Black Sigatoka is one of the most severe banana (Musa spp.) diseases worldwide, but no methods for the rapid early detection of this disease have been reported. This paper assesses the use of hyperspectral images for the development of a partial‐least‐squares penalized‐logistic‐regression (PLS–PLR) model and a hyperspectral biplot (HS biplot) as a visual tool for detecting the early stages of black Sigatoka disease.

中文翻译：

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使用高光谱图像早期检测香蕉叶中的黑色 Sigatoka

Black Sigatoka 是世界范围内最严重的香蕉 ( Musa spp.) 病害之一，但尚无快速及早发现该病害的方法的报道。本文评估了使用高光谱图像开发偏最小二乘惩罚逻辑回归 (PLS-PLR) 模型和高光谱双图 (HS 双图) 作为检测黑色 Sigatoka 病早期阶段的视觉工具.