Spatial Heterogeneity of Winter Wheat Yield and Its Determinants in the Yellow River Delta, China

Lin Chu,Gaohuan Liu,Chongfa Cai,Qingsheng Liu,Chong Huang

doi:10.3390/su12010135

Abstract

Understanding spatial differences of crop yields and quantitatively exploring the relationship between crop yields and influencing factors are of great significance in increasing regional crop yields, promoting sustainable development of regional agriculture and ensuring regional food security. This study investigates spatial heterogeneity of winter wheat yield and its determinants in the Yellow River Delta (YRD) region. The spatial pattern of winter wheat in 2015 was mapped through time series similarity analysis. Winter wheat yield was estimated by integrating phenological information into yield model, and cross-validation was performed using actual yield data. The geographical detector method was used to analyze determinants influencing winter wheat yield. This study concluded that the overall classification accuracy for winter wheat is 88.09%. The estimated yield agreed with actual yield, with R2 value of 0.74 and root mean square error (RMSE) of 1.02 t ha−1. Cumulative temperature, soil salinity and their interactions were key determinants affecting winter wheat yield. Several measures are recommended to ensure sustainable crop production in the YRD region, including improving irrigation and drainage systems to reduce soil salinity, selecting salt-tolerant winter wheat varieties, and improving agronomy techniques to extend effective cumulative temperature.

Highlights

Agricultural production is a critical issue related to food security guarantee, regional economic development and social stability for local government [1,2,3]
Identifying spatial heterogeneity of crop yields, determining the influencing factors and quantifying theirs effects on crop yield are of great significance for improving crop yield and achieving sustainable development of agriculture
The Sentinel-2 satellite with 10 m spatial resolution and 5-d temporal resolution will be a good solution for mixed pixel at regional scale in our future research, which satellite launched in June, 2015

Summary

Introduction

Agricultural production is a critical issue related to food security guarantee, regional economic development and social stability for local government [1,2,3]. Due to limited cultivated land resources and continued population growth, global agricultural production faces enormous challenges. Owing to continuously growing population from seven billion in 2010 to nine billion in 2050 and limited land resources, a global food gap will appear [5]. Affected by internal and external factors, the crop growth and its ultimate yield usually involve complex procedures, which have a significant spatial heterogeneity [6,7,8,9,10]. Identifying spatial heterogeneity of crop yields, determining the influencing factors and quantifying theirs effects on crop yield are of great significance for improving crop yield and achieving sustainable development of agriculture

Objectives

Methods

Results

Discussion

Conclusion