Effects of fallow tillage on winter wheat yield and predictions under different precipitation types

PeerJ

article

Yu Feng¹  Wen Lin¹  Shaobo Yu¹  Aixia Ren¹  Qiang Wang¹  Hafeez Noor¹  Jianfu Xue¹  Zhenping Yang¹  Min Sun¹  Zhiqiang Gao¹ 

[1] Shanxi Agricultural University;State Key Laboratory of Sustainable Dryland Agriculture ,(In preparation), Shanxi Agricultural University

关键词: Precipitation types;    Random Forest;    Tillage;    Winter wheat;    Yield prediction;   

DOI  :  10.7717/peerj.12602

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

In northern China, precipitation that is primarily concentrated during the fallow period is insufficient for the growth stage, creates a moisture shortage, and leads to low, unstable yields. Yield prediction in the early growth stages significantly informs field management decisions for winter wheat (Triticum aestivum L.). A 10-year field experiment carried out in the Loess Plateau area tested how three tillage practices (deep ploughing (DP), subsoiling (SS), and no tillage (NT)) influenced cultivation and yield across different fallow periods. The experiment used the random forest (RF) algorithm to construct a prediction model of yields and yield components. Our results revealed that tillage during the fallow period was more effective than NT in improving yield in dryland wheat. Under drought condition, DP during the fallow period achieved a higher yield than SS, especially in drought years; DP was 16% higher than SS. RF was deemed fit for yield prediction across different precipitation years. An RF model was developed using meteorological factors for fixed variables and soil water storage after tillage during a fallow period for a control variable. Small error values existed in the prediction yield, spike number, and grains number per spike. Additionally, the relative error of crop yield under fallow tillage (5.24%) was smaller than that of NT (6.49%). The prediction error of relative meteorological yield was minimum and optimal, indicating that the model is suitable to explain the influence of meteorological factors on yield.

【 授权许可】

CC BY