Asian Disaster Preparedness Center, Duty Station: ADPC-Bangladesh Office, Dhaka, Bangladesh.
Food Chem. 2013 Aug 15;139(1-4):689-94. doi: 10.1016/j.foodchem.2013.01.086. Epub 2013 Feb 9.
This study tries to quantify the effects of green leaf tea parameters that influence tea quality in Northeast India. The study is to identify the different parameters that have a significant influence on tea quality through the use of remote sensing. It investigates the methods for estimating tea quality based on remotely sensed Normalized Difference Vegetation Index (NDVI) data. Attention focused on high yielding TV clones (TV1, TV18, TV22, TV23, TV25 and TV26). NDVI was obtained from ASTER images. Statistical analysis shows that NDVI has a strong significant effect on the caffeine content followed by epicatechin (EC), epigallocatechin (EGC) and to some extent in other chemical parameters. Relationships therefore exist between quality parameters and remote sensing in particular for the TV clones. This leads to the conclusion that NDVI has a large potential to be used for monitoring tea quality of individual cultivars in the future.
本研究试图量化影响印度东北部绿茶品质的各种参数。通过遥感来确定对茶叶品质有显著影响的不同参数。研究基于遥感归一化植被指数(NDVI)数据来估计茶叶品质的方法。研究重点关注高产量的无性系(TV1、TV18、TV22、TV23、TV25 和 TV26)。从 ASTER 图像中获取 NDVI。统计分析表明,NDVI 对咖啡因含量有很强的显著影响,其次是表儿茶素(EC)、表没食子儿茶素(EGC),在一定程度上对其他化学参数也有影响。因此,质量参数与遥感之间存在关系,特别是对于 TV 克隆。这得出的结论是,NDVI 具有很大的潜力,可用于未来监测个别品种的茶叶品质。