Climate-smart agriculture (CSA) has emerged as a promising strategy for sustainably addressing the impacts of climate change by enhancing productivity and adaptability, reducing greenhouse gas (GHG) emissions, and ensuring food security. While research has examined the benefits, effects, and barriers to the widespread adoption of CSA practices, knowledge of the temporal perspective influencing adoption decisions in Africa remains limited. This study aims to identify the most widely adopted CSA practices, understand how farmers’ temporal perspectives shape decision-making, and examine the influence of financial, institutional, market, and policy mechanisms on CSA adoption. The study examined 55 core articles on CSA in Africa, using the PRISMA framework to search for and select the documents. Data were obtained from the Web of Science and Scopus databases. The findings revealed a diverse range of CSA practices implemented in different countries across Africa. These include conservation agriculture (63
This study was performed to evaluate Rhizophagus irregularis and Piriformospora indica as safe alternatives for suppressing the root-knot nematode, Meloidogyne incognita, on lettuce cv. Salinas. The primary aim was to assess the effects of individual and combined applications of these fungi on reducing nematode infestation and enhancing lettuce yield and quality. The combined application exhibited strong nematicidal activity against M. incognita, with efficacy comparable to chemical nematicides. Results showed that the mixed inoculation treatment significantly enhanced plant growth, yield, and enzymatic activity in both the plants and soil. The highest yield increase was observed in the combined treatment, rising from 28,400 heads in the control to 37,025 heads. The combined application of the biological agents significantly suppressed nematode populations. The reproduction factor (RF) was reduced from 1.24 to 0.33. This was accompanied by an 81.08
Apple is a fruit crop of global importance, require clonal rootstocks for its large-scale production. The availability of these rootstocks can be increased by successfully reusing the leftover portion of stock after grafting, successfully reusing these for propagation using hardwood cuttings, which is an easy and affordable method. This study emphasizes the significance of propagating novel exotic rootstocks (M9 T337, Bud 9, Bud 10 and Bud 118) of apples via hardwood stem cuttings of varying lengths (10, 12 and 15 inch) to determine rooting potential of these rootstocks in order to boost apple production during 2021-22. The rooting dynamics and development of apple clonal rootstocks were significantly altered by the varying lengths of hardwood cuttings. The results revealed that the combination having 15 inch cuttings length and M9 T337 rootstock was best by showing highest percentage of rooted cuttings (47.55
Climate change and agriculture are intrinsically connected, with sudden changes in climatic conditions known to adversely impact global food production and security. With the world’s human population projected to reach 9.7 billion by 2050, there is increased pressure on agricultural land to meet the world’s food demand. However, climate change-linked abiotic stressors like drought and high temperatures already result in crop failure and food insecurity. There is an exigent need for climate-adapted sustainable agricultural practices to sustain food production. Among many options being pursued in this regard, utilising extremophiles as plant growth-promoting rhizobacteria (PGPR) and stress alleviators is gaining momentum due to their unique mechanisms at anatomical, physiological, biochemical, and molecular levels that cope with stresses associated with extreme environments, which can be used to promote stress resilience in crops. Therefore, this review critically assesses research evidence on plant growth and stress resilience promoting potentials of extremophiles as an approach to foster crop tolerance to climate change-induced stress, particularly drought. There is strong scientific evidence to suggest that thermophiles directly promote plant growth through processes, including nutrient fixation, enzyme and phytohormone production, mineral solubilisation, stress alleviation, and/or tolerance-induced differential gene expression. However, while the application of extremophiles holds great potential for sustainable food production, several technological, ethical, and ecological challenges limit their use in agriculture. Consequently, effective collaboration among scientific communities, policymakers, and regulatory agencies is needed to create strong frameworks that both promote and regulate the utilisation of agriculture.
Rice seedlings were prepared and germinated under an aseptic technique, maintained under photoautotrophic growth conditions in vitro using vermiculite as the supporting material, and subsequently exposed to aluminum (Al) treatments [low Al (control) and high Al (1.0 mM Al) for 7 days]. The longest root was observed for IR64 genotype under high Al-treatment with upregulation of OsORC3 (Origin Recognition Complex subunit 3). Root length, root fresh weight, and root dry weight of KaoMakKaek (KMK) genotype under high Al treatment were significantly decreased by 19.16
Understanding the spatial variability of soil properties is fundamental for implementation of precision nutrient management in organic farming systems. The present study was conducted in 2022–2023 at the 56.25 ha organic farm in the Trans-Indo-Gangetic Plains of western India, to characterize and map spatial distribution of soil micronutrients. A total of 89 surface soil samples were collected and analyzed for various physico-chemical properties and micronutrient concentrations, including zinc, manganese, iron, copper, lead, cadmium and nickel. Soils exhibited neutral to alkaline reactions with variable salinity, characterized by moderate to high contents of soil organic carbon, available phosphorus and potassium, but comparatively low nitrogen availability. Micronutrient concentrations were generally adequate, except for zinc, which showed localized deficiencies. Geostatistical analysis, employing semivariogram modelling and ordinary kriging, revealed distinct spatial patterns: Gaussian model provided the best fit for zinc, manganese and lead, whereas exponential model more accurately characterized spatial variability of iron, copper, cadmium and nickel. Nugget values varied from 0 to 6.13 while sill values varied from 0.01 to 35.78. Semivariogram ranges varied markedly from 142.64 to 1521.47 m. Zinc and manganese exhibited moderate spatial dependence, whereas iron, copper, lead, cadmium and nickel exhibited strong spatial dependence. Principal component analysis extracted four principal components explaining 73.49
Weeds are the major constraints to productivity in paddy cultivation, often leading to significant yield losses. Among various weed management approaches, mechanical weeding is preferred due to its operational efficiency and sustainability compared to manual and chemical methods. Traditional weeders commonly employ horizontal axis tools. In this study, a novel vertical axis rotary weeder was developed for wetland paddy fields. The weeder consists of a vertical shaft fitted with multiple blades arranged to perform weeding, with a tool spacing of 170 mm, aligned to the crop spacing used in the System of Rice Intensification (SRI). The vertical axis tool was mounted on the test rig powered by a 1.5 hp AC electric motor and the performance was evaluated under simulated conditions in a soil bin. The experimental design followed a Box–Behnken approach, with forward speed (1 km h−1, 1.5 km h−1, 2 km h−1), depth of operation (25 mm, 50 mm, 75 mm), and tool rotational speed (50 rpm [0.39 ms−1], 100 rpm [0.79 ms−1], and 150 rpm [1.18 ms−1]) as independent variables. The optimal parameter combination of 1.5 km h−1 forward speed, 50 mm depth, and 100 rpm (0.79 ms−1) tool rotational speed, resulted in the maximum weeding efficiency of 81.9
This study presents an innovative, non-destructive remote sensing method for estimating sugarcane height using Landsat 8 imagery and meteorological and crop properties from 2018 to 2021 in the Shoeibeyeh area of Khuzestan province (Iran), at the field scale. Spectral bands from the visible to mid-infrared, along with thirty vegetation indices, meteorological data (cumulative temperature and sunny hours), and crop variety and age were used to model sugarcane height. The height of sugarcane was measured weekly across 178 fields, each with an average area of approximately 25 hectares. The dataset was rebalanced using the Synthetic Minority Over-Sampling Technique (SMOTE). Three popular machine learning (ML) methods were evaluated for regression models: Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM). Fifteen scenarios were analyzed, based on the dataset partitioning and these ML algorithms. Although all three ML methods performed well in estimating sugarcane height, RF performed slightly better than ANN and SVM. Based on model accuracy statistics and variable importance coefficients, the 5-RF-100-7 mode, with R2 = 0.86 and NRMSE = 21.96
Drought stress significantly impacts sorghum plant metabolism, growth and quality. This study evaluated the physiological and molecular responses of Sorghum bicolor (L. Moench) genotypes under water deficit, with emphasis on nitrogen metabolism, forage quality, and gene expression. Two brown midrib (CSV 43, SPV 2017) and two non-brown midrib (CSV 15, SPV 462) genotypes were cultivated under field conditions and subjected to drought stress. Morpho-physiological traits, activities of key nitrogen metabolizing enzymes, along with fodder quality parameters were recorded at 45, 55, 65, and 75 days after sowing. Gene expression of GLY-1, D-LDH, PAL, Rubisco, and Stag was assessed in polyethylene glycol (PEG)-primed seedlings of CSV 43 and CSV 15 at 10 and 20 days after treatment. Drought stress reduced chlorophyll content, enzyme activities, and fodder quality, with more pronounced effects observed in non-BMR genotypes. BMR genotypes exhibited superior nitrogen assimilation, greater biomass accumulation, and reduced concentrations of anti-nutritional compounds. Upregulation of GLY-1, D-LDH, Rubisco, and Stag was observed in CSV 43, while PAL expression was higher in CSV 15. Significant associations were identified between nitrogen metabolism traits, yield and quality parameters. BMR genotypes demonstrated enhanced drought tolerance and superior forage potential, underscoring their suitability for cultivation in water-limited regions. Nitrogen metabolism traits and stress-responsive gene expression may serve as reliable selection markers for drought resilience in sorghum.
The objective was to evaluate the genetic groups, categories, and carcass classification of beef cattle to obtain incentives from bonus programs in the meatpacking sector of Mato Grosso do Sul, Brazil. A total of 137 reports from the slaughter of 11,174 animals - castrated male, intact male, and heifers - belonging to the genetic groups Angus, ½ Angus × ½ Nelore (crossbred), and Nelore, were analyzed. The carcasses were evaluated according to the criteria of the following programs: Lista Trace, Cota Hilton, Novilho Precoce, Farol de Qualidade, Protocol 1953, and Protocol Angus. Producer payments were based on the value of the arroba (15 kg of carcass weight, @) in Brazilian reais (R), and the bonus amount awarded by each incentive program according to its specific criteria (R/@). For the carcasses of castrated and intact animals belonging to the Angus genetic group, the highest incentive values per arroba were paid by the Novilho Precoce program (P < 0.05). For heifer carcasses of the same genetic group, the highest incentive value per arroba was paid by the 1953 > 16@ program (P < 0.05). In the Nelore genetic group, the Novilho Precoce program paid higher bonuses for the carcasses of intact males and heifers (P < 0.001). The production of carcasses from Angus or crossbred heifers results in high incentive payments through the 1953 (payment made for carcasses above 16@) program. For both castrated and intact males of all genetic groups, the highest incentive payments are provided by the Novilho Precoce program.
Terpene is an important secondary metabolite during plant development. The gene family of terpene synthases (TPS) is in charge of producing thousands of different terpenes that can increase the environmental fitness of plant. Some types of terpene contribute aroma and flavor that influence consumer preferences in tobacco but the knowledge of the TPS genes encoded by local tobacco cultivars are limited. Here, a total of 186 TPS genes were identified by annotating the tobacco genome sequences. Phylogenetic analysis showed that a few tobacco-exclusive TPS clades emerged recently through gene duplication, which are likely to be responsible for a range of compounds that separate N. tabacum cultivars from its wild relatives. Transcriptome sequencing of two local cultivars at three developmental stages revealed that five TPS genes from the TPS-a and TPS-b lineages are constitutively expressed while other duplicated ones are only expressed at the time of harvest. Additionally, some TPS genes underwent alternative splicing, which further diversified the protein sequences of the TPS gene family. The expression diversity and the evolution dynamics of this important gene family highlighted its critical role in the plant of tobacco. Our study provided candidate gene target for future breeding improvement of this critical industrial crop.
Addressing the effects of climate change and water scarcity is crucial for maintaining global wheat production. This study evaluated 60 spring wheat genotypes from the CIMMYT Core Germplasm (CIMCOG) under both terminal water stress and optimal irrigation at two semi-arid field locations. Researchers analyzed 31 agronomic, morphological, and seed quality traits. Significant genetic diversity was observed, with path analysis identifying biomass (β = 0.642) and harvest index (β = 0.287) as the main direct factors influencing grain yield. Using multivariate methods such as principal component analysis and cluster analysis, the genotypes were effectively grouped into distinct phenotypic categories. Importantly, six drought-tolerant genotypes—CIMCOG_03, CIMCOG_19, CIMCOG_29, CIMCOG_47, CIMCOG_10, and CIMCOG_13—were singled out for their stable performance under water stress. These results define a refined “core collection” of genotypes and emphasize key traits affecting yield, offering a valuable resource for focused breeding efforts, genome-wide association studies, and marker-assisted selection aimed at enhancing wheat resilience and productivity in water-limited environments.
In India, cattle have traditionally served a dual purpose: female cattle are valued for milk production, and male cattle for their draught power in agricultural activities and rural transportation. However, due to the mechanization of agricultural operations, reduction in landholding size, and the prohibition of cattle slaughtering, the utility of male cattle has significantly reduced, making them uneconomical for farmers. Undesired cattle are often abandoned creating animal welfare and public safety concerns. Sexed semen technology, which enables the production of offspring of desired sex, is a practical and ethically aligned solution for addressing the issue of surplus male cattle. Nevertheless, its adoption remains constrained by a range of technical, economic, institutional, regulatory, and policy factors. In this study, we have prioritized strategies using Analytical Hierarchy Process (AHP) method, to unlock the potential of sexed semen technology for optimizing cattle population while promoting ethical sustainability. The findings underscore the necessity of improving the conception efficiency of sexed semen through focused breeding research, disseminating information regarding its welfare and productivity potential, enhancing its availability, and incentivizing its adoption. To achieve this, the findings strongly advocate for collaborative efforts among government institutions, cooperatives, and private enterprises to ensure that this technology operates effectively in real-world conditions.
A field trial carried out to compare twelve-grain sorghum hybrids, their corresponding parental lines, and H-306, the check hybrid, under different moisture regimes (100
Agriculture in Sub-Saharan Africa (SSA) is vital to food security and livelihoods, yet faces severe threats from climate change, underscoring the critical link between climate research and agriculture for adaptation. However, the scholarly response to this challenge remains uneven and fragmented, with critical gaps in regional and thematic coverage. To address this, we conducted a bibliometric and content analysis of 1565 Scopus-indexed publications (2004–2024) on climate change and agriculture in SSA. The analysis reveals nearly a fivefold increase in publications ( 472
Salinity continues to limit chickpea (Cicer arietinum L.) production, yet only a small part of the crop’s global diversity has been evaluated for tolerance. This study aimed to characterize genotypic variation in salinity tolerance, identify early physiological indicators of salt response, develop a simple model to predict genotype performance, and examine sequence variation in an HKT1-like gene among contrasting genotypes. We first screened 50 diverse accessions and found that 80 mM NaCl was a suitable level for distinguishing salt responses. Twenty-nine genotypes were then evaluated for a range of morpho-physiological traits, and biochemical assays and partial HKT1-like sequence analysis were carried out on ten contrasting genotypes. Heat map clustering grouped the genotypes into five categories, from highly tolerant to highly susceptible. Tolerant genotypes maintained higher chlorophyll content, relative water content, membrane stability, and antioxidant activity, along with lower Na⁺ levels and reduced Na⁺/K⁺ ratios. A regression model based on the salt tolerance index of chlorophyll content and shoot length explained 99
Sustainable soil management, driven by the spatial variability of soil properties, is crucial for enhancing crop productivity and preventing land degradation. India the world’s second-largest tea producer is witnessing soil fertility decline in major tea-growing regions like Terai and Dooars due to prolonged monoculture. This study aims to assess the spatial variability of soil properties and delineate soil management zones (MZs) for efficient nutrient management in tea plantations of Jalpaiguri district, West Bengal. A total of seventy-eight (78) geo-referenced representative surface soil samples (0–0.20 m depth) were collected from tea gardens of Mal, Matiali, and Nagrakata blocks and analyzed for soil properties viz. soil pH, organic carbon, available nitrogen, phosphorus, potassium, sulphur, boron, DTPA extractable zinc, copper, iron and manganese. The soil properties exhibited wide variation, with coefficients of variation ranging from low (11.2
Cowpea is an essential crop in Burkina Faso’s agriculture, but its production must cope with the consequences of climate change, particularly drought, which significantly reduces yields. The mechanisms of adaptation to drought vary between species and varieties and need to be understood to develop more drought-tolerant varieties. Seven cowpea genotypes were subjected to a 21-day water deficit induced before flowering under a screen house, using plastic pots. A split-plot design with three replications was used. The water regimes included continuous watering and induction of a 21-day water deficit initiated from the 30th day after sowing (DAS). Physiological, morphological, and productivity parameters were measured before and during the water deficit application. The results demonstrated a significant depressive effect of stress conditions on the evaluated parameters. The water deficit reduced average grain weight by 47
Silica (Si) in plants has become a subject of increasing interest for various communities, e.g., those involved in global change biogeochemistry, agronomy and biotechnology, and many techniques have been applied to quantitatively determine the Si content of plants. However, there are few applicable techniques for the in-situ assessment of Si contents because many methods are destructive and expensive. As a recent alternative, spectrophotometric analyses using hyperspectral data are both non-destructive and comparatively cheap, and machine learning algorithms have been used to enhance hyperspectral remote sensing to evaluate biochemical properties. The objectives of this study were to examine the potential of hyperspectral remote sensing approaches to estimate the silica content of Zizania latifolia using conventional machine learning algorithms including random forests, extreme gradient boosting and Cubist. The results indicate that Cubist was the best algorithm, achieving a ratio of performance to deviation of 2.02 and a root mean square error of 42.52 µg cm− 2.
Land use and land cover change (LULCC) strongly influences agricultural productivity and urban planning in arid regions. This study integrated multi‑temporal Landsat 8 imagery (2013, 2017, 2020, 2024), supervised classification in ENVI, and soil profile analysis (n = 15) to assess LULCC and land productivity in Assiut and Minya, Egypt. Results showed that in the full scene, vegetation cover declined from 50.10
