The number of cotton plants grown per unit of ground area has gained attention due to the high prices of inputs and lower production. Cotton yield per unit of area in Henan province has been stagnant in the last few years. The objectives of this study were to investigate cotton growth, yield, boll spatial distribution and biomass accumulation using different plant densities at cultivation and to find out the optimal plant density. A 2-year field experiment was conducted in a randomized complete block design under six plant densities (D1, 15,000; D2, 33,000; D3, 51,000; D4, 69,000; D5, 87,000 and D6, 105,000 ha⁻¹). Cotton grown at lower plant density produced taller plants and high number of leaves per plant while greater number of branches, fruiting nodes and high number of bolls per unit of ground area were produced under high plant density. Boll retention rate decreased as plant population increased and at nodes 1–8 the rate decreased slowly and then increased dramatically. The highest seed cotton yield (4546 kg ha⁻¹) and lint yield (1682 kg ha⁻¹) was produced by D5. The seed cotton and lint yield produced by D5 were 51–55%, 40–37%, 22–26%, 11–15%, 12–15%, 28–30%, 21–24%, 15–20%, 7–13% and 13–17% higher than D1, D2, D3, D4 and D6 during both years of experimentation, respectively. The increase in seed yield was due to higher biomass accumulation in reproductive organs under D5 plant density. The highest average (110.4 V_A kg ha⁻¹ d⁻¹) and maximum (126 V_M kg ha⁻¹ d⁻¹) rate of reproductive organs biomass was also accumulated by D5 as compared to other plant densities. The results suggest that D5 is the optimal plant density for high reproductive biomass accumulation and high yield for the area of Henan province.

Modification of the cotton canopy results in shade avoidance and competition for light, which shows that density and spatial arrangement of cotton have a great impact on light interception. This experiment was conducted in 2018 and 2019 in the experimental field at the Institute of Cotton Research of Chinese Academy of Agricultural Science in Anyang city, Henan Province, China. Six plant densities of cotton variety SCRC28 were used to assess spatial competition for light in cotton populations during the whole growing period. Light interception data were collected and analyzed according to the spatial grid method and the extension of Simpson’s 3/8 rule. The results showed that at the bottom of the canopy, greater light interception was observed at high densities than at low densities, while in the external part of the layer of the canopy in the horizontal direction, low light interception was recorded at low densities. Leaf area, aboveground biomass and plant height were obviously correlated with light interception, and the cotton population with a higher density (8.7 plants m⁻²) performed best at the light interception competition, and with the highest yield. The results will provide guidance on light management through the optimization of the structure of the canopy to provide more solar radiation and a significant basis by which to improve the management of light and canopy architecture.

The number of cotton plants grown per unit area has recently gained attention due to technology expense, high input, and seed cost. Yield consistency across a series of plant populations is an attractive cost-saving option. Field experiments were conducted to compare biomass accumulation, fiber quality, leaf area index, yield and yield components of cotton planted at various densities (D1, 1.5; D2, 3.3; D3, 5.1; D4, 6.9; D5, 8.7; and D6, 10.5 plants m⁻²). High planting density (D5) produced 21% and 28% more lint yield as compared to low planting density (D1) during both years, respectively. The highest seed cotton yield (4662 kg/ha) and lint yield (1763 kg/ha) were produced by high plant density (D5) while the further increase in the plant population (D6) decreased the yield. The increase in yield of D5 was due to more biomass accumulation in reproductive organs as compared to other treatments. The highest average (19.2 V_A gm m⁻² d⁻¹) and maximum (21.8 V_M gm m⁻² d⁻¹) rates of biomass were accumulated in reproductive structures. High boll load per leaf area and leaf area index were observed in high planting density as compared to low, while high dry matter partitioning was recorded in the lowest planting density as compared to other treatments. Plants with low density had 5% greater fiber length as compared to the highest plant density, while the fiber strength and micronaire value were 10% and 15% greater than the lowest plant density. Conclusively, plant density of 8.7 plants m⁻² is a promising option for enhanced yield, biomass, and uniform fiber quality of cotton.

Identifying the ideal plant nature and canopy structure is of great importance for improving photosynthetic production and the potential action of plants. To address this challenge, an investigation was accomplished in 2018 and 2019 at the Institute of Cotton Research (ICR) of the Chinese Academy of Agricultural Science (CAAS), Henan Province, China. Six cotton varieties with diverse maturities and plant canopy structures were used to evaluate the light interception (LI) in cotton, the leaf area index (LAI), the biomass, and the yield throughout the two years of study. The light spatial distribution in the plant canopy was evaluated using a geographic statistical method, following the increasing quantity of radiation intercepted, which was determined using the rules of Simpson. Compared to the cotton plants with a compact structure, varieties with both a loose and tower design captured a comparatively higher amount of light (average 31.3%) and achieved a higher LAI (average 32.4%), eventually achieving a high yield (average 10.1%). Furthermore, the polynomial correlation revealed a positive relationship between the biomass accumulation in the reproductive parts and canopy-accrued light interception (LI), signifying that light interception is critical for the yield development of cotton. Furthermore, when the leaf area index (LAI) was peaked, radiation interception and biomass reached the highest during the boll-forming stage. These findings will provide guidance on the light distribution in cotton cultivars with an ideal plant structure for light capture development, providing an important foundation for researchers to better manage light and canopies.

Taste determination in small molecules is critical in food chemistry but traditional experimental methods can be time-consuming. Consequently, computational techniques have emerged as valuable tools for this task. In this study, we explore taste prediction using various molecular feature representations and assess the performance of different machine learning algorithms on a dataset comprising 2601 molecules. The results reveal that GNN-based models outperform other approaches in taste prediction. Moreover, consensus models that combine diverse molecular representations demonstrate improved performance. Among these, the molecular fingerprints + GNN consensus model emerges as the top performer, highlighting the complementary strengths of GNNs and molecular fingerprints. These findings have significant implications for food chemistry research and related fields. By leveraging these computational approaches, taste prediction can be expedited, leading to advancements in understanding the relationship between molecular structure and taste perception in various food components and related compounds.

Optimizing irrigation strategies is crucial for sustaining cotton production in the face of growing water scarcity. The three-year experimental study (2020–2022) focused on the impact of varying irrigation amounts (320, 370, and 420 mm) and frequencies (4-, 8-, and 12-day intervals) on cotton growth, yield, yield components, and fiber quality in southern Xinjiang. Employing a completely randomized design with three replications, the results indicated higher irrigation amounts resulted in numerically 2.5–7.5% higher lint yields compared to those under medium and low irrigation amounts, notably significant in 2021. Boll density emerged as the primary yield component influencing yield loss due to irrigation amount, followed by seed cotton weight boll⁻¹. Increased boll density was associated with a greater total number of fruiting sites. Additionally, the increased seed cotton weight boll⁻¹ could be linked to an increased seed number boll⁻¹ and a decreased boll fraction at the lower fruiting branches with lower seed cotton weight boll⁻¹. Higher irrigation frequency improved lint yield by increasing boll density, though a significant effect was observed only in 2020. Increased irrigation amounts generally led to longer fiber lengths but lower micronaire values, while increased irrigation frequency resulted in longer, stronger fibers and reduced micronaire values. Furthermore, the highest yield stability was observed under the condition of high irrigation amount and high frequency. This study holds certain guiding significance for water resource management in cotton production in arid regions.