Development of a visible-NIR sensor for potato late blight detection

A&L Canada Labs Inc.正在开发一种带有多光谱相机的无人机， 确定营养（氮，磷，钾，镁）水平，检测疾病，并评估整体 特定作物的健康。多光谱相机将有6个辐射吸收带：一个在红色波段， 一个在蓝色波段，一个在绿色波段，三个在NIR区域。研究的目的是 确定哪些近红外波段最适合检测马铃薯田的晚疫病 位于爱德华王子岛。晚疫病是由于致病疫霉（Phytophthora infestans）引起的，并且使马铃薯叶和 块茎。已经开发了基于天气的晚疫病预报系统，因为它最常发生在凉爽， 气候潮湿，但该系统提供了一般性的预测，需要更精确的作物评估。一种方式 要实现这样的评估是通过使用基于非破坏性辐射的疾病的空中检测， 测量.在电磁光谱的可见光（400-700 nm）和NIR区域（700-1900 nm）中， 有许多光谱特征可能与马铃薯或番茄中的晚疫病有关。的 挑战是确定哪些光谱波段最适合检测马铃薯栽培品种中的致病疫霉 产于爱德华王子岛。对于每个波段，必须确定波段宽度和位置。

A&L Canada Labs Inc. is developing an UAV (Unmanned Aerial Vehicle) with a multi-spectral camera to determine nutrient (nitrogen, phosphorus, potassium, magnesium) levels, detect diseases, and to assess overall health of specific crops. The multi-spectral camera will have 6 radiation absorption bands: one in the red band, one in the blue band, one in the green band, and three in the NIR regions. The purpose of the study is to determine which near-infrared (NIR) bands are the most suitable to detect late blight disease in potato fields located in Prince Edward Island. Late blight is due to Phytophthora infestans, and devastates potato foliage and tuber. Late blight weather-based forecasting systems have been developed as it most commonly occurs in cool, wet climates, but the systems give general predictions and a more precise crop assessment is needed. One way to achieve such an assessment is through aerial detection of the diseases using non-destructive radiation based measurements. In the visible (400-700 nm) and NIR regions (700-1900 nm) of the electromagnetic spectrum, there are many spectral signatures that can be related to late blight diseases in potato or in tomato. The challenge is to identify which spectral bands are the best to detect P. infestans in the case of potato cultivars grown in Prince Edward Island. For each band, band width and locations will have to be determined.