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The tomato, one of the world’s most extensively cultivated and consumed vegetable crops is negatively impacted by various pathogens. This study aimed to observe the differentially expressed proteins in tomato samples in plant–pathogen-biocontrol interactions. The fungal pathogen associated with wilted plants were isolated and identified based on its morphological and molecular characteristics. Fourteen strains of Pseudomonas fluorescens from agricultural soils were identified and described using biochemical assays, molecular analyses, and screening for antagonistic ability against the Fusarium wilt pathogen. Results demonstrated that the potential of P. fluorescens (TPf12) positively influenced the expression of antagonism against tomato wilt disease. A total of 14 proteins expressed differently were revealed in the 2D-PAGE-MS investigation. Proteins such as nucleoside diphosphate kinase, phenylalanine ammonia-lyase, protein kinase family protein, Ser/Thr protein kinase-like are unchanged in FOL pathogen interaction, but up-regulated in FOL + TPf12 treated roots, and lipid transfer-like protein, and phenylalanine ammonia-lyase were down-regulated in FOL infested roots and upregulated in FOL + TPf12 treated tomato roots. Phenylalanine ammonia-lyase protein expression is commonly found in TPf12 bioenriched roots, and FOL + TPf12 treated roots, indicating its role in response to the application of TPf12 in tomato. A GC–MS analysis was performed to detect the bioactive metabolites synthesized by TPf12. Molecular docking investigations were conducted using the maestro’s GLIDE docking module of the Schrodinger Software program. Among the secondary metabolites, Cyclohexanepropanoic acid, 2-oxo-, methyl ester (CAS), and 3-o-(4-o-Beta-D-Galactopyranosyl-Beta-D-Galactopyraosyl)-2-Acetylamino-2-Deoxy-D-Galactose were shown to be top-ranked with a least docking score against each differently expressed proteins. The profiled molecules expressed differently due to plant-pathogen-biocontrol interactions may be directly or incidentally involved in the wilt disease resistance of tomato plants.

Natural dyes are gaining a great deal of attention due to their eco-friendly and sustainable properties for advanced apparel applications. However, the reproducibility and accessibility of various colors using natural dyes remain challenging. In this study, plant-extracted fluorescent protein C-phycocyanin (CP) is used as a natural dye source and doped in polyvinyl alcohol (PVA) nanofibers via electrospinning for advanced apparel applications. The prepared nanofibers show a smooth and bead-free surface morphology. The FTIR results confirmed the formation of PVA nanofibers followed by a major peak at 3304 cm−1 due to the stretching of hydroxyl groups. Subsequently, CP-doping in PVA nanofibers is observed by the N–H deformation peaks at 1541 cm−1; C–N stretching vibrations at 1250 cm−1 and 1092 cm−1; and the C=O stretching vibrations of the carboxyl group at 1722 cm−1, respectively. Thus, CP-doped PVA nanofibers exhibit a good color strength (K/S) of 0.2 having a blue color tune and good color fastness properties. The mechanical strength of PVA nanofibers increased from 6 MPa to 18 MPa, due to crystalline characteristics endowed by the dope dyeing technique. Further, CP-doped PVA nanofibers exhibit homogeneous bright red fluorescence in individual nanofibers. Therefore, the proposed CP-doped PVA nanofibers can be used for flexible advanced apparel and biosensor applications.

Al-based fluoroperovskites compounds AlMF

This paper explains our first-principle computational investigation regarding the structural, optical, elastic, and electrical characteristics of gallium-based GaMF

This work displays the structural, electronic, elastic, optical, and magnetic properties in spin-polarized configurations for cubic fluoroperovskite ABF3 (A = Tl, B = Nb, V) compounds studied by density functional theory (DFT) by means of the Tran-Blaha-modified Becke-Johnson (TB-mBJ) approach. The ground state characteristics of these compounds, i.e., the lattice parameters a0, bulk modulus (B), and its pressure derivative B' are investigated. The structural properties depict that the selected compounds retain a cubic crystalline structure and have stable ground state energy. Electronic-band structures and DOS (density of states) in spin-polarized cases are studied which reports the semiconducting nature of both materials. The TDOS (total density of states) and PDOS (partial density of states) studies in both spin configurations show that the maximum contributions of states to the different bands is due to the B-site (p-states) atoms as well as F (p-states) atoms. Elastic properties including anisotropy factor (A), elastic constants, i.e.

The distribution of large ungulates is more often negatively impacted by the changing climate, especially global warming and species with limited distributional zones. While developing conservation action plans for the threatened species such as the Himalayan goral (Naemorhedus goral Hardwicke 1825; a mountain goat that mostly inhabits rocky cliffs), it is imperative to comprehend how future distributions might vary based on predicted climate change. In this work, MaxEnt modeling was employed to assess the habitat suitability of the target species under varying climate scenarios. Such studies have provided highly useful information but to date no such research work has been conducted that considers this endemic animal species of the Himalayas. A total of 81 species presence points, 19 bioclimatic and 3 topographic variables were employed in the species distribution modeling (SDM), and MaxEnt calibration and optimization were performed to select the best candidate model. For predicted climate scenarios, the future data is drawn from SSPs 245 and SSPs 585 of the 2050s and 2070s. Out of total 20 variables, annual precipitation, elevation, precipitation of driest month, slope aspect, minimum temperature of coldest month, slope, precipitation of warmest quarter, and temperature annual range (in order) were detected as the most influential drivers. A high accuracy value (AUC-ROC > 0.9) was observed for all the predicted scenarios. The habitat suitability of the targeted species might expand (about 3.7 to 13%) under all the future climate change scenarios. The same is evident according to local residents as species which are locally considered extinct in most of the area, might be shifting northwards along the elevation gradient away from human settlements. This study recommends additional research is conducted to prevent potential population collapses, and to identify other possible causes of local extinction events. Our findings will aid in formulating conservation plans for the Himalayan goral in a changing climate and serve as a basis for future monitoring of the species.

Numerous investigations on plant ethnomedicinal applications have been conducted; however, knowledge about the medicinal use of wild animals is still limited. This present study is the second on the medicinal and cultural meaning of avian and mammalian species used by the population in the surrounding area of the Ayubia National Park, KPK, Pakistan. Interviews and meetings were compiled from the participants (N = 182) of the study area. The relative frequency of citation, fidelity level, relative popularity level, and rank order priority indices were applied to analyze the information. Overall, 137 species of wild avian and mammalian species were documented. Of these, 18 avian and 14 mammalian species were utilized to treat different diseases. The present research showed noteworthy ethno-ornithological and ethno-mammalogical knowledge of local people and their connection with fauna, which might be useful in the sustainable utilization of the biological diversity of the Ayubia National Park, Khyber Pakhtunkhwa. Furthermore, in vivo and/or in vitro examination of the pharmacological activities of species with the highest fidelity level (FL%) as well as frequency of mention (FM) might be important for investigations on faunal-based new drugs.

In the present study, pure, Co, Gd, and Co/Gd di-doped ZnO nanoparticles were synthesized via the co-precipitation synthesis route. The prepared samples were characterized through different techniques such as the X-ray diffraction method (XRD), scanning electron microscopy (SEM), UV-Vis spectroscopy, photoluminescence (PL)spectroscopy, and an impedance analyzer and vibrating sample magnetometer (VSM). The XRD pattern shows ZnO’s wurtzite hexagonal crystal structure; moreover, the shifting of characteristic peaks toward the lower angle indicates the inclusion of Co and Co/Gd in the ZnO host lattice. SEM micrographs show various morphologies such as rods, the agglomeration of particles, and spherical nanoparticles. The UV-Vis spectroscopy reveals that the absorption increased in the visible region and there was a substantial redshift for the doped samples. The bandgap decreased from 3.34 to 3.18 eV for the doped samples. The PL spectra show near-edge and inter-band transitions; the origin of inter-band transitions is attributed to the defect states present within the bands. The dielectric constant is strongly frequency dependent and decreases with Co and Co/Gd doping, while the electrical conductivity increases. A VSM study indicates that pure ZnO is diamagnetic, while the Co and Co/Gd doped ZnO nanoparticles showed ferromagnetic behavior. Under UV-visible light irradiation, the Co/Gd-ZnO nanoparticles showed higher photocatalytic activity than the ZnO nanoparticles. The enhanced photocatalytic activity may be attributed to a decreased bandgap with doping.

Climate change (CC) is a global threat to the agricultural system. Changing climatic conditions are causing variations in temperature range, rainfall timing, humidity percentage, soil structure, and composition of gases in environment. All these factors have a great influence on the phenological events in plants’ life cycle. Alternation in phenological events, especially in crops, leads to either lower yield or crop failure. In light of respective statement, the present study is designed to evaluate the climatic impacts on two heat-resistant wheat varieties (Sialkot–2008 and Punjab–2018). During the study, impacts of CC on wheat phenology and annual yield were predicted considering six climatic factors: maximum temp, minimum temperature, precipitation, humidity, soil moisture content, and solar radiation using two quantitative approaches. First, a two-year field experimental plot was set up at five different sites of study—each plot a bisect of two sites. Phenological changes of both varieties were monitored with respect to climatic factors and changes were recorded in a scientific manner. Secondly, experimental results were compared with Global climate models (GMC) models with a baseline range of the past 40 years (1970–2010) and future fifty years (2019–2068) under Representative Concentration Pathway (RCP) 8.5 model analysis. Field experiment showed a (0.02) difference in maximum temperature, (0.04) in minimum temperature, (0.17) in humidity, and about (0.03) significant difference in soil moisture content during 2019–2021. Under these changing climatic parameters, a 0.21% difference was accounted in annual yield. Furthermore, the results were supported by GMC model analysis, which was analyzed by Decision Support System for Agrotechnology Transfer (DSSAT) model. Results depicted that non-heat-resistant wheat varieties could cause up to a 6~13% reduction in yield during future 50 years (2019–2068)) compared with the last 40 years (1970–2010). A larger decline in wheat grain number relative to grain weight is a key reducer of wheat yield, under future climate change circumstances. Using heat-tolerant wheat varieties will not only assist to overcome this plethora but also provide a potential increase of up to 7% to 10% in indigenous environment. On the other hand, it was concluded that cultivating these heat-resistant varieties that are also ripening late culminates into enhanced thermal time chucks during the grain-filling period; hence, wheat yield will increase by 8% to 12%. In changing climatic conditions and varieties, ‘Punjab–2018′ will be the better choice for peasants and farm-land owners to obtain a better yield of wheat to cope with the necessities of food on the domestic and national level.

of the current research was to use plant growth promoting rhizobacteria for sequestration and biotransformation of the toxic form of Cr and As into non-toxic form. Remediating these contaminants using microbes is a common technique and rhizo-microbiota not only relieves metal stress but also acts as biofertilizers. Role of plant growth-promoting rhizobacterial (PGPR) strains Acinetobacter beijerinckii (C5) and Raoultella planticola (C9) in counteracting chromium and arsenic stress in soybean seedlings was assessed. The isolated rhizobacteria were able to tolerate excessive quantities (up to 1200 ppm) of chromate and arsenate in liquid media. Beside their growth in heavy metal containing media, the strains were able to bio-transform chromate and arsenate to their least toxic form. They released significant quantities of stress related metabolites including phenols, flavonoids, proline, sugars and protein even in the presence of 1200 ppm of the heavy metals. They also released several plant hormones together with indole-3-acetic acid (IAA), salicylic acid (SA) and gibberellins. Another important feature of the isolates was their ability to solubilize phosphate and release siderophores and exposure to different levels of the selected heavy metals enhanced phosphate solubilization potential of both the isolates by up to 2-fold. Release of siderophore in A. beijerinckii C5 was enhanced by increasing heavy metals concentration in the media but in case of R. planticola C9 a decline was noted. When inoculated on soybean seedlings, the isolates modulated several metabolites of the hos plant enabling them to combat heavy metal toxicity at different levels. The PGPR strains boosted host's antioxidants production which minimized the oxidative damage by scavenging excessive ROS produced under stress. Control plants showed upregulation of stress response metabolites compared to PGPR application, whereas, IAA and SA were significantly higher in PGPR associated seedlings. In conclusion, PGPR alters the physiological and metabolic responses of soybean enabling it to cope better with chromate and arsenic toxicity and grow well under the stress.

Arid and semi-arid ecosystems are categorized as having degraded soils due to the limited availability of water and nutrients. The perennial shrubs in these regions have developed different ecological and physiological adaptations to cope with harsh conditions. The plant species vary in the chemical profile of their root exudates, which can induce variability in the microbial community in the rhizosphere. The present research has been conducted (i) to investigate the variation in composition, diversity, and structure of rhizosphere’s bacterial community of desert plants; (ii) to identify plant-specific effects on the rhizosphere microbial community structure; and (iii) to determine the influence of soil moisture on the rhizosphere’s microbial community and soil biological properties under stressful conditions. Ten desert plant species from the Cholistan desert were selected as test specimens. Bacterial communities from the rhizosphere of 10 plants of each species were explored. Soil samples were collected during monsoon (June–August) and dry months (March–May). Microbial community structure analyses were carried out through 16S rRNA sequencing by targeting V3 and V4 regions. Among tested plant species, the rhizosphere of Leptadenia pyrotechnica (S6 vs. S16), Aerva javanica (Burm. f.) Juss. ex Schult (S9 vs. S19), and Vachellia jacquemontii (Benth.) (S10 vs. S20) had greater microbial diversity in both seasons. Higher levels of microbial communities were found during monsoon season. Furthermore, Gammaproteobacteria were abundant in the rhizospheres of all studied plants during the monsoon season. In contrast, the rhizosphere was abundant with unidentified_Actinobacteria during the dry season. The rhizospheric soil was further analyzed for biological properties. The maximum microbial biomass carbon (165 mg kg–1) and microbial biomass nitrogen (6.7 mg kg–1) were found in the rhizosphere of Vachellia jacquemontii (Benth.) Benth during monsoon season. However, a minimum of microbial biomass carbon (119 mg kg–1) and microbial biomass nitrogen (4.2 mg kg–1) were found in the rhizosphere of Cleome pallida Kotschy during dry seasons. The diversified microbial community structure and biological properties enable desert plants to cope with adverse climate conditions.

Potatoes are a high-value crop with a shallow root system and high fertilizer requirements. The primary emphasis in potato production is minimizing nitrogen-leaching losses from the shallow root zone through fertigation. Therefore, a field experiment was conducted for two consecutive years, 2018–2019 2019–2020 to assess the effect of nitrogen and irrigation amount and frequency on tuber yield, water balance components and water productivity of potatoes under surface and subsurface drip irrigation. The experiment was laid out in a split-plot design with three nitrogen levels (187.5 kg N ha−1 (N1), 150 kg N ha−1 (N2) and 112.5 kg N ha−1 (N3)) in main plots and six irrigation levels in the subsurface (drip lines were laid at 20 cm depth) and one surface drip in subplots. Irrigation scheduling was based on 100% of cumulative pan evaporation at an alternate (I1) and two-day interval (I2), 80% of cumulative pan evaporation at an alternate (I3) and two-day interval (I4), 60% of cumulative pan evaporation at an alternate (I5) and two-day interval (I6) and 80% of cumulative pan evaporation at alternate days with surface drip (I7). Our results showed that potato transpiration was higher in N1 and N2 compared to N3, while soil evaporation was higher in N3 over N1 and N2. Irrigation regimes I5 and I6 had lower transpiration than I1, I2, I3 and I7, while I7 had more soil evaporation than I1, I2 and I3. Leaf area index (LAI), dry matter accumulation (DMA), root mass density (RMD) and tuber yield in N1 and N2 were at par but significantly higher than N3. The LAI and DMA were statistically at par in I1, I2 and I3 but significantly higher than recommended irrigation (I7). Tuber yield was statistically at par in I1, I2, I3 and I7 but I3 and I7 saved 20% irrigation water compared to I1 and I2. On the other hand, real water productivity (WPET) under N1 and N2 were comparable in I3 and I4 but significantly higher than recommended practice (I7) as pooled evapotranspiration (ET) and soil evaporation (E) in I7 were 19.5 and 20.6 mm higher, respectively, than in I3. Among interactive treatment combinations, N1I1, N1I2, N1I3, N1I7, N2I1, N2I2 and N2I3 recorded the highest tuber yields without any significant differences among them. Treatment N2I3 saved 20% nitrogen and irrigation water compared to all other combinations. Water productivity in N1 and N2 was comparable in I3 and I4 but significantly higher than recommended practice (I7).

By 2050, the population of the world is anticipated to increase from 7.7 billion to 9.7 billion people, and, and wheat is expected to continue to play a vital role in ensuring food security globally. It is the main diet for 40% of the world’s population and supplies food for more than 4.5 billion people in 94 countries contains 21% of the joules and 20% of the protein. The present investigations were carried out during rabi 2017–2018 and 2018–2019 to determine how optimal nutrient management (INM) practices enhance fertilizer usage efficiency, productivity, soil health, and viability in wheat (Variety DBW 71) through innovative nutritional sources and their modes of application methods. The treatments comprised of, viz., control, basal applications of recommended NPK (80:60:40)/NPK granules (200 kg/ha) + FYM (5 t ha−1) + bio-stimulant granules (62.5 kg/ha), +NPK bio-fertilizer (seed treatment), along with a top dressing of urea (20 kg/ha)/bio-stimulant (625 mL ha−1)/NPK Powder (1%) sprays (40/55/70 DAS), which had triplicated randomized block design (RBD) at the crop research farm of SVPUA&T, Meerut (U.P.). The results revealed that wheat grown with incorporation of FYM and bio-stimulant –L attained significantly better growth and higher dry matter accumulation across the stages. The crop contained 1.63% N, 0.31% P, 0.69% K in grain, and 0.57% N, 0.11% P and 1.34% K in straw. Such crops exhibited agronomic, physiological, and apparent recovery efficiency of NPK of the order of 3.2 kg kg−1 of nutrient applied, 14.0 kg kg−1 of nutrient uptake, and 0.23% against recommended NPK. Applications of FYM, NPK bio-fertilizer+ urea, and bio-stimulant + NPK sprays worked synergistically and increased grain yields by 29.8, 35.2, 50.3 and 41.1% over their respective controls. The results also indicated that soil organic carbon (0.47%), available NPK (227.0, 27.7, 172.1 kg/ha), dehydrogenase activity, and microbial population (bacteria, fungal and actinomycetes) in soil was also highest with the treatment. Finally, the wheat crop required an investment of Rs ha−1 131,453 and fetched a net reoccurrence of Rs. 96,154, with benefits of Rs. 3.72 over cost, respectively. Therefore, the study reveals that integrated nutrient management, viz., FYM 5 t ha−1 +NPK (12–32–16) -G @ 200 kg/ha + NPK bio-fertilizer (seed treatment) + urea @ 20 kg/ha, foliar application NPK (18−18−18) -P@ 1% and bio-stimulant –L 0.62 L ha−1 improved the better growth, productivity, soil health and profitability of wheat crops. Finally, to boost production, the region must emphasize the wheat crop’s part in integrated nutrition management with foliar application of bio-stimulants. Furthermore, these investigations must be reinvestigated at different sites with different agro-climatic conditions and texturally divergent soils.

Intensive agriculture has led to generation of a vast volume of agri-residue, prompting a reliance on conservation tillage techniques for prudent management. However, to ascertain the long-term impacts of these practices, the interrelation with the carbon fractions and the biological properties of the soil must be identified. Therefore, in a long-term experiment, five different treatments involving the incorporation of paddy straw as mulch or through disc harrow and farmer practice, including the partial burning of rice straw, were evaluated. After the harvesting of the wheat crop, soil samples collected from 3 different depths (0–15, 15–30 and 30–45 cm) were analyzed for various attributes critical to assessing soil health. Crop residue retention in both seasons (T4) improved carbon fractions, soil microflora viable cell counts and enzyme activities. The principal component analysis (PCA) revealed a positive interaction among the organic carbon, bacterial counts and soil enzyme activities. Thus, a positive impact of conservation tillage techniques involving a minimal disturbance was recorded as improvement in the soil properties, build-up of organic carbon, and wheat productivity in rice–wheat cropping systems.

Documentation the relative influence of ecological dynamics on species diversity patterns can help us better understand spatial distribution patterns and devise a systematically comprehensive base for carrying out environmental explorations. The current attempt aimed at exploring the distribution patterns, diversity and richness of wild grasses with respect to climatic dynamics in the Gujrat district of Punjab, Pakistan. For this purpose, we applied the randomized sample method and sampled a total of 90 sites across the Gujrat district between 2019 and 2021 to document data on wild grasses and related ecological conditions. After assessment of the significant value index of each grass species with ecological records, we evaluated the data by ordination and cluster analysis. A total of 57 wild grasses from 37 genera were documented from the Gujrat district. The leading genera were Brachiaria, Cenchrus and Setaria, each accounting for 7.02% of all documented species, followed by Aristida and Panicum, each representing 5.76% of the species. Dactyloctenium, Dichanthium, Eragrostis,Polypogon,Poa and Saccharum each accounted for 5.26% of the species, and Digitaria, Pennisetum, Eragrostis, Chrysopogon Poa and Setaria each accounted for 3.51% of the species. Other genera each had a single species. Among all grasses, 75.44% of the species were native and 24.56% species were exotic and introduced to the study area. The leading life forms were therophytes (56.14%), followed by hemicryptophytes (42.11%) and geophytes (1.75%). Microphylls, with a 54.39% share, dominated the leaf size spectra of the wild grasses flora in this research. Other frequent classes included nanophylls (21.05%), macrophylls (19.3%) and leptophylls (5.26%). Flowering phenology of wild grasses showed that mainly species at the flowering phase were recorded during the months of June to August (40.35%) and July to September (19.29%). By applying Ward’s agglomerative clustering method, we classified the ninety transects into four major groups. Ordination analysis showed that different ecological factors had significant (p ≤ 0.002) effects on vegetation relations. The present endeavor provides a basic way to understand the impacts of ecological variables on the structure, diversity, composition and associations of wild grasses, which are helpful to improve the scientific-informed conservation and management measures for the environmental reestablishment of degraded habitat in the studied region.

Al-based fluoroperovskites compounds AlMF3 (M = Cr, B) are investigated computationally and calculated their elastic, structural, optical, and electrical properties in this study utilising TB-MBJ potential (also GGA+U for AlCrF3) approximations, according to the Birch Murnaghan Equation curve and tolerance factor, these material are structurally cubic and stable. The IRelast algorithm is used to forecast elastic properties, and the outputs show that these compound are mechanically stable, anisotropic and ductile. AlBF3 has a metallic nature and overlapping states, while AlCrF3 have a narrow indirect band gap at (X-M) points of symmetry, with band gaps of 0.71 eV for AlCrF3 and zero eV for AlBF3. The partial and total density of states are being used to determine the influences of different basic states to the conduction and valence bands (TDOS & PDOS). Investigation of Optical properties shows that these compounds have low refractive index and high absorption coefficient, conductivity, reflective coefficient at high energy ranges. Owing to the indirect band gap, the applications of these compounds are deemed in conducting industries. Here we are using these compounds for first time and are examined using the computational method, which delivers a complete view into the different properties.

Land productivity and quality were negatively impacted by both unbalanced fertilization and water-stressed conditions, which has arisen as an important topic of research. In the semi-arid tropics, sugarcane is the main source of sugar and ethanol; however, no potash (K) dose is recommended for the deficient sites in the region, which are further responsible for lower recovery. As a result, in order to standardize the K dose for deficient sites, present experiments carried out during plant (2019–2020) and ratoon (2020–2021) seasons. The statistical design was a split-plot design with main plot treatments comprised of I1 (irrigated) and I2 (stressed) treatments followed by K1, K2, K3, and K4 plots fertilized with 0, 40, 80, and 120 kg K2O ha−1 in subplots. Germination was reported to be 13.7, 25.0 and 32.3% higher during plant and 6.2, 17.3 and 24.4% higher during ratoon season in K2, K3, and K4 plots, respectively. Tiller’s cane−1 was recorded to be significantly affected by potash levels at 241 days after planting (DAP) and 261 and 326 days after harvesting (DAH). Periodic chlorophyll content of the sugarcane leaves was reported not to be affected by irrigation treatments except at 355 DAP and 324 and 357 DAH, where respected values were reported to be 2.06% in the plant season and 1.55 and 2.54% higher in the ratoon season in I1 plots, respectively. During plant season purity and extraction after the 10th month, respective values were reported to be 1.5% lower and 4.03% higher under I1 plots, while only Brix (%) was reported as significant and 2.42% higher in I1 plots during plant season after the 12th month. The incidence of early shoot borer (Chilo infuscatellus) and stalk borer (Chilo auricilius) was reported to be significantly higher under stressed conditions (30.4 and 21.5% lower in I1 plots) during the plant season, while early shoot borer (Chilo infuscatellus), stalk borer (Chilo auricilius) and top (Scirpophaga excerptalis) incidences were significantly lower in I1 plots to the tune of 19.6, 22 and 9.73% as compared to the I2 plots during the ratoon season. The application of 80 kg K2O ha−1 resulted in significantly higher cane yield and decreased insect-pest occurrence. Even though 120 kg K2O ha−1 promoted different plant and ratoon sugarcane characteristics, they were all statistically equivalent. In I1 plots, benefits increased from K2 to K3 plots by 26.7% during plant and 155% during ratoon seasons but decreased from K3 to K4 plots by 21.0% during plant and 26.1% ratoon seasons. In I2 plots, however, benefits from K2 to K3 plots were reported to be 72.7% during plant and 76.5% during ratoon seasons, which was reduced to 10.5% during plant and 16.7% during ratoon seasons in K4 plots. Results of a two-year study on plant and ratoon canes revealed that 80 kg K2O ha−1 at deficient sites significantly improved the performance of both plant and ratoon canes yields, sugar yields, reduced the insect-pests’ incidence, and finally the benefits of the cane farmers under both irrigation regimes.

This paper explains our first-principle computational investigation regarding the structural, optical, elastic, and electrical characteristics of gallium-based GaMF3 (M = Be and Ge) perovskite-type (halide-perovskite) compounds. Our current computation is based on density functional theory (DFT) and is achieved with the help of the WIEN2k code. We used the Birch–Murnaghan equation for optimization; in both compounds, we found that both GaBeF3 and GaGeF3 compounds are structurally stable. For the computation of elastic characteristics, the IRelast package for calculating elastic constants (ECs) is utilized. These compounds are mechanically ductile, scratch-resistant, anisotropic, and mechanically stable, showing huge opposition to plastic strain. The modified Becke–Johnson (TB-mBJ) potential approximation method is used to calculate different physical characteristics and shows that GaGeF3 behaves as a metal, whereas the GaBeF3 compound is insulating in nature. The involvement of various electronic states in band structures is calculated using the theory of the density of states. The different optical properties of these compounds can be studied easily using their band gap energy. At high energy ranges, these substances demonstrate strong absorption. At low energies, the GaGeF3 compound is transparent, while the GaBeF3 compound is opaque to incoming photons. Investigation of the optical characteristics has led us to the conclusion that both GaGeF3 and GaBeF3 compounds can be used for high-frequency ultraviolet device applications. This computational work is considered to be the first time that we can study these compounds, which to our knowledge have not previously been experimentally validated.

Pteridophytes have been used by humans for millennia, but in comparison to flowering plants, the documentation of their traditional uses is still neglected; as a result, they must be highlighted and popularized. The present study was carried out from January 2019 to November 2021 to gather ecological and traditional use information on pteridophytes from local inhabitants of the Kashmir valley via semi-structured personal interviews and group discussions. We recorded 58 pteridophyte species belonging to 13 families. The distributions of the species among the families were unequal, with four families constituting more than half of the total species (Dryopteridaceae 26%, Woodsiaceae 17%, Aspleniaceae 14%, and Pteridaceae (14%). The highest numbers of species (45%) were found growing on the forest floor, followed by those growing in rock crevices (26%). This was supported further by a cluster analysis, which identified two primary clusters based on the species presence in different habitats. Half of the species (56%) were reported from altitudes below 2000m, followed by 19% from 2001–2500m, and 8% (e.g., Deparia allantodioides, Dryopteris xanthomelas, Asplenium viride) from 3001–3500m. Among the documented species (N = 58), only 28 species had a traditional usage (as medicine, vegetables, for oral hygiene, and for veterinary use). The aerial parts were most commonly used (64%) followed by the rachis (18%). The highest use value was observed for Diplazium maximum and the lowest for Asplenium fontanum. The findings of our study contribute baseline data to fill the existing knowledge gaps on ecological and traditional knowledge of pteridophytes in the Himalayas.

The current study was conducted to assess how optimal tillage water and nitrogen management system are adopted to reduce various field inputs, to improve water footprint (WF), nutrient use efficiency (NUE), rice productivity and profitability. The W1 (CS to a depth of 5 cm) achieved significantly higher total water footprint (TWFP) compared to all other irrigation strategies. When N1 (control) and N2 (80 kg N ha−1) was used, the highest TWFP was observed. The rice transplanted on wide raised beds (WBed-TPR) (0.71 kg m−3) yielded the greatest water productivity (WPIRRI), followed by reduced tillage transplanted rice (RT-TPR) and conventional tillage puddled transplanted rice (CT-TPR). The physiological NUE values ranged from 33.3 to 50.6 kg grain/kg N absorption, the values decreasing as the N doses rose. According to the findings, WBed-TPR and RT-TPR plots similarly drank more moisture from the deeper profile layer than CT-TPR practice. In plots of CT-TPR and WBed-TPR, the yield contributing characteristics of rice all increased, while grain yield increased by 16.8% and 10.6% over NBed-TPR technique, respectively. Finally, CT-TPR reported with maximum cultivation costs, followed by NBed-TPR and the lowest in RT-TPR plots, although WBed-TPR had the highest net profit, B: C ratio.

Climate change is viewed as the main obstacle to agricultural development in developing countries. The high dependence on agriculture and allied sectors makes many countries vulnerable to the climate change phenomenon. There is a gap in macro and micro-level understanding of climate change. Thoughtful farmers’ perceptions and impacts of climate change on farming are fundamental for developing various mitigation and adaptation strategies. Therefore, the main aim of the present study was to understand the pattern of climate variability, farmers’ perceptions about climate change, and farmers’ adaptation strategies based on their socio-cultural background in the villages of Goa, on the west coast of India. The results reveal that about 62% of the sampled farmers have experienced climate change in terms of meteorological indicators such as increased average temperature, decreased total rainfall, delayed onset of monsoon, and an increase in the length of the summer season. The temperature trend analysis (0.009 °C/year) validated farmers’ perceptions, while the perception of rainfall differed (−1.49 mm/year). Farmers are convinced that climate change has affected their farming (declining crop and livestock productivity, water depletion, and other related farm operations). They strive to adapt to climate change through crop diversification, an integrated crop-livestock system, contingency crop planning, and the adaptation of new crops and varieties. This study could be helpful for policymakers to establish a climate-resilient agriculture system by ensuring timely availability of farm inputs, accurate weather forecasting, and encouraging insurance products for crop and livestock enterprises, which will help farmers cope with the changing climate to enhance their income and economic wellbeing. Further, adaption of integrated farming, agroforestry, and indigenous technical knowledge is imperative to combat the ill effects of climate change.

Development of sustainable and efficient irrigation strategies is a priority for producers faced with water shortages. A promising management strategy for improving irrigation water use efficiency (IWUE) is deficit irrigation, which attempts to optimize yield and IWUE. Soil water use, crop yield and IWUE of tomato were evaluated for two consecutive years under two types of irrigation methods (subsurface and surface drip irrigation) and three irrigation strategies: 1.0 of full irrigation supply (T1), 0.8 of full irrigation supply (T2) and 0.6 of full irrigation supply (T3). The results showed that the highest yields were found in the plots irrigated by subsurface drip irrigation at T1 (94.1 ton/ha) and T2 (81.4 ton/ha). Conversely, the fully stressed treatment (T3) reduced the amount of irrigation water by 40%, but significantly decreased mean tomato yield by 25.6% and 26.1% under subsurface and surface drip irrigation, respectively, as compared to T1. The maximum IWUE tended to be higher for subsurface drip than for surface drip irrigation system. The greatest IWUEs were obtained from subsurface drip and surface drip at T3 (19.7 kg/m3 and 18.3 kg/m3), whereas the lowest IWUEs were those estimated in T1 (15.9 kg/m3 and 14.8 kg/m3, respectively). The primary conclusion is that deficit irrigation strategies present certain advantages to crop water management with minimal effects on production and quality, thus contributing to crop sustainability.

Wind drift and evaporation losses (WDEL) play a significant role in the development of water conservation strategies in sprinkler irrigation. In this study, artificial neural network (ANN) and multiple linear regression (MLR) models were developed by taking data collected from published studies on predicted WDEL for several design, operational, and meteorological conditions of variables in sprinkler irrigation. Five combinations of input variables, including riser height, operating pressure, main nozzle diameter, auxiliary nozzle diameter (da), water discharge by main nozzle, water discharge by auxiliary nozzles, wind speed (WS), air temperature, and relative humidity were used to create prediction models for WDEL. The ANN and MLR models were trained and tested on 70% and 30% of the data points, respectively. The accuracy of the models was assessed by the coefficients of correlation (r), overall indices of model performance (OI), root mean square errors (RMSE), and mean absolute errors (MAE). Statistical results showed that the ANN and MLR models with all input variables had the best predicting capabilities. When comparing the results of different ANN and MLR models, it was seen that the ANN models had more success in predicting WDEL. The ANN models gave higher r (0.843–0.956) and OI (0.794–0.909) values, and lower RMSE (2.662%–4.886%) and MAE (2.197%–3.729%) values compared to the MLR models in the training stage. The MLR models’ r values ranged from 0.794 to 0.864, OI values ranged from 0.747 to 0.816, RMSE values ranged from 4.562% to 5.514%, and MAE values ranged from 3.513% to 4.414%. Furthermore, a contribution analysis found that the design parameter da and the climatic parameter WS were considered to obtain the most robust estimation model. It can be stated that the ANN model is a more suitable tool than the MLR model for the prediction of WDEL from sprinkler-irrigation.

Predicting groundwater levels is critical for ensuring sustainable use of an aquifer’s limited groundwater reserves and developing a useful groundwater abstraction management strategy. The purpose of this study was to assess the predictive accuracy and estimation capability of various models based on the Adaptive Neuro Fuzzy Inference System (ANFIS). These models included Differential Evolution-ANFIS (DE-ANFIS), Particle Swarm Optimization-ANFIS (PSO-ANFIS), and traditional Hybrid Algorithm tuned ANFIS (HA-ANFIS) for the one- and multi-week forward forecast of groundwater levels at three observation wells. Model-independent partial autocorrelation functions followed by frequentist lasso regression-based feature selection approaches were used to recognize appropriate input variables for the prediction models. The performances of the ANFIS models were evaluated using various statistical performance evaluation indexes. The results revealed that the optimized ANFIS models performed equally well in predicting one-week-ahead groundwater levels at the observation wells when a set of various performance evaluation indexes were used. For improving prediction accuracy, a weighted-average ensemble of ANFIS models was proposed, in which weights for the individual ANFIS models were calculated using a Multiple Objective Genetic Algorithm (MOGA). The MOGA accounts for a set of benefits (higher values indicate better model performance) and cost (smaller values indicate better model performance) performance indexes calculated on the test dataset. Grey relational analysis was used to select the best solution from a set of feasible solutions produced by a MOGA. A MOGA-based individual model ranking revealed the superiority of DE-ANFIS (weight = 0.827), HA-ANFIS (weight = 0.524), and HA-ANFIS (weight = 0.697) at observation wells GT8194046, GT8194048, and GT8194049, respectively. Shannon’s entropy-based decision theory was utilized to rank the ensemble and individual ANFIS models using a set of performance indexes. The ranking result indicated that the ensemble model outperformed all individual models at all observation wells (ranking value = 0.987, 0.985, and 0.995 at observation wells GT8194046, GT8194048, and GT8194049, respectively). The worst performers were PSO-ANFIS (ranking value = 0.845), PSO-ANFIS (ranking value = 0.819), and DE-ANFIS (ranking value = 0.900) at observation wells GT8194046, GT8194048, and GT8194049, respectively. The generalization capability of the proposed ensemble modelling approach was evaluated for forecasting 2-, 4-, 6-, and 8-weeks ahead groundwater levels using data from GT8194046. The evaluation results confirmed the useability of the ensemble modelling for forecasting groundwater levels at higher forecasting horizons. The study demonstrated that the ensemble approach may be successfully used to predict multi-week-ahead groundwater levels, utilizing previous lagged groundwater levels as inputs.

An in-situ field study on two types of irrigation methods and three irrigation regimes was conducted in a sandy loam soil located at King Saud University, Riyadh, Saudi Arabia in 2015 and 2016. The study was to assess the effects of different irrigation methods on physiological and yield responses of tomato crops under water shortage conditions. The tested irrigation methods were surface drip irrigation (SDI) and subsurface drip irrigation (SSDI) systems. Irrigation treatments consisted of three strategies: (1) plants were irrigated with a water depth of 100% of the full irrigation supply; (2) plants were irrigated with a water depth of 80% of the full irrigation supply; and (3) plants were irrigated with a water depth of 60% of the full irrigation supply. Results indicated that water shortage significantly affected yield and quality response for each season. Over a 2-year average, yield increase was greatest in T1-SSDI followed by T2-SSDI and then T1-SDI. The yield response factor was 0.95 and 1.05 for SSDI and SDI, respectively. The highest water use efficiency values were obtained in T2-SSDI (16.3 kg m−3) and T1-SSDI (15.6 kg m−3), and the lowest ones, those estimated in T1-SDI (10.9 kg m−3) and T3-SDI (9.5 kg m−3).

An increasing scarcity of water, as well as rapid global climate change, requires more effective water conservation alternatives. One promising alternative is rainwater harvesting (RWH). Nevertheless, the evaluation of RWH potential together with the selection of appropriate sites for RWH structures is significantly difficult for the water managers. This study deals with this difficulty by identifying RWH potential areas and sites for RWH structures utilizing geospatial and multi-criteria decision analysis (MCDA) techniques. The conventional data and remote sensing data were employed to set up needed thematic layers using ArcGIS software. The soil conservation service curve number (SCS-CN) method was used to determine surface runoff, centered on which yearly runoff potential map was produced in the ArcGIS environment. Thematic layers such as drainage density, slope, land use/cover, and runoff were allotted appropriate weights to produced RWH potential areas and zones appropriate for RWH structures maps of the study location. Results analysis revealed that the outcomes of the spatial allocation of yearly surface runoff depth ranging from 83 to 295 mm. Moreover, RWH potential areas results showed that the study areas can be categorized into three RWH potential areas: (a) low suitability, (b) medium suitability, and (c) high suitability. Nearly 40% of the watershed zone falls within medium and high suitability RWH potential areas. It is deduced that the integrated MCDA and geospatial techniques provide a valuable and formidable resource for the strategizing of RWH within the study zones.

Field experiments have been conducted in King Saud University, Riyadh- Saudi Arabia to study the weather-based irrigation controllers (WBICs) affecting agronomical characteristics and water use of irrigated. The assessed WBICs technologies were Weathermatic SL1600 and Hunter pro C controllers under subsurface drip irrigation system. The study investigated the effect of these technologies and its suitability for agricultural applications. The main results in this study can be summarized as the WBICs had significantly affected the tomato yield, water use efficiency and water savings. The WBICs could save irrigation water by 32.4 % and increased water use efficiency greatly up to 50.8 %, while maintaining competing yield as compared to a time-based irrigation schedules (control). Furthermore, the agronomical characteristics (vegetative growth, fruit quality and fruit yield traits) confirmed the priority of the WBICs when they compared with various time-based irrigation schedules.

CoxOy&ndash, manganese carbonate (X%)(CoxOy&ndash, MnCO3 catalysts (X = 1&ndash, 7)) were synthesized via a straightforward co-precipitation strategy followed by calcination at 300 &deg, C. Upon calcination at 500 &deg, C, these were transformed to CoxOy&ndash, dimanganese trioxide i.e., (X%)CoxOy&ndash, Mn2O3. A relative catalytic evaluation was conducted to compare the catalytic efficiency of the two prepared catalysts for aerial oxidation of benzyl alcohol (BzOH) to benzaldehyde (BzH) using O2 molecule as a clean oxidant without utilizing any additives or alkalis. Amongst the different percentages of doping with CoxOy (0&ndash, 7% wt./wt.) on MnCO3 support, the (1%)CoxOy&ndash, MnCO3 catalyst exhibited the highest catalytic activity. The influence of catalyst loading, calcination temperature, reaction time, and temperature and catalyst dosage was thoroughly assessed to find the optimum conditions of oxidation of benzyl alcohol (BzOH) for getting the highest catalytic efficiency. The (1%)CoxOy&ndash, MnCO3 catalyst which calcined at 300 &deg, C displayed the best effectiveness and possessed the largest specific surface area i.e., 108.4 m2/g, which suggested that the calcination process and specific surface area play a vital role in this transformation. A 100% conversion of BzOH along with BzH selectivity &gt, 99% was achieved after just 20 min. Notably, the attained specific activity was found to be considerably larger than the previously-reported cobalt-containing catalysts for this transformation. The scope of this oxidation reaction was expanded to various alcohols containing aromatic, aliphatic, allylic, and heterocyclic alcohols without any further oxidation i.e., carboxylic acid formation. The scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD), fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and Brunauer&ndash, Emmett&ndash, Teller (BET) specific surface area analytical techniques were used to characterize the prepared catalysts. The obtained catalyst could be easily regenerated and reused for six consecutive runs without substantial decline in its efficiency.

The proper planning of storage structures, waterways, irrigation schemes, water harvesting, erosion control structures, and groundwater development strategies requires accurate estimation of surface runoff. However, hydrologists in Saudi Arabia face serious challenges, specifically due to the rare availability of surface runoff data. In this study, the soil conservation service-curve number (SCS-CN) method integrated with geographic information system (GIS) and remote sensing (RS) was utilized to estimate the surface runoff in Wadi-Uranah basin, in the western region of Saudi Arabia. Different thematic maps such as slope, hydrologic soil group (HSG), land use/land cover (LULC), and daily rainfall have been created in GIS environment and processed to generate the curve number (CN) and surface runoff maps. Based on the soil classification results, the study area was categorized into two HSGs (B and C). The dominant HSG was group C, representing about 98.8% of the total area. The LULC analysis showed four main land use types in the study region: urban, rocks, barren soil, and agricultural areas. Furthermore, the finding results showed that CN values for the normal conditions (CNII) ranged between 74 and 93 in agricultural and both urban and rock areas, respectively. The CNII values were further corrected using slope data to derive slope-adjusted CNII. Moreover, the rainfall-runoff results showed an increase in the daily runoff of the study region with a minimum of 15 mm to a maximum of 74 mm. Another interesting result was rainfall-runoff linear regression analysis that showed a good correlation of 0.98. Additionally, the peak runoff hydrograph flows for 10-, 50-, and 100-year return periods obtained from the SCS-based dimensionless unit hydrograph were 828, 1353, and 1603 m3/s, respectively. Therefore, this study highlights that the SCS-CN method integrated with RS and GIS deserves further attention for estimating runoff of ungauged basins for better basins management and conservation purposes.

The determination of the water requirements and crop coefficient (Kc) of agricultural crops helps to create an appropriate irrigation schedule, and with the effective management of irrigation water. The aim of this research was to estimate the water requirement, Kc, and water-use efficiency (WUE) of potato using non-weighing-type lysimeters in four regions of the Kingdom of Saudi Arabia (Qassiem, Riyadh, Al-Jouf, and Eastern). Our results clearly show that the accumulated values of the measured crop evapotranspiration of potato derived from the lysimeters were 573, 554, 592, and 570 mm, while the accumulated values of the predicted crop evapotranspiration from Penman-Monteith equation based on FAO (Food and Agriculture Organization) were 651, 632, 672, and 647 mm for the Qassiem, Riyadh, Al-Jouf, and Eastern regions, respectively. The Kc values of potato obtained from the lysimeters were Kc initial (0.58, 0.54, 0.50, and 0.52), Kc middle (1.02, 1.05, 1.13, and 1.10), and Kc end (0.73, 0.74, 0.74, and 0.75) for the Qassiem, Riyadh, Al-Jouf, and Eastern regions, respectively. Based on the amount of water used and the yield achieved, the highest WUE (3.6 kg m&minus, 3) was observed in the Riyadh region, while the lowest WUE (1.5 kg m&minus, 3) was observed in the Al-Jouf region.