Exploring the potential of chlorophyll a fluorescence for detecting phosphorus status in cotton leaves (Gossypium hirsutum L.) to optimize phosphorus management in cotton production

Abstract

Phosphorus (P) is an essential macronutrient for cotton (Gossypium hirsutum L.) growth, and plays a crucial role in yield formation. In this context, P deficiency reduces yield due to the limited leaf photosynthesis caused by the disruption of photosynthetic apparatus, and thus can be detected early via photosynthesis-related chlorophyll a fluorescence before visible leaf changes. In addition, the leaf subtending to cotton boll (LSCB) is the primary source of photosynthates, contributing to the boll biomass accumulation. Therefore, it is necessary to develop methods for early assessment of P status in the LSCB, facilitating rapid intervention in cotton production. To satisfy above demand, this study conducted a field experiment to explore the impact of different P application levels [0 (Deficient P), 100 (Critical P), and 200 (Excess P) kg P₂O₅ ha⁻¹] on cotton yield, boll weight accumulation and LSCB photosynthesis. Results showed that the increase of boll weight under P application is a significant factor contributing to yield improvement, and 15-25 days post anthesis is the key development period of cotton boll regulated by P. During this key period, P deficiency decreases the I and P steps of chlorophyll a fluorescence transients (indicating the damage to oxygen-evolving complex), and thus lead to the impaired photosystem II (PSII) and the reduction of electron transfer capacity. Then, the relationship between the leaf phosphorus concentration (LPC) and JIP-test parameters was fitted by Partial Least Squares Regression (PLSR) and showed good accuracy (R²=0.61 in calibration; RMSE=0.05 %, RRMSE=14.00 % in validation). Among the JIP-test parameters, the six ones (i.e. RC/CSₘ, FV/FO, ETO/CSₘ, FV/FM, DIO/RC and PIABS) show the highest correlation to LPC. This study demonstrated that the PLSR model generated using JIP-test parameters has the potential to detect P status in cotton during the key development period, and provided a new insight for optimizing P nutrient management in cotton production.

Plant phenotyping relevance

綿花葉のクロロフィル蛍光からリン栄養状態を推定する生理フェノタイピング手法を開発・検証しており、PLSRモデルの検証も中心的に行っている。

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