Optimizing plant density and canopy structure to improve light use efficiency and cotton productivity: Two years of field evidence from two locations
Recently, the research team led by Dr. Wang Zhanbiao from the Cotton Research Institute of the Chinese Academy of Agricultural Sciences has revealed the effects of different planting densities on leaf area index, light interception, light use efficiency, cotton nutrient uptake, and seed cotton yield based on multi-year and multi-site field experiments. They have also analyzed the interactive mechanisms among these factors, which is of great significance for improving the utilization and yield of cotton resources in the Yellow River Basin. The research outcomes, titled "Optimizing plant density and canopy structure to improve light use efficiency and cotton productivity: Two years of field evidence from two locations," have been published in the internationally renowned journal Industrial Crops & Products (Top Tier journal in the Agricultural and Forestry Sciences category, IF=5.6) of the Chinese Academy of Sciences.
Optimizing the efficiency and effectiveness of light utilization is crucial for increasing cotton ( Gossypium hirsutum L. ) yields. However, how to increase light use efficiency and yield by improving canopy structure has not been fully verified and quantified through field trials, especially at different test sites. To explore this issue in greater depth, split-plot field experiments were conducted from 2019 to 2021 in Dongping and Jinxiang counties, Shandong, China. The effects of different planting densities and cotton varieties on the leaf area index (LAI), PAR interception rate (In), photosynthetically active radiation-use efficiency (PARUE), plant nutrient uptake, and seed cotton yield in a cropping system in which cotton was planted directly after garlic ( Allium sativum L. ) harvest were studied. The results revealed that increasing the planting density from the lowest value of 6.8×104 plant·ha−1 to 11.3×104 plant·ha−1 resulted in increases of 4.4–14.7 % in the cotton LAI, 2.5–12.4 % in the net photosynthetic rate (Pn), 5.0–6.8 % in the PAR interception rate, 16.0–53.2 % in the PARUE, and 5.2–13.4 % in the seed cotton yield. Notably, compared with those of Demian 15, the Lumian 532 variety presented greater LAI, Pn, PAR interception rate, PARUE, nutrient uptake, and seed cotton yield at D11.25 in the 2020 experiment in Jinxiang County. Specifically, on D11.25, Lumian 532 had the highest seed cotton yield, reaching 3939.0 kg·ha-¹. The LAI had a direct positive effect on nutrient uptake in cotton, with a value of 0.8. In addition, according to the Mantel test ( p < 0.05), the primary driving factor influencing seed cotton yield was the Pn. This factor was significantly and positively correlated with the PAR interception rate and seed cotton yield ( p < 0.01). Additionally, the PARUE was most significantly influenced by planting density (R=0.82, p < 0.01), with an increase of 2.0×10−4 g·MJ-¹ for each additional planting density. In conclusion, increasing the planting density of direct seeded short-season cotton plants after garlic harvesting can increase cotton light interception and utilization efficiency and improve plant nutrient uptake. This increase can result in increased seed cotton yield. Ultimately, the Lumian 532 variety performed optimally at D11.25. These results are essential for improving and managing cropping systems involving the planting of cotton in the Yellow River Basin of China and similar regions.
The research in this paper was financially supported by the "Tianshan Talents" Training Program (2023TSYCCX0020), the Tingzhou Science and Technology Innovation Team (2023CT09), and the China Postdoctoral Science Foundation (2024T171024). the Key Research and Development Plan of Shandong Province (Seed-Industrialized Development Program in Shandong Province) Cultivation of the new varieties of multi-resistance high quality early-maturing cotton (2023LZGC007), and the Earmarked Fund for Modern Agro-industry Technology Research System in Shandong Province (SDAIT-03-11).