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Review Papers | Agriculture and Technology | Brazil | Volume 9 Issue 4, April 2020
Near Infrared Hyperspectral Imaging Spectroscopy Applied to Investigation of Plant Leaves: A Brief Review
Vagner Sargentelli [2] | Jose Antonio Martins [2]
Abstract: World agricultural production is the focus of worldwide attention because increasing productivity is imperative today and in the near future. Increasing productivity not only requires soil management, use of pesticides or biological agents to obtain best vintages, but also the improved seed and grains quality and other intrinsic factors. Many technical advances were implemented in recent years in agriculture. The plant leaves study can be provide important information about nutrition, soil condition and integrated pest management. Near infrared hyperspectral imaging spectroscopy (NIR-HIS) combines spectroscopy and imaging, providing information about the chemical properties of a material and their spatial distribution and is a relatively new technique. It represents an advance of traditional Near Infrared (NIR) spectroscopy. NRI-HSI is a highly flexible form of analysis that can be applied to a wide range of analytical applications. Long a basic technology in remote sensing, NIR imaging has become popular as an economical tool for chemical analysis. NIR-HIS is used to analyze multiple constituents in a single scan and to identify a non-destructive or non-invasive analysis method. This paper aims to present a brief review of the principal aspects of the applicability of NIR-HIS in agriculture related to investigation of plant leaves in the last two decades.
Keywords: Hyperspectral chemical imaging, NIR spectral imaging, agriculture, plant leaves
Edition: Volume 9 Issue 4, April 2020,
Pages: 1055 - 1062
Similar Articles with Keyword 'agriculture'
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Research Paper, Agriculture and Technology, India, Volume 10 Issue 9, September 2021
Pages: 1471 - 1473Genetic Diversity Analysis for Yield and Yield Attributing Triats in Chickpea (Cicer arietinum L.)
Mekala Sai Aneesha | Gaibriyal. M. Lal
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Review Papers, Agriculture and Technology, India, Volume 11 Issue 5, May 2022
Pages: 1682 - 1688Artificial Intelligence in Agriculture
Shilpa Kaushal [3] | Shivam Kumar [3] | Sayed Tabrez [2]