Hyperspectral remote sensing for tobacco quality estimation, yield prediction, and stress detection: A review of applications and methods - Zhang, Mingzheng; Chen, Tian’en; Gu, Xiaohe; Chen, Dong; Wang, Cong; Wu, Wenbiao; Zhu, Qingzhen; Zhao, Chunjiang (Frontiers in Plant Science, 2023)
Tobacco is an important economic crop and the main raw material of cigarette products.Nowadays, with the increasing consumer demand for high-quality cigarettes, the requirements fortheir main raw materials are also varying. In general, tobacco quality is primarily determined by theexterior quality, inherent quality, chemical compositions, and physical properties. All these aspectsare formed during the growing season and are vulnerable to many environmental factors, suchas climate, geography, irrigation, fertilization, diseases and pests, etc. Therefore, there is a greatdemand for tobacco growth monitoring and near real-time quality evaluation. Herein, hyperspectralremote sensing (HRS) is increasingly being considered as a cost-effective alternative to traditionaldestructive field sampling methods and laboratory trials to determine various agronomic parametersof tobacco with the assistance of diverse hyperspectral vegetation indices and machine learningalgorithms. In light of this, we conduct a comprehensive review of the HRS applications in tobaccoproduction management. In this review, we briefly sketch the principles of HRS and commonlyused data acquisition system platforms. We detail the specific applications and methodologies fortobacco quality estimation, yield prediction, and stress detection. Finally, we discuss the majorchallenges and future opportunities for potential application prospects. We hope that this reviewcould provide interested researchers, practitioners, or readers with a basic understanding of currentHRS applications in tobacco production management, and give some guidelines for practical works.