Volume: 158, number: 10, article number: PII S0021859621000204
Publisher: CAMBRIDGE UNIV PRESS

    UKÄ Subject classification

    Agricultural Science

    Publication identifier

    DOI: https://doi.org/10.1017/S0021859621000204

    Permanent link to this page (URI)

    https://res.slu.se/id/publ/113715