Thermal imaging to assess the crop water status of melon plants under tropical semi-arid climate

Abstract

Abstract Deficit irrigation (DI) strategies and soil cover are highly effective to improve the the water productivity in semi-arid regions. However, the effective monitoring of plant water status under DI strategies becomes crucial. The main objective of this study was to evaluate the use of thermal images to estimate the water status of melon plants cultivated in soil with and without mulching under different irrigation regimes. The experience was carried out from October to December 2018. The study was carried out in a randomized block design, in a split plot arrangement. Plots were composed by soil cover (with and without mulching with plant material), and subplots by 5 irrigation regimes (120, 100, 80, 60 and 40% of crop evapotranspiration-ETc), with five replicates. The following variables were evaluated: canopy temperature (T canopy ), leaf water potential (Ψ leaf ), air temperature (T air ), soil moisture, crop yield and the thermal index (ΔT), this being defined as the difference between T canopy and T air . ΔT showed high correlations with crop yield and crop water consumption, evidencing that thermography is an efficient tool to identify the water status of melon plants and could be employed for a proper irrigation scheduling under the tropical semi-arid scenarios. Moreover, the use of thermal images also allowed the identification of beneficial effects of soil cover on leaf water status and crop yield, mainly under moderate DI. The obtained results also demonstrate that mulching is essential to increase melon yield and water productivity in tropical regions.

Plant phenotyping relevance

熱画像でメロンの水分状態を推定する方法を中心に評価し、熱指標と収量・水分状態の相関を検証しているため、植物フェノタイピング手法の実質的応用・検証に該当する。

Code and data availability

The preprint describes thermal imaging measurements of melon canopy temperature, leaf water potential, and yield, but contains no public data, image, or code availability statement. The only supplementary item is a Tables.pdf hosted on Research Square itself (not an allowed URL), and no author-deposited dataset, image,

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