Dataset of laboratory chlorophyll content measurements and spectral indices based on multispectral imaging in Arabica coffee-Castillo variety.

Chlorophyll is a crucial plant pigment that plays a vital role in photosynthesis. Its presence and concentration in leaves can be used as an indicator of the physiological state of plants. A statistically significant correlation is thought to exist between laboratory-measured chlorophyll content and spectral indices obtained from multispectral imaging in Coffea arabica variety Castillo at leaf level. The data show that indices such as GARI, NDVI, and ARVI have a moderate to strong correlation with laboratory-measured chlorophyll content, especially when using the NIR and red bands. The data show correlations more significant than ρ=0.83 between IV (NDVI, GARI, IPVI, NLI, and GR-NDVI) and laboratory-estimated chlorophyll content. Therefore, it can be indicated that the indices are suitable indicators of chlorophyll content indirectly at the level of coffee leaves of Coffea arabica species. Furthermore, given the high correlations found, it can be stated that it is possible to establish regression models to estimate leaf LCC through vegetation indices.

叶绿素作为一种至关重要的植物色素，在光合作用中发挥着举足轻重的作用。其在叶片中的存在与浓度可作为衡量植物生理状态的指示器。据认为，在阿拉伯咖啡品种Castillo的叶片水平上，实验室测定的叶绿素含量与多光谱成像获取的光谱指数之间存在显著的相关性。数据表明，GARI、NDVI和ARVI等指数与实验室测定的叶绿素含量具有中等至强烈的关联性，尤其是在使用近红外和红光波段时。研究结果显示，IV（NDVI、GARI、IPVI、NLI和GR-NDVI）与实验室估算的叶绿素含量之间的相关性显著高于ρ=0.83。因此，可以推断这些指数是阿拉伯咖啡种叶片水平上叶绿素含量的间接适宜指标。此外，鉴于所发现的高度相关性，可以断言，建立回归模型以通过植被指数估算叶片叶绿素含量（LCC）是可行的。