Using a Portable Active Sensor to Monitor Growth Parameters and Predict Grain Yield of Winter Wheat.

Jiayi Zhang,Weixing Cao,Yan Zhu,Yan Liang,Xiaojun Liu,Xia Liu,Yongchao Tian,Qiang Cao

doi:10.3390/s19051108

Abstract

Rapid and effective acquisition of crop growth information is a crucial step of precision agriculture for making in-season management decisions. Active canopy sensor GreenSeeker (Trimble Navigation Limited, Sunnyvale, CA, USA) is a portable device commonly used for non-destructively obtaining crop growth information. This study intended to expand the applicability of GreenSeeker in monitoring growth status and predicting grain yield of winter wheat (Triticum aestivum L.). Four field experiments with multiple wheat cultivars and N treatments were conducted during 2013–2015 for obtaining canopy normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) synchronized with four agronomic parameters: leaf area index (LAI), leaf dry matter (LDM), leaf nitrogen concentration (LNC), and leaf nitrogen accumulation (LNA). Duration models based on NDVI and RVI were developed to monitor these parameters, which indicated that NDVI and RVI explained 80%, 68–70%, 10–12%, and 67–73% of the variability in LAI, LDM, LNC and LNA, respectively. According to the validation results, the relative root mean square error (RRMSE) were all <0.24 and the relative error (RE) were all <23%. Considering the variation among different wheat cultivars, the newly normalized vegetation indices rNDVI (NDVI vs. the NDVI for the highest N rate) and rRVI (RVI vs. the RVI for the highest N rate) were calculated to predict the relative grain yield (RY, the yield vs. the yield for the highest N rate). rNDVI and rRVI explained 77–85% of the variability in RY, the RRMSEs were both <0.13 and the REs were both <6.3%. The result demonstrates the feasibility of monitoring growth parameters and predicting grain yield of winter wheat with portable GreenSeeker sensor.

Highlights

Wheat (Triticum aestivum L.) is increasingly important in consequence of its role as a staple calories output, in particular for the Chinese population [1,2]
The analysis showed that Leaf area index (LAI) and leaf dry matter (LDM) were more variable during Feekes growth stages 4–7 (CV = 43.02% and 39.44%, respectively) than stages 8–10 (CV = 38.97% and 34.16%, respectively), and leaf nitrogen concentration (LNC) showed more variable during Feekes stages 8–10 (CV = 20.66%) than stages 4–7 (CV = 15.97%), while leaf nitrogen accumulation (LNA) during the two stages was similar (CV = 43.92% and 44.88%, respectively) (Table 2)
Our results showed that normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) are closely related to LDM

Summary

Introduction

Wheat (Triticum aestivum L.) is increasingly important in consequence of its role as a staple calories output, in particular for the Chinese population [1,2]. Due to a further growing population with a constant or even decreasing planting area, crop cultivation management aiming at high production and sustainability of natural resources is required. Leaf area index (LAI), dry matter, and nitrogen (N) are the main growth indicators for crop growth status monitoring and yield prediction [6,7,8]. Among various indirect methods for measuring plant N nutrient status, chlorophyll meter is most widely used [9]. Yuan et al [10] established prediction models of plant nitrogen accumulation and nitrogen nutrition index using chlorophyll meter values. In 2018, Padilla et al [9] concluded that chlorophyll meters are suitable for on-farm use to provide rapid assessment of crop N status. Canopy remote sensing provides new chance for monitoring crop growth and nutrition status

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Discussion

Conclusion