Phosphorus (P) plays a pivotal role in cotton by enhancing the reproductive growth and yield formation. Cotton cultivars vary greatly in response to P availability, especially under P-deficient conditions. So, we hypothesized that the increasing P level promotes the reproductive growth in cotton cultivars varying with P sensitivity. For this, two cotton cultivars, Lu-54 (sensitive to low P) and Yuzaomian-9110 (tolerant to low P), in response to three different P levels (P0: 0 (control), P1: 100, and P2: 200 kg P₂O₅ ha⁻¹) were studied at 39, 52, 69, 83, and 99 days after transplanting during 2017 and 2018. The results revealed that the seed cotton yield was improved in P1 and P2 treatments by 23.9%–34.5% and 30.8%–52.3% in Lu-54, and 16.6%–25.6% and 20.6%–38.5% in Yuzaomian-9110 during 2017 and 2018, respectively. The accumulation of reproductive organ biomass was 21.0%–52.1% and 28.5%–56.8% higher in Lu-54 and 24.2%–56.8% and 34.8%–69.1% higher in Yuzaomian-9110 in P1 and P2 over the control, respectively. During the fast accumulation period, the average accumulation of N, P, K, and biomass across the years in P2 were recorded as 0.75, 0.6, 0.5, and 120.5 kg ha⁻¹ d⁻¹ in Lu-54, while they were 0.65, 0.5, 0.8, and 98.5 kg ha⁻¹ d⁻¹ in Yuzaomian-9110. Overall, a longer period, in terms of reproductive biomass accumulation, was recorded for Yuzaomian-9110 compared with Lu-54 in 2017 and vice versa across the 2018 growing season. The results suggested that increasing P rate improved yield, reproductive organ biomass, as well as nutrient accumulation in both cotton cultivars. However, low P-sensitive cultivar (Lu-54) was more responsive to P application compared with low P-tolerant cultivar.

Keeping in view the yield losses instigated by heat stress in several crops, we carried out an experiment to explore the curative effect of exogenous applications of proline on the morpho-physiological, biochemical, and water-related attributes of okra genotypes under high-temperature stress (controlled conditions). Four contrasting genotypes C1, C2, C3, and C4 heat tolerant and heat sensitive genotypes were selected from a diverse panel of okra genotypes (n = 100) to examine plant responses to high-temperature stress and exogenous application of proline. Four-week-old seedlings were subjected to heat stress by gradually increasing the temperature of a growth chamber from 28/22 °C to 45/35 °C (day/night) and sprayed with an optimized proline concentration 2.5 mM. The experiment consisted of a factorial arrangement of treatments in a completely randomized design. The results showed that there were maximum increases in shoot length (32.7%), root length (58.9%), and shoot fresh (85.7%). The quantities of leaves per plant were increased by 52.9%, 123.6%, 82.5%, and 62.2% in C1, C2, C3, and C4 after proline application. On the other hand, only root fresh weight decreased in all genotypes after proline application by 23.1%, 20%, 266.7%, and 280.8% (C1, C2, C3, C4). A lower leaf temperature of 27.72 °C, minimum transpiration of 3.29 mmol m⁻² s⁻¹, maximum photosynthesis of 3.91 μmol m⁻² s⁻¹, and a maximum water use efficiency of 1.20 μmol CO₂ mmol H₂O were recorded in the genotypes C2, C1, C3, and C4, respectively. The highest enzymatic activity of superoxide dismutase, peroxidase and catalase were 14.88, 0.31, and 0.15 U mg-protein in C2, C1, and C3, respectively. Maximum leaf proline, glycinebetaine, total free amino acids, and chlorophyll content 3.46 mg g⁻¹, 4.02 mg g⁻¹, 3.46 mg g⁻¹, and 46.89 (in C2), respectively, due to foliar applications of proline. Another important finding was that heat tolerance in okra was highly linked highly linked to genotypes’ genetic potential, having more water use efficiency, enzymatic activities, and physio-biochemical attributes under the foliar applications of proline.

Timely and accurate estimation of Above-Ground-Biomass (AGB) in cotton is essential for precise production monitoring. The study was conducted in Shaya County, Aksu Region, Xinjiang, China. It employed an unmanned aerial vehicle (UAV) as a low-altitude monitoring platform to capture multispectral images of the cotton canopy. Subsequently, spectral features and textural features were extracted, and feature selection was conducted using Pearson’s correlation (P), Principal Component Analysis (PCA), Multivariate Stepwise Regression (MSR), and the ReliefF algorithm (RfF), combined with the machine learning algorithm to construct an estimation model of cotton AGB. The results indicate a high consistency between the mean (MEA) and the corresponding spectral bands in textural features with the AGB correlation. Moreover, spectral and textural feature fusion proved to be more stable than models utilizing single spectral features or textural features alone. Both the RfF algorithm and ANN model demonstrated optimization effects on features, and their combination effectively reduced the data redundancy while improving the model performance. The RfF-ANN-AGB model constructed based on the spectral and textural features fusion worked better, and using the features SIPI2, RESR, G_COR, and RE_DIS, exhibited the best performance, achieving a test sets R² of 0.86, RMSE of 0.23 kg·m⁻², MAE of 0.16 kg·m⁻², and nRMSE of 0.39. The findings offer a comprehensive modeling strategy for the precise and rapid estimation of cotton AGB.

Effect of various combinations of potting substrates was assessed to enhance vegetative growth, plant productivity and mineral composition of Caladium bicolor. Different substrates like leaf compost, farmyard manure, coconut compost, compost and perlite were used in different combinations with silt. Bulbs were sown in pots filled with different combinations of potting substrates, which were arranged under completely randomized design (CRD), with three replications, and totally there were ten treatment combinations. Application of different treatments of growing media either alone or in combinations led to considerable improvement in plant growth characteristics as compared to respective control. However, response differed according to the type of media manipulation. The highest stimulatory effect with maximum plant growth in terms of early sprouting, plant height, leaf area, chlorophyll contents, fresh and dry weights of tubers was observed in plants treated with silt+leaf compost+perlite combination; this combination significantly enhanced plant growth (30−150%) as compared to control. In case of NPK and protein contents, treatment combination of silt+leaf compost+coconut compost was greatly affected which lowered the pH, increased available organic matter and consequently maximized nutrient uptake by the plants. The best selection of conventional organic and inorganic potting media is the key to successful mass propagation of containerized plants. Generally, it could be concluded that application of potting mixes with silt, perlite, leaf composts and coco-based residues is a good cultural practice to improve the crop productivity and provide a better growing environment for plants.