Japanese Bindweed (Calystegia hederacea) Abundance and Response to Winter Wheat Seeding Rate and Nitrogen Fertilization in the North China Plain

2013 ◽  
Vol 27 (4) ◽  
pp. 768-777 ◽  
Author(s):  
Alexander Menegat ◽  
Ortrud Jäck ◽  
Jinwei Zhang ◽  
Kathrin Kleinknecht ◽  
Bettina U. Müller ◽  
...  

Japanese bindweed was found to be one of the most abundant and most difficult-to-control weed species during a 2-yr weed survey in more than 100 winter wheat fields in the North China Plain region. Multivariate data analysis showed that Japanese bindweed is most abundant at sites with comparative low nitrogen (N) fertilization intensities and low crop densities. To gain deeper insights into the biology of Japanese bindweed under various N fertilization intensities, winter wheat seeding rates, herbicide treatments, and their interactions, a 2-yr field experiment was performed. In nonfertilized plots, a herbicide efficacy (based on density reduction) of 22% for 2,4-D, and of 25% for tribenuron-methyl was found. The maximum herbicide efficacy in Nmin-fertilized plots (target N value based on expected crop yield minus soil mineral nitrogen content,) was 32% for 2,4-D and 34% for tribenuron-methyl. In plots fertilized according to the farmer's practices, a maximum herbicide efficacy of 72% for 2,4-D and of 64% for tribenuron-methyl could be observed. Furthermore, medium and high seeding rates improved the herbicide efficacy by at least 39% for tribenuron-methyl and 44% for 2,4-D compared to the low seeding rate. Winter wheat yield was not significantly affected by seeding rate itself, whereas at low and medium seeding rates, Nminfertilization was decreasing winter wheat yield significantly compared to the farmer's usual fertilization practice. At the highest seeding rate, Nminfertilization resulted in equal yields compared to the farmer's practices of fertilization.

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3094
Author(s):  
Jianhua Yang ◽  
Jianjun Wu ◽  
Leizhen Liu ◽  
Hongkui Zhou ◽  
Adu Gong ◽  
...  

Understanding the winter wheat yield responses to drought are the keys to minimizing drought-related winter wheat yield losses under climate change. The research goal of our study is to explore the response patterns of winter wheat yield to drought in the North China Plain (NCP) and then further to study which climatic factors drive the response patterns. For this purpose, winter wheat yield was simulated by the Environmental Policy Integrated Climate (EPIC) crop model. Drought was quantified by standardized precipitation evapotranspiration index (SPEI), and the contributions of the various climatic factors were evaluated using predictive discriminant analysis (PDA) method. The results showed that the responses of winter wheat yield to different time-scale droughts have obvious spatial differences from the north part to the south part in the NCP. Winter wheat yield is more sensitive to the medium (6–9 months) and long (9–12 months) time-scale droughts that occurred in the key growth periods (April and May). The different response patterns of winter wheat yield to the different time-scale droughts are mainly controlled by temperature and water balance (precipitation minus potential evapotranspiration) in winter in the NCP. Compared with the water balance, temperature plays a more important role in driving the response pattern characteristics. These findings can provide a reference on how to reduce drought influences on winter wheat yield in the NCP.


2017 ◽  
Vol 207 ◽  
pp. 30-41 ◽  
Author(s):  
Qin Fang ◽  
Xiying Zhang ◽  
Suying Chen ◽  
Liwei Shao ◽  
Hongyong Sun

2020 ◽  
Vol 12 (13) ◽  
pp. 5436
Author(s):  
Dongrui Han ◽  
Hongyan Cai ◽  
Xiaohuan Yang ◽  
Xinliang Xu

Yield gridded datasets are essential for agricultural land management, food security and harmonious human–land relationships. Many studies have developed yield spatialization models that are based on cropland areas. However, crop planting areas, phenological dates, and net primary production (NPP) have received minimal attention. This study proposes a novel method to simulate winter wheat yields in China from 2000 to 2015 using crop phenological datasets, phenological observations, and NPP. The results showed that the NPP in the growing season and statistical yield showed a significant positive correlation (R2 = 0.93, p < 0.01). The mean prediction error of the gridded yield dataset was 12.01%. The relative errors of the gridded yield dataset for approximately half of the samples were between −10% and 10%. Furthermore, the yield distribution was high in the east and low in the west. The high yield was primarily concentrated in the North China Plain, while low yield was observed in eastern Gansu, central Shanxi, southern Hebei, and eastern Sichuan. From 2000 to 2015, the yield mainly showed an increasing trend in the study area, with the average rate of 0.17 t ha−1 yr−1, especially in the North China Plain. This study suggests that NPP is a key indicator to evaluate the yield of winter wheat. Furthermore, this method can be used to generate gridded yield maps along with providing credible and fundamental data for climate change and sustainable agricultural development.


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