Early detection of stress in strawberry plants using hyperspectral image analysis

Abstract

Strawberry plants produce one of the highest quantities of soft fruits in the UK. The plants are grown in fields and glass houses where the environment is hard to completely control. There are a variety of biotic and abiotic stresses that affect the plants' production rate, lifespan and the quality of the fruit. It is possible to mitigate these stresses, but first they must be detected as early as possible. Drought, or water deficit, is an environmental stress which impacts the plants' productivity. The stress can be monitored by looking for visible signs, but detection by a person can occur too late. Using technology could improve the detection before a person can see the signs. One such technology is hyperspectral imaging. Hyperspectral imaging has the potential to detect certain features in plants by examining their reflectance spectrum. In this work, a spectral range from visible to near-infrared will be used to record reflectance changes from plants during drought experiments. The data collected in this thesis comprises strawberry plants undergoing drought conditions. Initial inspection of the data suggests that a difference in reflectance may exist throughout this time period, but the data is noisy and ... (continues)

Plant phenotyping relevance

イチゴの乾燥ストレスという植物状態を、可視〜近赤外ハイパースペクトル画像の反射スペクトルから早期検出する手法が研究の中心であるため。

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