Impact of Meteorological Factors on Rice Growth Stages and Yield
文献类型: 外文期刊
第一作者: Kulyakwave, Peter David
作者: Kulyakwave, Peter David;Xu, Shiwei;Wen, Yu;Kulyakwave, Peter David
作者机构:
关键词: Meteorological factors; natural and non-natural factors; rice; weather; yield
期刊名称:PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY ( 影响因子:0.6; 五年影响因子:0.6 )
ISSN: 0128-7680
年卷期: 2020 年 28 卷 3 期
页码:
收录情况: SCI
摘要: Weather variability poses threats to rural crop producers in Tanzania. This research aimed to find the impact of weather variation on the growth stage and yield of rice in Tanzania. The analyses were done using rice yield data and weather variables from 1981-2017. The approaches used were; decomposing rice yields into yield tendency and yield weather, stepwise integral regression for identification of significant yield model, and applied Fisher's meteorological regression and Chebyshev polynomial function to compute coefficients for weather factors. From the results, other than the non-natural factors, rainfall, maximum and minimum temperature, and sunshine significantly affect rice yield from sowing to harvest stage. The effect of rainfall, sunshine, maximum and minimum temperature coefficients on the rice yield differ by growth stage. An increase of 1 millimeter of rainfall at the sowing-seedling stage increased rice yield by 2.7 kg/ha. In the sowing-seedling stage, the temperature had a stronger positive influence on the rice yield as with every 1 degrees C in average maximum temperature increased the rice yield by 674.1 kg/ha. The minimum temperature coefficient had stronger influences in the vegetative, tillering-booting stages, thus, with 1 degrees C increase in average minimum temperature, the rice yield increased by 70.1 kg/ha and 420.7 kg/ha respectively. In the flowering-grain formation stage, the maximum temperature had a greater influence on rice yield, that is, as 1 degrees C increased, the rice yielded increased by 674.7 kg/ha. The sunshine duration had a higher influence on the harvesting stage. Increased 1-hour duration of sunshine increased rice yield by 495.95 kg /ha. Finally, a meteorological rice model, which could be used for rice yield forecasting in the region, was developed.
分类号:
- 相关文献
作者其他论文 更多>>
-
Climate and Socio-economic Factors Affecting the Adoption of Irrigation Practices for Improved Rice Yield in Mbeya Region, Tanzania
作者:Kulyakwave, Peter David;Xu, Shiwei;Wen, Yu;Kulyakwave, Peter David
关键词:adoption; irrigation; Mbeya-Tanzania; regression; weather; yield
-
Predicting maize yield in Northeast China by a hybrid approach combining biophysical modelling and machine learning
作者:Li, Jianzheng;Li, Ganqiong;Li, Denghua;Gao, Chao;Zhuang, Jiayu;Zhou, Han;Xu, Shiwei;Li, Jianzheng;Wang, Ligang;Li, Hu;Zhuang, Minghao;Hu, Zhengjiang;Wang, Enli
关键词:Maize; Yield prediction; APSIM; Random Forest
-
A Comprehensive Evaluation of Benefit of High-Standard Farmland Development in China
作者:Wang, Yu;Li, Ganqiong;Wang, Shengwei;Zhang, Yongen;Li, Denghua;Zhou, Han;Yu, Wen;Xu, Shiwei
关键词:high-standard farmland; benefits evaluation; China
-
Analytical bi-level multi-local-world complex network model on fresh agricultural products supply chain
作者:Liu, Yunqing;Xu, Shiwei;Liu, Jiajia;Zhuang, Jiayu;Xu, Shiwei;Liu, Jiajia;Zhuang, Jiayu;Liu, Yunqing;Xu, Shiwei;Liu, Jiajia;Zhuang, Jiayu
关键词:fresh agricultural products; supplying process; supply chain; complex network; multi-local-world model
-
Intelligent Decision Method of Multi-Agricultural Commodity Model Based on Machine Learning
作者:Zhuang, Jiayu;Xu, Shiwei;Li, Ganqiong;Zhong, Zhiping
关键词:Agricultural commodity model; machine learning; long short-term memory neural network
-
Wearable Crop Sensor Based on Nano-Graphene Oxide for Noninvasive Real-Time Monitoring of Plant Water
作者:Li, Denghua;Li, Ganqiong;Li, Jianzheng;Xu, Shiwei;Li, Denghua;Li, Ganqiong;Xu, Shiwei;Li, Denghua;Li, Jianzheng;Xu, Shiwei
关键词:graphene oxide; sensor; crop water; noninvasive; monitoring
-
Prediction of China's Grain Consumption from the Perspective of Sustainable Development-Based on GM(1,1) Model
作者:Zhang, Xiaoyun;Bao, Jie;Xu, Shiwei;Wang, Yu;Wang, Shengwei
关键词:food security; food consumption; sustainable; GM(1; 1) model; prediction