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Eslam Javadnia

محمدرضا مباشری، اسلام جوادنیا
ارائه شاخصی جدید جهت برآورد میزان کلروفیل گیاه با استفاده از ترکیب شاخصهای ابرطیفی 
Improvement of New Index for estimating Plant Chlorophyll Content, Using Integration of Hyperspectral Indices
Abstract


The plant chlorophyll content is a good index of photosynthetic activity, stress levels and nutritional status of plants; therefore, it has a special significance in precision agriculture. Spectral reflectance is a rapid and nondestructive method for estimating ‫plant chlorophyll content. A wide range of spectral indices have been used for chlorophyll content estimation. Most of these indices have been designed and tested only for one or at most a few plant species. Therefore, they cannot be efficient and useful for species with different structural features. The purpose of this study is to expand and incorporate indices to develop a new index which is largely independent of species and leaf structure. In this paper, five indices, i.e. NDVI, MSR, MCARI, TCARI and OSVAI were used. Each of these indices was evaluated alone as well. The results show that none of these indices alone can be a good estimator of chlorophyll content. Next, different combinations of the five indices were tested and their RMSE was calculated for test values. Finally, combining the two indices of MCARI and OSAVI led to generating a new index called MCAVI which showed a high accuracy in estimating chlorophyll. The RMSE and R2 of the new index were 21 and 0.87 respectively. Data used in this study were identified and validated based on LOPEX'93.

 

 

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