Identifying key meteorological factors to yield variation of potato and the optimal planting date in the agro-pastoral ecotone in North China

2018 ◽  
Vol 256-257 ◽  
pp. 283-291 ◽  
Author(s):  
Jianzhao Tang ◽  
Jing Wang ◽  
Enli Wang ◽  
Qiang Yu ◽  
Hong Yin ◽  
...  
2021 ◽  
Vol 269 ◽  
pp. 108179
Author(s):  
Yang Li ◽  
Jing Wang ◽  
Jianzhao Tang ◽  
Enli Wang ◽  
Zhihua Pan ◽  
...  

2019 ◽  
Vol 111 (1) ◽  
pp. 343-353 ◽  
Author(s):  
Qin Fang ◽  
X. Y. Zhang ◽  
S. Y. Chen ◽  
L. W. Shao ◽  
H. Y. Sun ◽  
...  

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
Yunlong Zhang ◽  
Xuan Wang ◽  
Chunhui Li ◽  
Yanpeng Cai ◽  
Zhifeng Yang ◽  
...  

1976 ◽  
Vol 16 (79) ◽  
pp. 265 ◽  
Author(s):  
GA Constable ◽  
NV Harris ◽  
RE Paull

The effect of planting dates between September 30 and November 30 on the yield and some fibre properties of two cotton cultivars has been studied over three seasons. The yield of the commercial cultivar (Deltapine Smoothleaf) fell by an average of 20 kg ha-1 day-1 delay in planting after October 20, earlier planting dates having equal yields, producing a plateau effect. The yield of an early maturing cultivar (Short Sympodial) fell linearly by 11 kg ha-1 day-1 delay in planting. Planting dates after mid-October had an adverse effect on micronaire in the commercial cultivar, but lint length and strength were not affected. Thus maximum yield and micronaire for plantings after mid-October came from the early cultivar. Tolerance to low temperature is an important factor in cultivar earliness, and accounts for the performance of Short Sympodial in these experiments. The number of days from first flower to first frost was as reliable as growing degree days in explaining yield variation within a cultivar


2016 ◽  
Vol 216 ◽  
pp. 1-12 ◽  
Author(s):  
Baozhong Zhang ◽  
Di Xu ◽  
Yu Liu ◽  
Fusheng Li ◽  
Jiabing Cai ◽  
...  

2018 ◽  
Vol 18 (8) ◽  
pp. 5343-5358 ◽  
Author(s):  
Ziyue Chen ◽  
Xiaoming Xie ◽  
Jun Cai ◽  
Danlu Chen ◽  
Bingbo Gao ◽  
...  

Abstract. With frequent air pollution episodes in China, growing research emphasis has been put on quantifying meteorological influences on PM2.5 concentrations. However, these studies mainly focus on isolated cities, whilst meteorological influences on PM2.5 concentrations at the national scale have not yet been examined comprehensively. This research employs the CCM (convergent cross-mapping) method to understand the influence of individual meteorological factors on local PM2.5 concentrations in 188 monitoring cities across China. Results indicate that meteorological influences on PM2.5 concentrations have notable seasonal and regional variations. For the heavily polluted North China region, when PM2.5 concentrations are high, meteorological influences on PM2.5 concentrations are strong. The dominant meteorological influence for PM2.5 concentrations varies across locations and demonstrates regional similarities. For the most polluted winter, the dominant meteorological driver for local PM2.5 concentrations is mainly the wind within the North China region, whilst precipitation is the dominant meteorological influence for most coastal regions. At the national scale, the influence of temperature, humidity and wind on PM2.5 concentrations is much larger than that of other meteorological factors. Amongst eight factors, temperature exerts the strongest and most stable influence on national PM2.5 concentrations in all seasons. Due to notable temporal and spatial differences in meteorological influences on local PM2.5 concentrations, this research suggests pertinent environmental projects for air quality improvement should be designed accordingly for specific regions.


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