Application of Internet of Things technology in winter wheat yield forecast

Lihong Song; Suhong Lv; Yuanbo Dang; Qiguo Duan; Yan Wang; Yaqian Qin; Lei Shi

doi:10.1117/12.2629108

22 April 2022 Application of Internet of Things technology in winter wheat yield forecast

Lihong Song, Suhong Lv, Yuanbo Dang, Qiguo Duan, Yan Wang, Yaqian Qin, Lei Shi

Proceedings Volume 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021); 121740N (2022) https://doi.org/10.1117/12.2629108
Event: International Conference on Internet of Things and Machine Learning (IoTML 2021), 2021, Shanghai, China

Abstract

In the case of frequent extreme weather, in order to improve the accuracy of winter wheat yield forecasts. Based on the data from the Internet of Things, this paper takes Henan Province as the research area and calculates the influence of extreme temperatures on the growth of winter wheat, and takes the sum of growth degree-day (SGDD) and Sum of Extreme Degrees (SEDD)as two major factors; Based on remote sensing technology, this paper calculates the growth area of winter wheat. And the normalized vegetation index (NDVI) of each period; finally use the above three factors, to establish two regression models for winter wheat yield forecast. The model constructed by the two influencing factors of SEDD shows that NDVI is a sensitive factor for yield prediction. The results show that both models in northeastern Henan Province have achieved good results. The model can provide methods for winter wheat production management and decisionmaking in Henan Province support.

Citation Download Citation

Lihong Song, Suhong Lv, Yuanbo Dang, Qiguo Duan, Yan Wang, Yaqian Qin, and Lei Shi "Application of Internet of Things technology in winter wheat yield forecast", Proc. SPIE 12174, International Conference on Internet of Things and Machine Learning (IoTML 2021), 121740N (22 April 2022); https://doi.org/10.1117/12.2629108

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KEYWORDS

Atmospheric modeling

Remote sensing

Temperature metrology

Vegetation

Internet

Meteorology

Environmental sensing

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