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Establishment of a Monitoring Model for the Cotton Leaf Area Index Based on the Canopy Reflectance Spectrum

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  • Xianglong Fan

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

  • Xin Lv

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

  • Pan Gao

    (College of Information Science and Technology, Shihezi University, Shihezi 832003, China)

  • Lifu Zhang

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China)

  • Ze Zhang

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

  • Qiang Zhang

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

  • Yiru Ma

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

  • Xiang Yi

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

  • Caixia Yin

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

  • Lulu Ma

    (Xinjiang Production and Construction Crops Oasis Eco-Agriculture Key Laboratory, Shihezi University College of Agriculture, Shihezi 832003, China)

Abstract

Cotton is the main economic crop in China and is important owing to its use as an industrial raw material and a cash crop. This experiment was conducted in the main cotton-producing area of Xinjiang, China. A hyperspectrometer was used to monitor the canopy spectral reflectance of cotton at different stages of growth. The results showed that the leaf area index (LAI) increased with the increase in the amount of nitrogen fertilizer added during the early full boll stage and decreased with the increase in nitrogen fertilization in the full and late boll stages. Insufficient or excessive fertilization led to a decrease in the LAI. The visible light band indicated that the canopy spectral reflectance decreased, and the amount of fertilizer increased in all the growth stages. The near-infrared band revealed that the canopy spectral reflectance increased with the amount of nitrogen applied during the bud stage, early boll stage, and the most vigorous period of boll growth. During the flowering period, the spectral reflectance followed the order N3 > N4 > N2 > N1 > N0. During the entire growth period of cotton, the values of the cotton LAI predicted using the ratio vegetation index (RVI) model were found to best fit the measured values. The LAI monitoring models of cotton in each growth stage were different. The TVI model is the best in the bud and early boll stages. The NDVI model is the best in the flowering stage, and the DVI model is the best in the full boll stage. This study provides a basis to accurately monitor the LAI in each growth period of cotton.

Suggested Citation

  • Xianglong Fan & Xin Lv & Pan Gao & Lifu Zhang & Ze Zhang & Qiang Zhang & Yiru Ma & Xiang Yi & Caixia Yin & Lulu Ma, 2022. "Establishment of a Monitoring Model for the Cotton Leaf Area Index Based on the Canopy Reflectance Spectrum," Land, MDPI, vol. 12(1), pages 1-19, December.
    • Handle: RePEc:gam:jlands:v:12:y:2022:i:1:p:78-:d:1015775
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    References listed on IDEAS

    as
    1. Gregoriy Kaplan & Offer Rozenstein, 2021. "Spaceborne Estimation of Leaf Area Index in Cotton, Tomato, and Wheat Using Sentinel-2," Land, MDPI, vol. 10(5), pages 1-13, May.
    2. Kaplan, Gregoriy & Fine, Lior & Lukyanov, Victor & Malachy, Nitzan & Tanny, Josef & Rozenstein, Offer, 2023. "Using Sentinel-1 and Sentinel-2 imagery for estimating cotton crop coefficient, height, and Leaf Area Index," Agricultural Water Management, Elsevier, vol. 276(C).
    3. Jing Peng & Fuqiang Yang & Li Dan & Xiba Tang, 2022. "Estimation of China’s Contribution to Global Greening over the Past Three Decades," Land, MDPI, vol. 11(3), pages 1-16, March.
    4. Azad Rasul & Sa’ad Ibrahim & Ajoke R. Onojeghuo & Heiko Balzter, 2020. "A Trend Analysis of Leaf Area Index and Land Surface Temperature and Their Relationship from Global to Local Scale," Land, MDPI, vol. 9(10), pages 1-17, October.
    5. Michael Fradley & Sarah Gyngell, 2022. "Landscapes of Mobility and Movement in North-West Arabia: A Remote Sensing Study of the Neom Impact Zone," Land, MDPI, vol. 11(11), pages 1-20, October.
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