Redirigiendo al acceso original de articulo en 22 segundos...
Inicio  /  Agronomy  /  Vol: 14 Par: 3 (2024)  /  Artículo
ARTÍCULO
TITULO

Field-Deployed Spectroscopy from 350 to 2500 nm: A Promising Technique for Early Identification of Powdery Mildew Disease (Erysiphe necator) in Vineyards

Sergio Vélez    
Enrique Barajas    
José Antonio Rubio    
Dimas Pereira-Obaya and José Ramón Rodríguez-Pérez    

Resumen

This study explores spectroscopy in the 350 to 2500 nm range for detecting powdery mildew (Erysiphe necator) in grapevine leaves, crucial for precision agriculture and sustainable vineyard management. In a controlled experimental vineyard setting, the spectral reflectance on leaves with varying infestation levels was measured using a FieldSpec 4 spectroradiometer during July and September. A detailed assessment was conducted following the guidelines recommended by the European and Mediterranean Plant Protection Organization (EPPO) to quantify the level of infestation; categorising leaves into five distinct grades based on the percentage of leaf surface area affected. Subsequently, spectral data were collected using a contact probe with a tungsten halogen bulb connected to the spectroradiometer, taking three measurements across different areas of each leaf. Partial Least Squares Regression (PLSR) analysis yielded coefficients of determination R2 = 0.74 and 0.71, and Root Mean Square Errors (RMSEs) of 12.1% and 12.9% for calibration and validation datasets, indicating high accuracy for early disease detection. Significant spectral differences were noted between healthy and infected leaves, especially around 450 nm and 700 nm for visible light, and 1050 nm, 1425 nm, 1650 nm, and 2250 nm for the near-infrared spectrum, likely due to tissue damage, chlorophyll degradation and water loss. Finally, the Powdery Mildew Vegetation Index (PMVI) was introduced, calculated as PMVI = (R755 - R675)/(R755 + R675), where R755 and R675 are the reflectances at 755 nm (NIR) and 675 nm (red), effectively estimating disease severity (R2 = 0.7). The study demonstrates that spectroscopy, combined with PMVI, provides a reliable, non-invasive method for managing powdery mildew and promoting healthier vineyards through precision agriculture practices.

 Artículos similares

       
 
Liyuan Zhang, Xiaoying Song, Yaxiao Niu, Huihui Zhang, Aichen Wang, Yaohui Zhu, Xingye Zhu, Liping Chen and Qingzhen Zhu    
As prior information for precise nitrogen fertilization management, plant nitrogen content (PNC), which is obtained timely and accurately through a low-cost method, is of great significance for national grain security and sustainable social development. ... ver más
Revista: Agriculture

 
Zhongyu Yang, Zirui Yu, Xiaoyun Wang, Wugeng Yan, Shijie Sun, Meichen Feng, Jingjing Sun, Pengyan Su, Xinkai Sun, Zhigang Wang, Chenbo Yang, Chao Wang, Yu Zhao, Lujie Xiao, Xiaoyan Song, Meijun Zhang and Wude Yang    
Aboveground biomass (AGB) is a key parameter reflecting crop growth which plays a vital role in agricultural management and ecosystem assessment. Real-time and non-destructive biomass monitoring is essential for accurate field management and crop yield p... ver más
Revista: Agronomy

 
Yuanyuan Shao, Shengheng Ji, Guantao Xuan, Yanyun Ren, Wenjie Feng, Huijie Jia, Qiuyun Wang and Shuguo He    
The objective is to develop a portable device capable of promptly identifying root rot in the field. This study employs hyperspectral imaging technology to detect root rot by analyzing spectral variations in chili pepper leaves during times of health, in... ver más
Revista: Agronomy

 
Enze Song, Guangcheng Shao, Xueying Zhu, Wei Zhang, Yan Dai and Jia Lu    
Plant height and biomass are important indicators of rice yield. Here we combined measured plant physiological traits with a crop growth model driven by unmanned aerial vehicle spectral data to quantify the changes in rice plant height and biomass under ... ver más
Revista: Agronomy

 
Haixia Jin, Jingjing Peng, Rutian Bi, Huiwen Tian, Hongfen Zhu and Haoxi Ding    
Mapping soil organic carbon (SOC) accurately is essential for sustainable soil resource management. Hyperspectral data, a vital tool for SOC mapping, is obtained through both laboratory and satellite-based sources. While laboratory data is limited to sam... ver más
Revista: Agronomy