|
|
|
|
|
Siyao Yu, Haoran Bu, Xue Hu, Wancheng Dong and Lixin Zhang
In order to explore the feasibility of rapid non-destructive detection of cotton leaf chlorophyll content during the growth stage, this study utilized hyperspectral technology combined with a feature variable selection method to conduct quantitative dete...
ver más
|
|
|
|
|
|
|
|
|
Maylin Acosta, Isabel Rodríguez-Carretero, José Blasco, José Miguel de Paz and Ana Quiñones
Visible and near-infrared (Vis/NIR) hyperspectral imaging (HSI) was used for rapid and non-destructive determination of macro- and micronutrient contents in persimmon leaves. Hyperspectral images of 687 leaves were acquired in the 500?980 nm range over 6...
ver más
|
|
|
|
|
|
|
|
|
Xintao Yuan, Xiao Zhang, Nannan Zhang, Rui Ma, Daidi He, Hao Bao and Wujun Sun
Rapid and non-destructive estimation of the chlorophyll content in cotton leaves is of great significance for the real-time monitoring of cotton growth under verticillium wilt (VW) stress. The spectral reflectance of healthy and VW cotton leaves was dete...
ver más
|
|
|
|
|
|
|
|
|
Bolappa Gamage Kaushalya Madhavi, Anil Bhujel, Na Eun Kim and Hyeon Tae Kim
Non-destructive and destructive leaf area estimation are critical in plant physiological and ecological experiments. In modern agriculture, ubiquitous digital cameras and scanners are primarily replacing traditional leaf area measurements. Thus, measurin...
ver más
|
|
|
|
|
|
|
|
|
Muhammad Zulkarnain Abd Rahman, Md Afif Abu Bakar, Khamarrul Azahari Razak, Abd Wahid Rasib, Kasturi Devi Kanniah, Wan Hazli Wan Kadir, Hamdan Omar, Azahari Faidi, Abd Rahman Kassim and Zulkiflee Abd Latif
Recent methods for detailed and accurate biomass and carbon stock estimation of forests have been driven by advances in remote sensing technology. The conventional approach to biomass estimation heavily relies on the tree species and site-specific allome...
ver más
|
|
|
|