Using a Whole Crop Model

1985 ◽  
pp. 339-355 ◽  
Author(s):  
A. H. Weir ◽  
W. Day ◽  
T. G. Sastry
Keyword(s):  
2021 ◽  
Vol 300 ◽  
pp. 108313
Author(s):  
Alex C. Ruane ◽  
Meridel Phillips ◽  
Christoph Müller ◽  
Joshua Elliott ◽  
Jonas Jägermeyr ◽  
...  

2021 ◽  
Vol 146 ◽  
pp. 105975
Author(s):  
Andrea Parenti ◽  
Giovanni Cappelli ◽  
Walter Zegada-Lizarazu ◽  
Carlos Martín Sastre ◽  
Myrsini Christou ◽  
...  

Author(s):  
L. S. Sampaio ◽  
R. Battisti ◽  
M. A. Lana ◽  
K. J. Boote

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 m2), 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 m2, as expected, but with greater yield gain increments occurring at low plant density going from 10 to 20 pl per m2. In Santarém, 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 m2, resulting in a relative increase of 20, 8 and 4% for each additional 10 pl per m2. Overall, the crop model had adequate performance, indicating a minimum recommended plant density of 20 pl per m2, while sowing dates and maturity groups showed different yield level and pattern across sites in function of the local climate.


2021 ◽  
Vol 41 (4) ◽  
Author(s):  
Dominique Courault ◽  
Laure Hossard ◽  
Valérie Demarez ◽  
Hélène Dechatre ◽  
Kamran Irfan ◽  
...  

2018 ◽  
Vol 93 ◽  
pp. 73-81 ◽  
Author(s):  
Hélène Tribouillois ◽  
Julie Constantin ◽  
Eric Justes
Keyword(s):  

2014 ◽  
Vol 52 ◽  
pp. 121-135 ◽  
Author(s):  
B. Dumont ◽  
V. Leemans ◽  
M. Mansouri ◽  
B. Bodson ◽  
J.-P. Destain ◽  
...  

Author(s):  
Mohammad El Hajj ◽  
Nicolas Baghdadi ◽  
Bruno Cheviron ◽  
Gilles Belaud ◽  
Mehrez Zribi
Keyword(s):  

2018 ◽  
Vol 115 (47) ◽  
pp. 11935-11940 ◽  
Author(s):  
Ethan E. Butler ◽  
Nathaniel D. Mueller ◽  
Peter Huybers

Continuation of historical trends in crop yield are critical to meeting the demands of a growing and more affluent world population. Climate change may compromise our ability to meet these demands, but estimates vary widely, highlighting the importance of understanding historical interactions between yield and climate trends. The relationship between temperature and yield is nuanced, involving differential yield outcomes to warm (9−29 °C) and hot (>29 °C) temperatures and differing sensitivity across growth phases. Here, we use a crop model that resolves temperature responses according to magnitude and growth phase to show that US maize has benefited from weather shifts since 1981. Improvements are related to lengthening of the growing season and cooling of the hottest temperatures. Furthermore, current farmer cropping schedules are more beneficial in the climate of the last decade than they would have been in earlier decades, indicating statistically significant adaptation to a changing climate of 13 kg·ha−1· decade−1. All together, the better weather experienced by US maize accounts for 28% of the yield trends since 1981. Sustaining positive trends in yield depends on whether improvements in agricultural climate continue and the degree to which farmers adapt to future climates.


Sign in / Sign up

Export Citation Format

Share Document