scholarly journals Assessment of efficient crop planting calendar for cassava crops using the FAO-Aqua crop model

2021 ◽  
Vol 22 (1) ◽  
pp. 83-85
Author(s):  
SEUNG KYU LEE ◽  
TRUONG AN DANG
Keyword(s):  
2014 ◽  
Vol 53 (3) ◽  
pp. 598-613 ◽  
Author(s):  
Moussa Waongo ◽  
Patrick Laux ◽  
Seydou B. Traoré ◽  
Moussa Sanon ◽  
Harald Kunstmann

AbstractIn sub-Saharan Africa, with its high rainfall variability and limited irrigation options, the crop planting date is a crucial tactical decision for farmers and therefore a major concern in agricultural decision making. To support decision making in rainfed agriculture, a new approach has been developed to optimize crop planting date. The General Large-Area Model for Annual Crops (GLAM) has been used for the first time to simulate maize yields in West Africa. It is used in combination with fuzzy logic rules to give more flexibility in crop planting date computation when compared with binary logic methods. A genetic algorithm is applied to calibrate the crop model and to optimize the planting dates at the end. The process for optimizing planting dates results in an ensemble of optimized planting rules. This principle of ensemble members leads to a time window of optimized planting dates for a single year and thereby potentially increases the willingness of farmers to adopt this approach. The optimized planting date (OPD) approach is compared with two well-established methods in sub-Saharan Africa. The results suggest earlier planting dates across Burkina Faso, ranging from 10 to 20 days for the northern and central part and less than 10 days for the southern part. With respect to the potential yields, the OPD approach indicates that an average increase in maize potential yield of around 20% could be obtained in water-limited regions in Burkina Faso. The implementation of the presented approach in agricultural decision support is expected to have the potential to improve agricultural risk management in these regions dominated by rainfed agriculture and characterized by high rainfall variability.


Agrotek ◽  
2018 ◽  
Vol 2 (4) ◽  
Author(s):  
R. Milyaniza Sari ◽  
Supri Hadi

Intention of� this research� is to determine of� agriculture prime commodities of South Buru Regency. The observation was focussed to know potensial area to development agriculture harvesting/cattle.� This paper aims to examine the implementation of LQ approach uses wide of �agriculture harvesting/cattle population series data for five year period (2005-2009) from South Buru Regency as main source. The result of study showed that there was most of sub regency in South Buru regency have the same of prime commodities, and several sub regency have specific prime commodities. The number of prime commodities to the sub sector food crop agriculture are 6, prime commodities to sub sector vegetables and fruits planting are 18, prime commodities to the sub sector tree crop planting are 5� and prime commodities to sub sector husbandry /breeding are 5 commodities.


2013 ◽  
Vol 21 (12) ◽  
pp. 1515-1525 ◽  
Author(s):  
Ding-Hua OU ◽  
Jian-Guo XIA ◽  
Li ZHANG ◽  
Zhi ZHAO

2021 ◽  
Vol 300 ◽  
pp. 108313
Author(s):  
Alex C. Ruane ◽  
Meridel Phillips ◽  
Christoph Müller ◽  
Joshua Elliott ◽  
Jonas Jägermeyr ◽  
...  

2008 ◽  
Vol 28 (8) ◽  
pp. 3760-3768 ◽  
Author(s):  
Deng Zhenyong ◽  
Zhang Qiang ◽  
Pu Jinyong ◽  
Liu Dexiang ◽  
Guo Hui ◽  
...  

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 107
Author(s):  
Ge Song ◽  
Hongmei Zhang

Cultivated land use layout adjustment (CLULA) based on crop planting suitability is the refinement and deepening of land use transformation, which is of great significance for optimizing the allocation of cultivated land resources and ensuring food security. At present, people rarely consider the land suitability of crops when using cultivated land, resulting in an imbalance between crop distribution and resource conditions such as water, heat, and soil, and adversely affects the ecological security and utilization efficiency of cultivated land. To alleviate China’s grain planting structural imbalance and efficiency loss, this paper based on the planting suitability of main food crops (rice, soybean, and maize) to adjust and optimize the cultivated land use layout (CLUL) in the typical counties of the main grain production area in Northeast China, using the agent-based model for optimal land allocation (AgentLA) and GIS technology. Findings from the study show that: (1) The planting suitability of rice, soybean, and maize in the region is obviously different. Among them, the suitability level of soybean and maize is high, and that of rice is low. The current CLUL of the food crops needs to be further optimized and adjusted. (2) By optimizing the layout of rice, soybean, and maize, the planting suitability level of the food crops and the concentration level of the CLUL spatial pattern have been improved. (3) The plan for CLULA is formulated: The study area is divided into rice stable production area, maize-soybean rotation area, maize dominant area, and soybean dominant area, and town or village is identified as the implementation unit of CLULA. The plan for CLULA will be conducive to the concentrated farming of food crops according to the suitable natural conditions and management level. The research realized the optimization of spatial structure and cultivated land use patterns of different food crops integrating farming with protecting land. The significance of the study is that it provides a scientific basis and guidance for adjusting the regional planting structure and solving the problem of food structural imbalance.


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 ◽  
...  

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