This study aimed to evaluate the synergistic effects of zinc sulfate and Pseudomonas spp. in terms of mitigating drought stress in maize (Zea mays L.) by analyzing physiological, biochemical, and morphological responses under field conditions. A two-year (2018-2019) field experiment investigated two irrigation levels (optimal and moderate stress) and twelve treatment combinations of zinc sulfate application methods (without fertilizer, soil, foliar, and seed priming) with zinc-solubilizing bacteria (no bacteria, Pseudomonas fluorescens, and Pseudomonas aeruginosa). Drought stress significantly reduced chlorophyll content, increased oxidative damage, and impaired membrane stability, leading to a 42.4% increase in electrolyte leakage and a 10.9% reduction in leaf area index. However, the combined application of zinc sulfate and P. fluorescens, and P. aeruginosa mitigated these effects, with seed priming showing the most significant improvements. Specifically, seed priming with zinc sulfate and P. fluorescens increased catalase activity by 76% under non-stress conditions and 24% under drought stress. Principal component analysis revealed that treatments combining zinc sulfate and P. fluorescens, and P. aeruginosa were strongly associated with improved chlorophyll content, carotenoid content, and grain yield while also enhancing osmotic adjustment and antioxidant enzyme activity. These findings highlight the potential of the use of zinc sulfate and P. fluorescens as well as P. aeruginosa as sustainable strategies for enhancing maize drought tolerance, mainly through seed priming and soil application methods.

The structures and the physical and mechanical properties of Ferrocalamus strictus culms were differently affected by the environment in different habitats. Correlation analysis, random forest and cluster analysis were used to investigate the effects of environmental factors in five habitats on the structure and physical and mechanical properties of bamboo poles or stalks of F. strictus. The air-dry density of F. strictus stalks ranged from 0.66 to 0.91 g/cm3. Data showed that the average annual temperature, soil water content and available potassium content were important factors affecting air-dry density the bamboo stalks. The compressive strength of F. strictus stalks varied from 60.62 to 126.16 MPa and was positively correlated with mean annual sunshine hour. The modulus of rupture (MOR) ranged from 57.95 to 252.09 MPa and the soil available phosphorus content limited the MOR of F. strictus. The modulus of elasticity (MOE) ranged from 6.04 to 12.89 GPa. The outer hardness ranged from 66.75 to 94.83 HD (Shore D hardness) and the inner hardness ranged from 28.42 to 58.42 HD. Soil silicon content affected the structures and mechanical tissue strength of F. strictus culms. The principal component analysis indicated that the Yuanyang was the optimal habitat of F. strictus with highest composite scores of 14.07, the F. strictus of Yuanyang had the highest bending strength in the world, suggested that selecting a habitat site as breeding materials be reasonable. The regulation of hydrothermal conditions, i.e. soil pH, silicon (Si), phosphorus (P) and potassium (K) elements, was essential for the growth rate and physical and mechanical properties of F. strictus stalks. Further research will work on regulating the growth conditions of F. strictus at Yuanyang according to the information found from this paper and evaluating the impact of regulation.

Overwintering frost damage is a major challenge for the wine grape industry in northern China. This study investigates overwintering treatments to improve survival rates and mitigate frost damage in the wine grape production area of the northern foothills of the Tianshan Mountains. Seven overwintering treatments were tested: soil-covered striped cloth, striped cloth, sandwiched striped cloth, thickened striped cloth, double-layered striped cloth, heat-insulating striped cloth, and heat-insulating sandwich striped cloth. Temperature and humidity were continuously monitored during the overwintering period, both aboveground and at depths of 20 and 40 cm underground. By analyzing temperature trends, the duration of low temperatures, and temperature fluctuations, comprehensive overwintering indices were derived through principal component analysis to assess heat retention, moisture preservation, and the impact on grapevine survival. The results showed that the sandwiched striped cloth treatment provided the best insulation, with a 4.4 degrees C higher minimum daily temperature and a 356% increase in overwintering indices compared to striped cloth alone. The double-layer striped cloth treatment also improved safety, with a 130% increase in overwintering indices. Other treatments, including the soil-covered and the heat-insulating striped cloth, showed reduced performance. The sandwiched striped cloth and double-layer striped cloth treatments are recommended for northern China's wine grape regions, with further research needed to evaluate their economic viability.

Quantification and evaluation ofthe spatiotemporal changes in soil quality is importantto understand soil degradation mechanisms and restore the damaged land productivity. However, the effects of coal mining subsidence on the spatial and temporal characteristics of soil quality are not well understood. We investigated the contents of pH, organic matter (OM), total nitrogen (TN), nitrate nitrogen (NN), ammonia nitrogen (AN), total phosphorus (TP), available phosphorus (AP), available potassium (AK), total potassium (TK), cation exchange capacity (CEC), sucrase activity (SA), urease activity (UA), phosphatase activity (PA), catalase activity (CA) and dehydrogenase activity (DA) in the coal mining subsided area. The results showed that the contents of TN, NN, AN, TP, AK, TK, SA, UA, PA, CA and DA exhibited significant (P < 0.05) differences among the four seasons. Compared with the upper layer (0-20 cm), the lower layer (20-40 cm) contained higher contents of AN, NN, TN, TP and TK but lower contents of SA, UA, PA, CA and DA. The NN, AP, TP, AK and UA were identified as key indicators in the minimum dataset using principal component analysis. The seasonal changes of soil quality index (SQI) were in the following order: winter (0.707), spring (0.681), summer (0.616), and autumn (0.563). The spatial changes of SQI were highest for middle slope position 3 (0.508), followed by lower slope position 4 (0.507), top slope position 1 (0.446), upper slope position 2 (0.442), and bottom slope position 5 (0.437). Based on these spatiotemporal changes in soil quality, it was suggested that the application of multiple land use types may be a useful method for land reclamation and the interest of local farmers in the coal mining subsided area.

Droughts cause significant economic damage worldwide. Evaluating their impacts on crop yield and water resources can help mitigate these losses. Using single variables such as precipitation, temperature, the soil moisture condition index (SMCI) and the vegetation condition index (VCI) to estimate drought impacts does not provide sufficient information on these complex conditions. Therefore, this study uses station-based and remote-sensingbased data to develop new composite drought indexes (CDIs), including the principal component analysis drought index (PSDI) and the gradient boosting method drought index (GBMDI). The first dataset includes historical observations of the standardized precipitation index (SPI), standardized precipitation evapotranspiration index (SPEI), and the self-calibrated Palmer drought severity index (SC-PDSI) at the 1-, 3-, 6-, and 12month timescales. The second dataset consists of remote-sensing-based data including the VCI, SMCI, temperature condition index (TCI), and precipitation condition index (PCI). We validated the results of PSDI and GBMDI by comparing them with historical drought events, in-situ drought indices, and annual winter wheat crop yield data from 2003 to 2022 using a regression model. Our temporal analysis revealed extreme to severe drought events during1990s and 2010s. GBMDI typically aligned with actual drought events and exhibited stronger correlations with in-situ drought indices than PSDI. We observed that drought intensity in winter were more severe than in summer. GBMDI was the most effective method, followed by PSDI, for assessing drought impacts on winter wheat yields. Thus, the proposed integrated monitoring framework and indexes offered a valuable and innovative approach to addressing the complexities of agricultural drought, particularly in evaluating its effects.

Agriculture is considered the leading field around the world, which is also the backbone of India. Agriculture is in a flawed state because the temperature changes, along with their uncertainty, cause huge damage to the crops during the manufacturing process. So, the appropriate prediction of crop expansion plays a vital role in the management of crop growth. This prediction can enhance the federated industries to make their sustainability toward the occupation. Recently, the farmers have not selected suitable crops for their cultivation based on soil factors. This makes a negative impact on crop yield, and thus, the Indian farmers can suffer from severe losses besides the monetary front. Hence, the optimal crop recommendation model has to consider different parameters of the soil for forecasting the best crop for cultivation, which increases crop growth and crop production. Thus, this research work explores a new crop recommendation model for precision agriculture intending to promote crop yield and alleviate the loss to farmers. Initially, this research work gathers the standard data regarding the agricultural parameters of some areas. Then, the deep features using an autoencoder, and statistical features are gathered along with the Principal Component Analysis (PCA)-based features. Next, all three sets of features are fused and fed to the developed Adaptive Henry Gas Solubility Optimization (AHGSO) for selecting the optimal features. Finally, the chosen optimal features are fed to the recommendation stage, where a Gated Recurrent Unit with Ridge Classifier (GRU-RC) is suggested for getting the precise outcome regarding the recommended crop suitable to that agricultural parameter. Here, the optimal solutions are attained by tuning the parameters of GRU and ridge classifier with the same I-HGSO. At last, the results obtained from the hybrid method can be considered more efficient.

The literature shows that a circular economy can benefit some sectors such as the construction industry. This sector demands huge amounts of raw materials and produces waste when buildings and structures are demolished. This paper explores the possibility of manufacturing at industrial scale paving blocks using different types of construction and demolition wastes as aggregates, without modifying the commonly used industrial conditions. A total of four different recycled aggregates were used in this research. Both natural and recycled aggregates have been characterized. The dosages were optimized (three different formulations). Prefabricated tests have been carried out on the products manufactured in industrial plants and the evolution of mechanical properties over time has been analysed. The results obtained were analysed statistically by applying the principal component analysis (PCA) method. To ensure the security of the elements manufactured, the ionic leaching of the materials used as recycled aggregate and of the elements produced has been tested. The main implications of this research on the construction industry show that the majority of recycled aggregates used could replace 25% of the natural aggregate in manufactured precast concrete, that the properties of the aggregates should be taken into account in the different standards and that all paving blocks manufactured in this study can be considered environmentally safe (no risk of leaching) according to the Netherland Soil Quality Decree. Therefore, it is evident that it is possible to manufacture on an industrial scale paving blocks with mixed recycled aggregates, concrete and ceramic in nature, both with the fine and coarse fractions that meet the requirements of its reference standard UNE-EN 1338 and the Netherland Soil Quality Decree that evaluates environmental risks due to leaching.

Currently, little is known about the spatial variability of significant soil properties and their relationships to forest ecosystems of different vegetation grades. This work evaluates the variability of the properties of the upper layer of Cambisol taxa and their relationship to altitude and forest ecosystems of 2nd to 5th forest vegetation grades selected in the Western Carpathians using PCA and regression analysis. The content of clay, total carbon and total nitrogen, humus, energy, and ash in the soils varied between 5.43 and 11.53 %, 21-65 mg g-1, 1.9-4.7 mg g-1, 36-112 mg g-1, 438.4-5845.7 J g- 1 and 852.9-946.3 mg g-1, and C/N, pHH2O, and pHKCl values ranged between 11.2 and 16.7, 4.0-5.8 and 3.1-4.6. PCA showed that EAC in the 3rd oak-beech vegetation grade had significantly higher pH values and significantly lower energy content, ESC in the 4th beech vegetation grade had a significantly higher ash content and a significantly lower energy content, and DC in the 5th fir-beech vegetation grade had a significantly higher content of Ct, Nt, and humus. Linear regression revealed a strong negative correlation between the energy content and soil reaction (R2 for pHH2O = 0.48; R2 for pHKCl = 0.38) for all Cambisol taxa. Ct content and ash show a strong negative correlation (R2 = 0.78). The positive relationship between altitude and FVGs was found only for the soil Ct (R2 = 0.87), Nt (R2 = 0.81), and humus content (R2 = 0.87). A strong negative linear relationship between altitude and FVGs showed the ash content (R2 = 0.77). In turn, the oscillatory, polynomial course had a relationship between the clay content (R2 = 0.65) and energy (R2 = 0.75) to altitude and FVGs. Recognizing significant soil variables and better understanding their impact on the development of forest ecosystems is a prerequisite for distinguishing areas with the highest risk of their damage under conditions of various anthropogenic interventions and climate change. Therefore, this topic continues to require increased research efforts. For this reason, a better understanding of the relationships between soil properties and ecologically differentiated communities of forest ecosystems will allow us to identify areas with the highest risk of ecological changes that could lead to the degradation of European forests in the future.

Soybean is an important oilseed crop worldwide; however, it has a high sensitivity to temperature variation, particularly at the vegetative stage to the pod-filling stage. Temperature change affects physiochemical and genetic traits regulating the soybean agronomic yield. In this regard, the current study aimed to comparatively evaluate the effects of varying regimes of day and night temperatures (T1 = 20 degrees C/12 degrees C, T2 = 25 degrees C/17 degrees C, T3 = 30 degrees C/22 degrees C, T4 = 35 degrees C/27 degrees C, and T5 = 40 degrees C/32 degrees C) on physiological (chlorophyll, photosynthesis, stomatal conductance, transpiration, and membrane damage) biochemical (proline and antioxidant enzymes), genetic (GmDNJ1, GmDREB1G;1, GmHSF-34, GmPYL21, GmPIF4b, GmPIP1;6, GmGBP1, GmHsp90A2, GmTIP2;6, and GmEF8), and agronomic traits (pods per plant, seeds per plant, pod weight per plant, and seed yield per plant) of soybean cultivars (Swat-84 and NARC-1). The experiment was performed in soil plant atmosphere research (SPAR) units using two factorial arrangements with cultivars as one factor and temperature treatments as another factor. A significant increase in physiological, biochemical, and agronomic traits with increased gene expression was observed in both soybean cultivars at T4 (35 degrees C/27 degrees C) as compared to below and above regimes of temperatures. Additionally, it was established by correlation, principal component analysis (PCA), and heatmap analysis that the nature of soybean cultivars and the type of temperature treatments have a significant impact on the paired association of agronomic and biochemical traits, which in turn affects agronomic productivity. Furthermore, at corresponding temperature regimes, the expression of the genes matched the expression of physiochemical traits. The current study has demonstrated through extensive physiochemical, genetic, and biochemical analyses that the ideal day and night temperature for soybeans is T4 (35 degrees C/27 degrees C), with a small variation having a significant impact on productivity from the vegetative stage to the grain-filling stage.

The cryosphere in the Himalaya-Karakoram (H-K) is widespread, and its services significantly affect the SDGs implementation in the region, in particular related to the 'No poverty' (SDG 1), 'zero hunger' (SDG 2), 'good health and well-being' (SDG 3), 'work and economic' (SDG 8) and 'partnership for the goals' (SDG 17). We here established the networks to illustrate the complex relationship of cryosphere services with national SDG priorities in the countries of H-K, including Afghanistan, Pakistan, India, China, Nepal and Bhutan. The cryosphere services contributing to the national SDG priorities and the key targets were elucidated in line with the centralities of the network. It was found that 'freshwater', 'clean energy', 'runoff regulation', 'climate regulation', 'research and education' and 'infrastructure and engineering' are the services that play critical roles in H-K, and they were then applied to assess the impact of cryosphere services on the national SDG priorities. We subsequently identified a set of principal indicators in relation to the key targets of national SDG priorities, which has the explanation up to 85% of six entry points (SEPs) to advance SDGs of each country in H-K. In conjunction with the centrality of the key targets to be contributed by the overall cryosphere services in the network for each country, the dependency of SEPs on the cryosphere services can be established through principal indicators in association with the national SDG priorities in H-K countries.