International Journal of Environment and Climate Change

Energy Potential and Fuel Quality of Biomass from Selected Rice Varieties in India

Mon, 02 Nov 2026 00:00:00 +0000

Rice straw is a widely available agricultural residue, but differences in its physicochemical composition can affect its suitability for energy production. This study assessed the fuel quality and energy potential of straw from 16 selected rice varieties in India. Swarna rice straw was characterised experimentally, whereas corresponding data for 15 other varieties were obtained from published studies. Swarna samples were sun-dried, ground and sieved before proximate and ultimate analyses and higher heating value (HHV) determination using an oxygen bomb calorimeter. The compiled data were compared descriptively because differences in data sources and analytical conditions precluded reliable inferential testing. Across the selected varieties, moisture content ranged from 5.12% to 11.04%, ash content from 8.98% to 22.16%, volatile matter from 63.54% to 75.69%, fixed carbon from 6.36% to 18.18%, and HHV from 11.46 to 22.98 MJ kg⁻¹. Swarna exhibited a moisture content of 5.12%, ash content of 10.90%, fixed carbon content of 18.18% and HHV of 15.05 MJ kg⁻¹. Nabina recorded the highest reported HHV, whereas Maudamani recorded the lowest. The combination of low moisture, moderate ash and relatively high fixed carbon indicates that Swarna merits further evaluation as a solid biofuel feedstock. However, these findings represent preliminary fuel-quality screening rather than a definitive ranking of varieties. Standardised comparative testing and conversion experiments are needed to assess practical performance.

Studies on the Pollinator Fauna on Drumstick (Moringa oleifera L.)

S. Lohith, B. V. Shwetha, K. S. Jagadish — Tue, 03 Nov 2026 00:00:00 +0000

This study documented the species composition, relative abundance and daily activity patterns of insect floral visitors to drumstick (Moringa oleifera Lam.) var. PKM-1 at the Zonal Agricultural Research Station, Gandhi Krishi Vigyana Kendra, Bengaluru, during the 2023–2024 flowering period. Insect floral visitors were recorded through visual observations and sweep-net sampling. During peak flowering in April 2024, observations were made at hourly intervals from 0600 to 1800 h over five days. Each five-minute sampling period covered 25 inflorescences distributed across five trees. Floral-visitor diversity was evaluated using the Shannon–Wiener index, while relative dominance was assessed using the Berger–Parker index. Overall, 24 insect floral visitor species belonging to five orders—Hymenoptera, Diptera, Hemiptera, Coleoptera and Lepidoptera—were documented. Hymenoptera was the most species-rich and abundant order. Among the 11 major floral visitors considered in the abundance analysis, Apis dorsata was predominant (29.57%), followed by Xylocopa latipes (16.57%) and Apis cerana (14.28%). Total visitor abundance was highest during 0900–1000 h (57.60 insects per 25 inflorescences per five minutes) and lowest during 0600–0700 h (12.40). The Shannon–Wiener index ranged from 1.14 to 2.18, reaching its maximum during 1200–1300 h. Apis dorsata also recorded the highest Berger–Parker dominance index (0.29). These findings describe the composition and temporal variation of the observed insect floral visitor assemblage under the study conditions.

Climate Vulnerability of Farm Households in a Context of Internal Displacement: A Livelihood Vulnerability Index Approach in Passoré and Yatenga, Burkina Faso

Tue, 03 Nov 2026 00:00:00 +0000

Aim: This study assesses the livelihood vulnerability of farm households to climate variability and change in two provinces, Passoré and Yatenga, of the Yaadga region of Burkina Faso. It pays particular attention to the context of internal displacement and to the proportion of surveyed households hosting internally displaced persons (IDPs).

Study Design: A descriptive comparison of provincial vulnerability profiles based on a purposive, quota-based household survey.

Place and Duration of Study: Four communes in the provinces of Passoré and Yatenga; data were collected from December 2025 to January 2026.

Methodology: Primary data were collected through structured questionnaires administered to 300 farm households. Secondary climate data complemented the survey. Vulnerability was assessed using the Livelihood Vulnerability Index (LVI) and the IPCC-framed LVI-IPCC approach. The indices were aggregated and compared at the provincial level.

Results: The descriptive LVI values were higher in Yatenga (0.34) than in Passoré (0.31). Yatenga had higher scores for sociodemographic characteristics, livelihood strategies, water and food, whereas Passoré had higher scores for health and social capital. Climate-variability scores were similar in the two provinces (0.375 in Passoré and 0.366 in Yatenga). IDP-hosting households represented 56% of the surveyed sample in Yatenga and 25.33% in Passoré. The multiplicative LVI-IPCC values were close to zero (0.0022 in Passoré and −0.0049 in Yatenga), while the additive formulation gave 0.329 for Passoré and 0.348 for Yatenga. No statistical tests were conducted, so these differences should be interpreted as descriptive rather than statistically significant.

Conclusion: The provincial profiles indicate different patterns of livelihood vulnerability in Passoré and Yatenga, although the observed differences have not been tested for statistical significance. In Yatenga, the results point to water access, food security, livelihood security and support for households hosting IDPs as important priorities. In Passoré, access to health services and household support mechanisms deserve attention. In both provinces, early-warning systems and access to climate information need strengthening. These findings can inform territorially tailored adaptation planning, while further research using representative samples and household-level inferential analysis is needed to test the robustness of the observed differences.

Assessment of Chickpea (Cicer arietinum L.)-Chandrasur (Lepidium sativum L.) Intercropping Productivity Using Competitive Indices under Varying Moisture Regimes

Mahanand Sahu , U. K. Dhruw, Sakshi Bajaj, Hemlata Nirala, Sanjeev Gurjar — Tue, 03 Nov 2026 00:00:00 +0000

A two-season field investigation conducted at Raipur, Chhattisgarh, during the 2020–2021 and 2021–2022 rabi seasons examined chickpea (Cicer arietinum L.) and garden cress (Lepidium sativum L.) grown in replacement-series arrangements under three irrigation schedules. A split-plot design with three replications comprised no irrigation, irrigation at 35 days after sowing (DAS), and irrigation at 35 and 70 DAS as main-plot treatments, crossed with sole crops and 1:1, 2:1, 3:1 and 2:2 chickpea–garden cress row arrangements. Reported component seed-yield means were used to derive land equivalent ratios (LER), proportion-adjusted competitive ratios, aggressivity, relative crowding coefficients and actual yield loss indices. Across the two seasons, mean chickpea yield increased from 945.59 kg ha⁻¹ without irrigation to 1,347.15 kg ha⁻¹ with two irrigations. The 3:1 arrangement produced chickpea seed yields of 1,385.83 and 1,142.36 kg ha⁻¹ and garden cress yields of 420.73 and 570.74 kg ha⁻¹, respectively. Its LERs, obtained from treatment-mean yields, were 1.27 and 1.30. In contrast to interpretations based on unadjusted yield predominance, proportion-standardised competitive ratios for chickpea in the 3:1 arrangement were 0.83 and 0.62, indicating greater relative competitiveness of garden cress per unit sown share. The yield and index estimates suggest land-use complementarity, but the analyses of derived indices are descriptive because the replicate-level data required for uncertainty estimation were unavailable. Consequently, agronomic interpretations should be restricted to the seasons and environments studied.

Visitor Satisfaction and the Ex Situ Conservation Potential of Medicinal Plant Garden: Implications for Biodiversity Conservation and Public Engagement

Tue, 03 Nov 2026 00:00:00 +0000

Herbal gardens play a pivotal role in the conservation of medicinal plant diversity, while simultaneously serving as centres for education, recreation, and public engagement. This study assesses visitor perceptions, satisfaction, and the conservation significance of Dr. Sushila Tiwari Herbal Garden, Rishikesh, Uttarakhand, India. A cross-sectional survey was conducted from January to June 2023 among 150 visitors using a structured questionnaire covering demographic, visitation, usage, and satisfaction-related questions. Responses were summarised with descriptive statistics, and the conservation status of the collection was assessed against the IUCN Red List. All respondents agreed that the garden has a role in conserving medicinal plants. Most rated their visit as excellent (52.7%) or good (40.0%); more than 92% intended to revisit and 87.3% would recommend the garden. Pathway design and maintenance received the highest share of ‘strongly agree’ responses (88.0%), followed by interpretive signage (75.3%) and plant diversity (74.7%), while landscape aesthetics received the lowest (63.3%). The collection contained 105 medicinal plant taxa, including one Critically Endangered, four Endangered, one Near Threatened, 61 Least Concern, and 38 Data Deficient medicinal plant taxa. The nakshatra vatika, an astro-botanical planting of 27 tree species, links the collection with local cultural knowledge. Therefore, the garden contributes to ex situ conservation of plants, germplasm preservation and biodiversity conservation.

Farmers' Perceptions of Temperature and Rainfall Changes: A Descriptive Comparison of Four Villages in Cilacap Regency, Indonesia

Watemin, Pujiati Utami, Fadhil Adi Nugraha , Retno Dwiyanti — Tue, 03 Nov 2026 00:00:00 +0000

Climate variability poses important challenges for farm management, but farmers' interpretations of changing weather conditions may differ across locations. This study describes perceived temperature and rainfall changes among 100 farmers in four villages of Cilacap Regency, Central Java, Indonesia. The sample comprised 25 farmers from each of Cilopadang and Boja villages in Majenang District and Sidamulya and Penyarang villages in Sidareja District. Questionnaire-derived summary scores for four perception indicators were compared descriptively between the two district-based groups. The reported scores were identical for perceived temperature change (80.8 in each group). Majenang respondents had higher reported scores for hotter temperatures (86.4 versus 80.0), changes in rainfall (84.4 versus 80.8), and reduced rainfall (82.8 versus 79.2). The corresponding differences were 6.4, 3.6, and 3.6 score points, respectively. These differences represent descriptive comparisons of questionnaire-derived scores within the sampled villages and do not establish statistical significance, independently observed climatic trends, or differences in agricultural impacts. Further research incorporating transparent questionnaire scoring procedures, meteorological observations, and broader geographical sampling is needed to investigate the relationship between farmers' perceptions and observed climatic conditions.

Effect of pH and Temperature on the Mycelial Growth of Alternaria lini Causing Alternaria Blight of Linseed under in vitro Conditions

Himanshu Kumar Gupta, Satyendra Nath Singh , Ramesh Singh, V. K. Singh — Thu, 05 Nov 2026 00:00:00 +0000

Alternaria blight of linseed, caused by Alternaria lini, is associated with fungal development under environmental conditions that influence mycelial growth and sporulation. This study evaluated the effects of pH and temperature on the radial growth, colony characteristics and sporulation of A. lini under in vitro conditions. The fungus was cultured on potato dextrose agar, with five pH treatments (4, 5, 6, 7 and 8) and five incubation temperatures (15, 20, 25, 30 and 35°C). Three replicates were maintained per treatment, and colony growth was measured after seven days of incubation. Among the pH treatments, maximum radial growth occurred at pH 6 (36.33 mm), followed by pH 7 (34.00 mm), whereas minimum growth was observed at pH 4 (11.67 mm). Excellent sporulation was recorded at pH 6 and 7. Among the temperature treatments, radial growth was greatest at 25°C (39.67 mm), followed by 30°C (25.33 mm), 20°C (23.33 mm) and 15°C (20.67 mm), and was lowest at 35°C (13.00 mm). Sporulation was excellent at 25°C and 30°C but poor at 15°C and 35°C. Colony growth patterns and textures also varied across treatments. The findings indicate that pH 6 and 25°C favoured radial mycelial growth of the tested culture on this medium. These laboratory observations describe fungal growth responses and do not establish field disease-severity thresholds.

Heavy Metal Contamination in Vegetables Species and Associated Health Risks at Bachaoli Bujurg, Jhansi, Uttar Pradesh, India

Rajeev Ranjan Prasad Kaushik, Vinit Kumar, H. D. Bhartiya, Anshu Dhaka — Fri, 06 Nov 2026 00:00:00 +0000

Contamination of edible vegetables by heavy metals is a potential pathway of dietary exposure and requires assessment using crop-specific measurements and age-related consumption assumptions. A field investigation was conducted during 2023–24 and 2024–25 at Bachaoli Bujurg (Site 1) to assess heavy metal accumulation in commonly consumed vegetables and evaluate the potential health risks associated with dietary exposure to contaminated vegetables. Five vegetables, namely spinach, brinjal, cabbage, okra and tomato, were evaluated for the concentrations of lead (Pb), cadmium (Cd), zinc (Zn), iron (Fe) and copper (Cu), along with exposure parameters, estimated daily intake (EDI), target hazard quotient (THQ) and hazard index (HI). Among the vegetables studied, spinach recorded the highest pooled Pb concentration (0.407 mg kg⁻¹), followed by brinjal (0.355 mg kg⁻¹), cabbage (0.328 mg kg⁻¹), okra (0.3125 mg kg⁻¹) and tomato (0.284 mg kg⁻¹). Cadmium concentration was also highest in spinach (0.082 mg kg⁻¹) and lowest in tomato (0.0415 mg kg⁻¹). In contrast, okra recorded the highest pooled concentrations of Zn (0.1315 mg kg⁻¹) and Fe (0.1305 mg kg⁻¹), whereas tomato showed comparatively lower concentrations. Copper concentration was comparatively higher in okra, which was also reflected in its higher estimated dietary intake. The exposure parameters indicated a higher vegetable ingestion rate in adults, increasing from 0.21 kg day⁻¹ in 2023–24 to 0.30 kg day⁻¹ in 2024–25, with a pooled mean of 0.255 kg day⁻¹, whereas children showed a pooled ingestion rate of 0.105 kg day⁻¹. The exposure frequency was 365 days year⁻¹ for both age groups. Adults had pooled exposure duration of 30.15 years, compared with 7.07 years for children, while the pooled average body weights were 57.84 and 15.615 kg, respectively. The estimated daily intake of Pb was highest through spinach consumption (0.0013 mg kg⁻¹ day⁻¹), followed by brinjal (0.0012 mg kg⁻¹ day⁻¹), whereas tomato showed the lowest pooled Pb intake (0.0008 mg kg⁻¹ day⁻¹). For Cd, spinach recorded the highest pooled EDI (0.0002 mg kg⁻¹ day⁻¹), while Zn intake was highest through spinach and okra (0.0004 mg kg⁻¹ day⁻¹). Copper showed the highest pooled EDI in okra (0.0008 mg kg⁻¹ day⁻¹). The pooled THQ values for Pb, Cd, Zn, Fe and Cu were 0.00133, 0.002455, 0.001025, 0.000625 and 0.00112, respectively. All THQ values were substantially below the benchmark value of 1.0, indicating low estimated non-carcinogenic risk from individual metals through vegetable consumption. The pooled hazard index (HI) was also considerably below 1.0, indicating that the combined exposure to Pb, Cd, Zn, Fe and Cu through consumption of the studied vegetables was below the commonly used non-carcinogenic risk threshold. Overall, spinach exhibited comparatively greater accumulation of Pb and Cd, whereas okra showed higher accumulation and dietary intake of Zn, Fe and Cu. The findings emphasise the importance of continuous monitoring of heavy metal concentrations in agricultural soils and vegetables and the assessment of age-specific dietary exposure to ensure long-term food safety under the agro-climatic conditions of the Bachaoli Bujurg region.

Comparative Assessment of Rice Husk, Sugarcane Bagasse, and Pinecone as Bioadsorbents for Lead and Copper Removal from Wastewater: Insights from SEM–EDX Characterization

Sakshi, D. S. Malik, Achin Kumar — Fri, 06 Nov 2026 00:00:00 +0000

Heavy-metal contamination of wastewater has increased interest in using agricultural waste as potential low-cost bioadsorbents. This study compared rice husk (RH), sugarcane bagasse (SB), and pinecone (PC) for the removal of Pb(II) and Cu(II) from wastewater and characterised the materials using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). The untreated residues were washed, ground, and sieved to 200–250 µm, then investigated in triplicate batch experiments at an adsorbent dose of 10 g/L, an agitation speed of 150 rpm, a contact time of 120 min, and a temperature of 27 ± 2 °C. SEM revealed porous, layered, and fibrous structures in RH; granular and fibrous structures in SB; and rough, flaky surfaces with microcracks and pores in PC. EDX showed that SB had the highest carbon content (68.4 ± 3.4 wt.%), followed by PC (67.6 ± 3.3 wt.%) and RH (48.0 ± 2.4 wt.%). RH had the highest silicon content (19.8 ± 0.9 wt.%). PC recorded the highest Pb(II) removal efficiency (72.94 ± 2.60%), followed by RH (51.20 ± 2.20%) and SB (27.91 ± 1.40%). Cu(II) removal was also highest for PC (98.11 ± 3.20%), followed by SB (94.36 ± 2.70%) and RH (88.40 ± 2.40%). Under the studied conditions, PC performed best for both metals and merits further assessment for wastewater treatment. Further studies under a wider range of operating conditions are needed to establish the suitability of pinecone as a practical bioadsorbent for wastewater treatment.

Stand Structure and Carbon Stock in Logged and Unlogged Areas of Managed Tropical Forests in Cameroon: The case of FMUs 10 038 and 10 054 in East Cameroon

Fri, 06 Nov 2026 00:00:00 +0000

In Cameroon, forest resource management is carried out in production forests, particularly within Forest Management Units (FMUs). However, the impact of logging on stand structure and carbon stocks before and after logging remains poorly documented. The objective of this study is to assess the influence of logging activities on stand structure and carbon stock in logged and unlogged forest stands within UFAs 10 038 and 10 054. Six permanent plots measuring 200 x 200 m were established in logged and unlogged stands. Three plots were therefore established in the logged stands and three in the unlogged stands. Within each permanent plot 20 m x 20 m quadrats were established at the four sides of the plot’s base to inventory all woody species with a DBH ≥ 10 cm. The results showed that species richness is higher in the unlogged stands (152 species) than in the logged (141 species). Two of the stands studied exhibited an inverted “J”-shaped structure. There is no significant difference between logged and unlogged in terms of density and basal area. The carbon stored in unlogged stands (55.61 tC/ha with a mean of of 18.53 tC/ha) is not significantly different from that in logged (52.32 tC/ha with a mean of of 17.44 tC/ha). These study indicate that well-planned forest harvesting, implemented in accordance with the principles of sustainable forest management, can enable timber production without significantly degrading stand structure or reducing carbon stocks.

Assessment of Rainfall Variability and Extreme Wet and Dry Events Using the Standardized Precipitation Index in the Bharathapuzha River Basin, Kerala, India

Mon, 09 Nov 2026 00:00:00 +0000

Rainfall variability and extreme wet and dry events were characterized for the Bharathapuzha River Basin, Kerala, India, using 35 years (1991–2025) of India Meteorological Department (IMD) 0.25° gridded daily rainfall data. The Standardized Precipitation Index (SPI) was calculated at 1-, 3-, 6- and 12-month timescales. Trends and change points were evaluated using the Mann–Kendall test, Sen’s slope estimator, and Pettitt’s test. The mean annual rainfall was 2,073 mm with a coefficient of variation of 19.7 percent, and nearly two-thirds of the rainfall was received in the southwest monsoon season. Annual rainfall varied from 1,251 mm in 2003 to 2,923 mm in 2018. SPI-6 registered eight extreme wet and eleven extreme dry events; the most intense wet event occurred between June and November 2018 (peak SPI = +2.81), and the longest dry event lasted eight months from July 2003 to February 2004. Trends in the frequency of extreme wet and dry months were not statistically significant at the SPI-1 timescale (p = 0.220 and p = 0.922, respectively). Annual rainfall was significantly different among the three study subperiods (p = 0.043), but the long-term trend was not significant (p = 0.105). Trends of increasing September rainfall and increasing frequency of wet months at the SPI-3 and SPI-6 timescales were not significant after correction for multiple tests. The results show significant variability in rainfall and the presence of different wet and dry periods, demonstrating the importance of multi-timescale SPI analysis for characterizing meteorological rainfall conditions relevant to flood and drought assessment in monsoon-dominated river basins.

Determinants of the Integration of Local Knowledge and Organizational Innovations by Producers Facing Climate Change in the Koulsé Region, Burkina Faso

Mon, 09 Nov 2026 00:00:00 +0000

Background: Climate change threatens agro-pastoral livelihoods in Burkina Faso, while the roles of local environmental indicators and organizational initiatives in producer responses remain insufficiently documented in the Koulsé region.

Aims: This study analysed producers’ resilience strategies in Burkina Faso in the face of climate change.

Place and Duration of Study: The rural communes of Boussouma and Korsimoro in the Koulsé region, between November and December 2025.

Methodology: The data were collected through a survey of 270 households. Descriptive analyses and Poisson and logit econometric models were applied.

Results: The results show that the migratory pattern of the Tockus nasatus bird (15 %), the disappearance of the Myrmica sp. insect and the construction of termite mounds by Cubitermes sp. (15 %), wind patterns (13 %) and the maturation of certain trees (Pterocarpus lucens and Ficus sycomorus : 4 %) guide farmers’ decision-making regarding the practices to adopt in anticipation of the likely impacts of climate change. These practices include agro-sylvo-pastoral techniques (zaï: 88 %, stone bunds: 78 %, fattening: 37 %, agroforestry: 92 %) and organizational innovations, including Village Savings and Loan Associations (VSLA: 40%). The econometric analysis reveals that technical training (IRR = 1.232; p < .001), land tenure status (IRR = 1.489; p = .018) and cultivated area (IRR = 1.028; p = .003) are significantly and positively associated with the intensity of resilience practices. VSLA participation is predominantly female (OR = 0.183; p < .001) and is influenced by institutional support (OR > 4; p < .05).

Conclusion: Greater recognition of local knowledge in agricultural policies and institutional support for rural women could support a more effective response to climate change.

Mapping Tomato Cultivar Distribution and Production Constraints across Three Distinct Agroecological Zones in Kenya

Grace Kiruki, Felister Nzuve, John Muhia — Tue, 10 Nov 2026 00:00:00 +0000

Modern commercial tomato hybrids of Solanum lycopersicum L. display a narrowed genetic base containing only about 5% of the genetic variation found in wild relatives, leading to severe genetic erosion and extreme vulnerability to pests and diseases. In Kenya, where tomato production has been reported to reach 410,033 tonnes annually, continuous pesticide application has triggered the evolution of local pathogens, creating an urgent need to identify resilient germplasm with low chemical demands. This study investigated 168 tomato accessions collected across contrasting agroecological areas in Kajiado, Baringo, Laikipia and Kirinyaga to document variety distribution, farmer-recalled challenges, and biotic stressors. Using an open questionnaire alongside observations and fruit sampling, data were analysed through descriptive statistics, canonical variable analysis, principal component analysis and hierarchical clustering with Ward linkage. The geographic distribution of the collected samples comprised Kajiado at 41.1%, Kirinyaga/Laikipia at 32.1%, and Marigat at 26.8%. Among the reported variety categories, farmers relied heavily on two principal accessions, namely BIG ROCK (22.6%) and ANSAL (20.2%), which also had the highest numbers of reported stress incidences with 28 stress incidences each. Tuta absoluta was the most frequently reported stressor with 22 reports in the stated-pressure summary and 36 cumulative mentions in the variety-level matrix and formed a prominent column across nearly all commercial favourites. While farmers prioritised high yield (37.0%) and long shelf life (32.6%), a distinct difference in post-harvest characteristics was reported: SALA and BIG ROCK suffered from short shelf lives, whereas KILELE and STVE 8444 displayed soft fruit traits. Dendrogram-based clustering revealed that Kajiado and Kirinyaga/Laikipia share highly similar complex stress profiles, whereas Marigat stood out due to unique localized pressures such as frost, red mites and high soil salinity. This descriptive characterisation provides a crucial core collection and passport dataset, which may guide targeted crossing programmes, minimise pesticide misuse, and build climate-resilient tropical varieties.

Phenophase Specific Weather-Yield Relationships and Machine Learning Based Prediction of Alphonso Mango Across Contrasting Agroclimatic Regions of India

Tue, 10 Nov 2026 00:00:00 +0000

Understanding how weather conditions influence mango productivity at different developmental stages is essential for improving yield estimation across contrasting growing environments. This study investigated phenophase-specific weather–yield relationships and evaluated the integration of meteorological and satellite-derived variables for predicting Alphonso mango (Mangifera indica L.) yield across three major production regions of India. Field observations were conducted during the 2025-2026 growing season in 54 orchards distributed across Muthalamada, Kerala (15 orchards), Dharwad, Karnataka (17 orchards), and Konkan, Maharashtra (22 orchards), comprising 109 flowering cohort observations. Meteorological information from ERA5 Land was combined with vegetation, moisture and thermal indicators derived from Sentinel-2 and MODIS satellite observations. Pearson correlation analysis, with Benjamini–Hochberg false discovery rate adjustment, was used to examine relationships between six meteorological variables during six reproductive and fruit development stages and orchard yield. Six regression algorithms were evaluated across seven phenological feature sets using nested orchard-grouped cross-validation and independent testing. Weather–yield relationships varied considerably among regions and developmental stages. Inflorescence emergence showed prominent associations in Muthalamada, while flowering and early fruit development were particularly relevant in Dharwad. In Konkan, solar radiation during the marble-size fruit stage exhibited the strongest positive association with yield (r = 0.770), whereas relative humidity during inflorescence emergence showed the strongest negative association (r = −0.686). Among the 42 feature set model combinations, lasso regression using flowering stage predictors (Feature Set 3) achieved the highest predictive accuracy, with a cross-validation R² of 0.921 and RMSE of 0.334 t ha⁻¹. Independent testing yielded an R² of 0.890 and RMSE of 0.323 t ha⁻¹, with positive predictive performance across all three regions. The findings highlight the importance of developmental timing in weather-yield relationships and demonstrate the potential of integrating phenological, meteorological and remote-sensing information for Alphonso mango yield estimation.

Environmental Sustainability Assessment of Bioenergy Production Systems Using Advanced Life Cycle Modeling

B. Kailashkumar, S M Subhashini, V Priyadharshini, J Vishnupriya — Tue, 10 Nov 2026 00:00:00 +0000

The transition toward low-carbon energy systems has increased interest in bioenergy as a renewable alternative to fossil-based energy. However, the environmental performance of bioenergy production systems depends strongly on feedstock characteristics, land-use practices, conversion technologies, transportation requirements, energy inputs, coproduct allocation, and the treatment of biogenic carbon. Consequently, evaluating bioenergy sustainability requires a comprehensive life cycle perspective rather than considering only emissions occurring during energy conversion. This article presents an advanced life cycle assessment (LCA) framework for evaluating the environmental sustainability of bioenergy production systems using openLCA, an open-source LCA software platform. The proposed framework integrates feedstock cultivation or collection, preprocessing, transportation, conversion, energy generation, coproduct management, waste treatment, and end-of-life processes within a cradle-to-grave system boundary.

The methodology combines process-based life cycle inventory modelling with scenario analysis, sensitivity analysis, uncertainty assessment, and contribution analysis. Multiple impact categories, including global warming potential, cumulative energy demand, eutrophication, acidification, photochemical ozone formation, particulate matter formation, water consumption, and land-use impacts, can be evaluated to identify environmental trade-offs. Particular attention is given to methodological issues that substantially influence bioenergy LCA results, including system boundaries, functional units, allocation procedures, biogenic carbon accounting, soil carbon changes, indirect land-use change, and electricity-system assumptions. The article demonstrates how openLCA can be used to construct transparent and reproducible models for comparing alternative bioenergy pathways. The resulting framework can support technology selection, process optimisation, policy development, and the design of more resource-efficient and environmentally sustainable bioenergy systems.

Cropping Pattern Dynamics, Climatic Trends and Rice Water Use in Thiruvarur District, Tamil Nadu, India: An Economic Analysis

C. Aroutselvam, A. Pouchepparadjou — Wed, 11 Nov 2026 00:00:00 +0000

Rice-based agriculture in the lower Cauvery Delta is subject to climatic variability and water-management pressures. This study integrates district crop-area indices for 2013–2014 to 2023–2024, annual meteorological trend statistics, contextual vulnerability indicators, two seasonal rice-water scenarios and stochastic-frontier estimates for 120 rice farms in Thiruvarur district. The composite entropy index decreased from 0.409 to 0.118, with fluctuations and a pronounced decline in 2023–2024. A 10-state Markov matrix implies conditional stationary shares of 0.246 for cotton and 0.105 for rice, rather than observed crop substitutions. The minimum-temperature Sen slope was +0.0216 °C/year (nominal p = 0.0257), and the wind-speed slope was −0.0082 m/s/year (nominal p = 0.0020); after Holm adjustment for five tests, only wind speed remained significant at 0.05. Exposure, sensitivity and adaptive-capacity indicator means were 0.650, 0.750 and 0.475, but inconsistent score direction and absent validation preclude a district vulnerability classification. Using stated seasonal water depths, yields and nitrogen assumptions, green, blue-evapotranspiration and grey footprints were approximately 570, 593 and 205 m³/t for Kuruvai rice and 697, 558 and 212 m³/t for Samba rice. Their composite unweighted seasonal mean was 1,417 m³/t, not a measured district-wide footprint. The frontier's reported inefficiency variance fraction was 0.0031, although insufficient information is available for causal attribution. The illustrative gross-output-to-irrigation ratio was ₹10.19/m³. The findings characterise crop-area variability and conditional water-use indicators; independent validation of underlying time series and fitted models is still necessary.

Weather Associations and Disease Progression of Potato Late Blight under the Influence of Different Sowing Dates at Tarai Region of Uttarakhand

Aditi Maithani, Shailbala Sharma, Ayushi Chamoli, Tannu Rani — Wed, 11 Nov 2026 00:00:00 +0000

Aim: Potato late blight caused by Phytophthora infestans (Mont.) de Bary was analysed to assess the effects of sowing dates and the relationship between disease development and weather parameters in the 2023-24 potato season at the Vegetable Research Centre, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand.

Study Design: Disease severity was assessed across three sowing dates and two varieties, Kufri Bahar (V1) and Kufri Jyoti (V2), in a split-plot experiment with four replications

Place and Duration of Study: Vegetable Research Centre, G. B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, during the 2023-24 potato season.

Methodology: Disease severity was assessed visually using a 0–100% scoring scale (European and Mediterranean Plant Protection Organization,1989) under three sowing dates and two varieties, Kufri Bahar (V1) and Kufri Jyoti (V2), at seven-day intervals across five assessment dates, from 19^th December 2023 to 16^th January 2024. Weekly mean disease severity was correlated with weekly mean weather parameters (n = 5) during that season, followed by fitting of exponential, monomolecular, logistic and Gompertz growth models.

Results: On 16^th January, the mean disease severity was 58.72% for D1, 54.36% for D2 and 46.75% for D3. The mean disease severity of the two varieties was 59.65% for Kufri Bahar and 46.91% for Kufri Jyoti. Among the four disease-progress models, Gompertz had the highest reported R2 values, from 0.9965 to 0.9997, and the lowest Akaike information criterion (AICc) for all six treatment combinations. For the disease-weather relationship, disease severity was negatively correlated with maximum temperature (r = -0.978), sunshine hours (r = -0.968) and evaporation (r = -0.848). Minimum temperature (r = 0.436), morning relative humidity (r = 0.611), afternoon relative humidity (r = 0.906) and wind velocity (r = 0.995) showed positive correlations. These results are from a single season at one location and are descriptive.

Climate Variability Awareness and Vulnerability Status among Smallholder Crop Farmers in Kenya: Evidence from Kuria East Sub-county

Mwita Paul Chacha, George Makokha, Christopher Shisanya — Wed, 11 Nov 2026 00:00:00 +0000

This study examined the relationship between smallholder farmers’ awareness of climate variability and their level of vulnerability. A cross-sectional survey was conducted in Nyabasi East and Nyabasi West wards of Kuria East Sub-County, Migori County, Kenya, during 2025. A sample size of 361 smallholder farmers growing arable crops calculated using Cochran’s (1977) method was utilized. The study employed random sampling to select respondents. Awareness of climate variability was assessed based on the farmers’ reported knowledge and observations regarding indicators of climate variability and was then classified into three levels: low, moderate and high. The level of vulnerability was determined based on the number of climate-related impacts reported on agricultural activities, with farmers reporting at least three effects classified as highly vulnerable. A chi-squared test of independence was used to test the null hypothesis that there is no statistically significant association between farmers’ awareness of climate variability and their level of vulnerability. The descriptive results showed that the majority of farmers (65.1 per cent) demonstrated moderate awareness of climate variability while 29.1 per cent had low awareness and 5.8 per cent had high awareness. Cumulatively, 30.5 per cent of farmers were classified as highly vulnerable. The chi-squared test revealed no statistically significant association between awareness and the level of vulnerability; ^χ² (2, N = 361) = 4.65, p = 0.098, at a significance level of 0.05. This result indicates that awareness alone does not determine farmers’ levels of vulnerability, suggesting that other factors not measured in this study may also influence vulnerability. The study recommends that climate change adaptation policy in the study region go beyond awareness-raising campaigns and move towards integrated interventions that combine the dissemination of information with concrete institutional support.

Climate Change and Farmers’ Livelihood Status in the Semi-Arid Eastern Plain of Rajasthan, India

Thu, 12 Nov 2026 00:00:00 +0000

Background: Farming households in semi-arid Rajasthan depend substantially on rain-fed agriculture and are exposed to variations in temperature, rainfall and humidity. This study assessed farmers’ livelihood status and examined its relationship with climate-related and socio-economic variables in the Semi-arid Eastern Plain of Rajasthan.

Methods: Primary data were collected through structured interviews with 120 farmers from the Kekri and Sarwar blocks of Ajmer district and the Jobner and Sambhar Lake blocks of Jaipur district. Secondary temperature, rainfall and relative humidity records for 1992–2023 were obtained from the India Meteorological Department. A Livelihood Assessment Index (LAI) was developed using five dimensions of the Sustainable Livelihood Framework: human, natural, social, physical and financial capital. Descriptive statistics and multiple linear regression were used for analysis.

Results: The study reported an overall LAI of 0.7976, with a higher score in Ajmer (0.8175) than in Jaipur (0.7778). Human and natural capital were relatively strong, whereas financial capital was the weakest dimension. Temperature change, rainfall pattern and humidity levels had statistically significant negative regression coefficients. Livestock ownership showed a small positive coefficient, with a p-value of 0.0505.

Conclusion: The findings indicate differences in livelihood resources between the two districts and associations between climate-related variables and livelihood status. Water conservation, livestock support, improved access to formal credit and strengthened agricultural extension services are relevant adaptation priorities.

From the Return of Water to Composite Risk: Hazards, Damage and Vulnerability in the Southern Korama Valley (Zinder, Niger)

Fri, 13 Nov 2026 00:00:00 +0000

Background: The southern Korama Valley of Niger is an endorheic basin where the accumulation and persistence of surface water in interdunal depressions create challenges for rural communities. The interaction of groundwater rise, prolonged flooding and seasonal salt concentration poses potential risks to agricultural production, household infrastructure, vegetation and local livelihoods. Understanding these interconnected hazards is essential for assessing the spatial distribution of damage and socio-economic vulnerability in the affected communes.

Aims: To show that the return of rainfall in the endorheic southern Korama valley produces a composite risk of linked climate, hydrological and hydrochemical hazards acting on vulnerable households.

Study Design: Mixed-methods case study combining climate series, remote sensing, groundwater records, in situ water measurements, a household survey and focus groups.

Place and Duration of Study: Rural communes of Kwaya, Bandé and Dungass, Zinder Region, Niger; fieldwork from September 2024 to April 2026.

Methodology: We analysed rainfall (1950-2024) and temperature (1994-2024) records at Magaria using the Mann-Kendall, Sen and Pettitt tests; Landsat classifications (1975-2025); a Sentinel-1/2 inventory of cuvettes (2020-2025); groundwater records from 23 piezometers (2014-2023); electrical conductivity (EC) and pH measurements at 20 cuvettes in January and April 2026, summarised using a salinisation risk index mapped for each cuvette; a survey of 293 households; and a count of 504 woody plants. A socio-economic vulnerability index (SVI) was computed by commune.

Results: Annual rainfall showed no significant trend (P = .65), but six of the seven seasons from 2018 to 2024 were in surplus and minimum temperature rose by 0.63 °C per decade (P < .001). Water surfaces rose from 847 ha (2000) to 5,223 ha (2025). The water table was less than 2.6 m deep at 8 of 12 piezometers and rose at 4. Mean EC doubled between January and April (from 2.2 to 4.4 dS/m) and exceeded 5 dS/m in seven cuvettes, all in Bandé, while groundwater EC stayed at 0.12 dS/m. Overall, 95% of households reported at least one building collapse, 97% reported crop losses, and 15.5% had sold a field; 45% of woody plants were dead. Dungass had the highest SVI (0.61).

Conclusion: The risk works as a chain from rainfall to land loss. It is mainly perceived in Kwaya, contrasted and dynamic in Bandé and moderate in Dungass, calling for groundwater and water-quality monitoring and household-level measures.

Calibration and Validation of the CERES-Wheat Crop Simulation Model for Phenology, Leaf Area Dynamics and Yield of Wheat (Triticum aestivum L.) under Varying Sowing Dates, Irrigation Schedules and Nitrogen Levels in a Subtropical Agro-Ecosystem of the Vin

Wasim Khan, Rajesh Singh, Shraddha Rawat — Fri, 13 Nov 2026 00:00:00 +0000

Aims: To calibrate and validate the CERES-Wheat model of the Decision Support System for Agrotechnology Transfer (DSSAT v4.7) to simulate phenology, leaf area index (LAI), grain yield and biological yield of wheat (Triticum aestivum L.) cultivar HD 2967 under varying sowing dates, irrigation schedules and nitrogen levels.

Study Design: Split-plot field experiment with three replications and 18 treatment combinations of sowing date (main plot), irrigation and nitrogen.

Place and Duration of Study: Crop Research Farm, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, Uttar Pradesh, India, during the rabi (winter) seasons of 2019–20 and 2020–21.

Methodology: Wheat was sown on 20 November and 20 December, with two, three or four irrigations and nitrogen rates of 80, 120 or 160 kg N ha⁻¹. Genetic coefficients were calibrated using 2019–20 data and validated against data from an independent season (2020–21) using mean bias error (MBE), root mean square error (RMSE), normalised RMSE (nRMSE), and Willmott’s index of agreement (d-stat).

Results: Anthesis and maturity were simulated with nRMSE below 6% in both seasons, although maturity was predicted 3.5–7.5 days early in the warmer 2020–21 season. Grain yield was simulated with acceptable accuracy in calibration (nRMSE 1.9–20.4%) but less accurately in validation (6.7–27.6%), when it was overpredicted under timely sowing. The model underestimated biological yield in both seasons (nRMSE 6.7–31.0% and 14.2–28.6% in calibration and validation, respectively), and harvest index was overestimated. Maximum LAI was underestimated in calibration (nRMSE 21.2–40.8%) but was simulated accurately in validation (11.1–14.0%).

Conclusion: The calibrated genetic coefficients captured the phenology and grain-yield levels of HD 2967 reasonably well, but the underestimation of biomass and canopy growth and the early maturity in the warmer season show that they need refinement with multi-season data before the model is used for management optimisation or yield forecasting in the Vindhyan zone.

Spatiotemporal Weather Variability Modelling for Mango Yield Forecasting Using Machine Learning Techniques

P. Jona Innisai Rani, K. R. Rajadurai, M. Radha, C. Hemabharathi — Sat, 14 Nov 2026 00:00:00 +0000

This study developed and evaluated a machine-learning framework for forecasting mango yield in two mango-growing areas of Tamil Nadu, India: Periyakulam (Theni district) and Krishnagiri district. Annual rainfall, minimum and maximum temperature, relative humidity and mango-yield observations were compiled for 2010–2023 in Periyakulam and 2015–2023 in Krishnagiri. The resulting dataset included 114 district–variety–year observations covering six mango varieties. Descriptive assessments of inter-annual weather variability were combined with Pearson correlation analysis, analysis of variance (ANOVA) and a lightweight one-dimensional convolutional neural network (1D-CNN) regression model. Model performance was assessed using a 70:30 training–validation split and five-fold cross-validation, with Random Forest, Support Vector Regression and multiple linear regression as comparators. Yield differed significantly among varieties (F = 10.465, p < 0.001), whereas the district main effect was not significant (F = 0.406, p = 0.525). Validation root mean square error (RMSE) ranged from 3.12 to 3.94 kg/tree in Periyakulam and from 2.98 to 4.01 kg/tree in Krishnagiri. Across the two districts, validation correlations ranged from 88.65% to 95.64%. In the reported cross-validation comparison, the 1D-CNN yielded an RMSE of 3.42 kg/tree and a correlation of 91.8%, outperforming the baseline models. These findings suggest potential for weather-informed, district- and variety-specific mango-yield forecasting, although broader temporal and geographical validation is required.

Impact of Global Warming on Black Flies Ecology: A Growing Threat to Exposed Populations in an Epidemiological Facies of Onchocerciasis in Côte d’Ivoire

Fri, 06 Nov 2026 00:00:00 +0000

Global warming may influence blackfly ecology by changing the environmental conditions that affect aquatic development and adult activity. This study assessed local bioecological conditions associated with blackfly abundance and daily biting activity in the Touba Department, northern Côte d’Ivoire. During three consecutive days in December 2023, adult female blackflies were collected using human bait and haemolysis tubes at two locations: the Bagbê River bridge and an agricultural field 10 km from the river. Microclimatic conditions and selected physicochemical properties of river water were recorded. Of 801 blackflies collected, 582 were captured at the field site and 219 at the bridge site. Morphological identification assigned 794 specimens to the savannah group and seven to the forest group of the Simulium damnosum complex. Hourly biting activity increased after noon at both sites and peaked between 3 and 4 p.m. The highest recorded hourly biting rate was 120 bites per person at the field site. Mean air temperatures were similar at the field and bridge sites, with no statistically significant difference (p = 0.917). The reported analyses indicated negative associations of turbidity and conductivity with blackfly density density (p = ˂ 0.01; R2 = - 0.859), whereas water temperature showed a positive association (p = 0.02; R2 = 0.684). These observations indicate substantial human exposure to blackfly bites during the sampling period. Continued entomological and environmental surveillance is warranted, although the findings do not establish a long-term effect of global warming or confirm ongoing parasite transmission.

Regenerative Agriculture in Tea Systems: A Review of Soil Degradation, Nutrient Management, Climate Risk and the Role of Certification-Based Implementation, with Evidence from India

Antara Bera, Rajesh Bhuyan — Fri, 30 Oct 2026 00:00:00 +0000

Tea (Camellia sinensis (L.) Kuntze) is a long-lived perennial crop subject to climate variability, soil degradation and the environmental consequences of intensive nutrient use. This critical narrative review synthesises evidence on climatic constraints to tea production, soil acidification and carbon dynamics, nitrogen management and greenhouse-gas emissions, and the relevance of regenerative agriculture and voluntary sustainability standards to Indian tea systems. Published studies indicate that prolonged high nitrogen inputs can intensify soil acidification and nitrogen losses, although agronomically appropriate rates differ with site conditions, yield targets and tea type. Tea soils can be substantial sources of nitrous oxide, while the relative contributions of field activities and factory processing depend on the carbon-accounting boundary. Organic amendments, diversified vegetation management and more efficient fertilisation may improve particular soil indicators, but long-term replicated evidence for integrated regenerative packages in Indian tea remains limited. As an illustrative, non-experimental case, monitoring summaries from an Indian tea regenerative agriculture (REGEN) programme are considered. The programme reports a mean baseline soil organic carbon concentration of 1.06%, pH of 4.73, made-tea yield of 1,828 kg ha⁻¹ and synthetic nitrogen application of 131.8 kg N ha⁻¹. Its operator-reported early summaries indicate relative changes of more than 5% in soil organic carbon, 18% in culturable microbial counts, 3% in productivity, −15% in synthetic nitrogen and approximately −21% in field/source-point greenhouse-gas emission intensity. These figures lack documented matched-cohort denominators, uncertainty estimates and independent verification, and cannot establish effects attributable to the programme. The principal research priority is longitudinal, independently assessed measurement of soil carbon stocks, nitrogen balances, productivity and emissions under comparable field and factory boundaries.

Leaf Colour Chart–guided Nitrogen Management in Cereal Systems: Yield, Efficiency and Sustainability

Mon, 02 Nov 2026 00:00:00 +0000

Nitrogen fertilisation is essential for cereal production, but fixed rates and schedules frequently fail to reflect field-to-field variation in indigenous soil supply and crop demand. The leaf colour chart (LCC) is a low-cost, visually interpreted proxy for crop nitrogen status that can guide in-season fertiliser application without specialised electronic equipment. This critical narrative review examines physiological validity, chart calibration, field performance in rice, wheat and maize, nitrogen-use efficiency, environmental effects, adoption constraints and digital extensions. Peer-reviewed experimental and contextual evidence was critically compared according to crop and genotype, chart threshold, dose per application, baseline management, study design and outcome measurement. The most consistent findings support the ability of locally calibrated chart rules to adjust nitrogen topdressing and, in systems where conventional practice oversupplies fertiliser, preserve yield with reduced input. Results are less uniform across cereal species, cultivars and establishment methods. Maximum grain yield, highest nitrogen-use efficiency and largest economic return often occur at different threshold-and-dose combinations. Chart colour is affected by leaf morphology and non-nitrogen stresses, creating a risk of incorrect fertiliser recommendations if interpreted in isolation. A smaller evidence base supports reductions in directly measured environmental losses under specific management conditions; changes in applied nitrogen alone do not demonstrate lower greenhouse-gas emissions or leaching. On-farm implementation requires consistent sampling, viable labour arrangements and locally trusted advice, while digital colour analysis requires independent validation of both measurement and fertiliser decisions. The review identifies priority needs for external threshold testing, dose-matched comparisons, long-term soil and nutrient balances, direct environmental monitoring and prospective farmer-adoption studies. Leaf colour charts offer a practical contribution to evidence-based nitrogen stewardship when treated as calibrated decision aids rather than universal predictors of sustainable yield gains.

LED Lighting in Greenhouse Floriculture: A Critical Review of Photobiology, Spectral Optimisation, Energy Dynamics and Climate-Smart Cultivation

Tue, 03 Nov 2026 00:00:00 +0000

Light-emitting diode (LED) technology has expanded the possibilities for manipulating floral induction, plant architecture, ornamental quality and resource use in protected floriculture. Yet improvements demonstrated under controlled spectra do not necessarily translate into commercially valuable gains under variable greenhouse sunlight, nor does higher electrical efficacy automatically reduce whole-greenhouse energy demand. This critical narrative review synthesises physiological, crop-production and engineering evidence relating to supplemental and photoperiodic LED lighting, with particular attention to cut roses, chrysanthemums, gerbera and bedding ornamentals. Relevant peer-reviewed literature and methodological sources were identified through targeted searches of accessible scholarly indexes and reference tracing, with a literature cut-off of 23 August 2026. The evidence supports distinct, interacting roles for radiation quantity, spectral composition, timing and photoperiod. Red-rich spectra can favour cut-rose productivity in particular cultivar and greenhouse settings, but there is no universally optimal red-to-blue ratio. Far-red and blue radiation regulate elongation and flowering in ways strongly conditioned by photoperiodic category, baseline sunlight, developmental stage and the absolute flux of other wavelengths. Changes in the daily light integral frequently account for apparent spectral benefits, whereas flowering responses to low-intensity night interruption need not involve substantial photosynthetic energy. Greenhouse energy models show that replacement of high-pressure sodium lamps with LEDs can reduce lighting electricity while increasing heating requirements because less useful heat is emitted by the lamps. This distinction complicates claims of cost, carbon and energy savings. The review proposes a decision framework that separates photobiological effects from photon-dose effects and evaluates crop quality, timing, energy, heating, water and postharvest performance within explicit environmental and economic boundaries. Priority is given to sunlight-aware multi-factor trials, independent replication, dynamic controls and transparent, whole-system accounting. LEDs are best understood as flexible control tools rather than intrinsically climate-smart inputs; their net contribution depends on crop, climate, management and system design.

Environmental Justice in the Sustainable Development Goal Era: Inclusive and Transformative Policy Architectures

Roshan Baa — Tue, 03 Nov 2026 00:00:00 +0000

The Sustainable Development Goals (SDGs) place social inclusion and ecological protection within a shared international agenda, yet aggregate progress indicators can obscure unequal exposure to environmental harm, unequal access to benefits and unequal influence over decisions. This critical narrative review examines how environmental justice can be made operational across interconnected policies for pollution control, climate adaptation, energy transition, conservation and development. Literature published principally from 2015 to 23 August 2026 was interpreted alongside foundational scholarship and authoritative institutional instruments. The synthesis distinguishes distributive, procedural, recognitional, restorative and intergenerational dimensions of justice; critically compares empirical evidence across urban and rural settings; and assesses whether policy architectures create enforceable duties rather than merely participatory aspirations. Evidence consistently documents patterned disparities in air pollution, heat exposure and environmental decision-making, although geographical coverage, exposure measurement and causal identification remain uneven. Climate and conservation interventions can reduce aggregate environmental pressures while displacing costs towards marginalised communities, particularly where land tenure, affordable housing, labour protections or effective remedies are weak. SDG interactions therefore cannot be assumed to be uniformly beneficial: apparently successful sectoral programmes may produce inequitable outcomes across places, groups or generations. The review proposes an integrated architecture linking disaggregated diagnostics, meaningful decision-making authority, enforceable safeguards, distributive fiscal choices, remedy mechanisms and independent evaluation. This proposal is an analytical synthesis, not a validated universal model. Priority research needs include longitudinal causal evaluations, community-defined indicators, stronger evidence from underrepresented regions and comparative tests of policy enforcement. Environmental justice in the SDG era is best understood as an assessable property of institutions, distributional outcomes and power relations, rather than a descriptive label attached to environmental programmes.

From Root Recruitment to Systemic Drought Tolerance: A Mechanistic Review of Endophyte–Plant Interactions

Smriti Dhruw, Sandhya Sahu, Jayesh Shesh — Thu, 05 Nov 2026 00:00:00 +0000

Drought tolerance depends on coordinated adjustments in root water relations, metabolism, hormonal signalling, redox homeostasis and shoot physiology. Endophytic microorganisms can influence these processes, yet the links between microbial recruitment, internal root establishment and systemic drought adaptation remain incompletely resolved. This review synthesises evidence concerning the proposed sequence from drought-induced changes in root physiology and exudation to microbial attraction, attachment, root entry, endophytic colonisation, host signalling and whole-plant responses. Root exudates may affect microbial chemotaxis, motility and biofilm formation, whereas successful entry can depend on developmental root zones, microbial motility and modification of cell-wall barriers. Internal establishment also requires interactions with host immune regulation and signalling pathways associated with calcium, reactive oxygen species and abscisic acid. Evidence from experimentally studied endophytes, particularly Piriformospora indica, links local root colonisation with changes in distal-root responses, drought-associated gene expression, antioxidant protection, osmotic adjustment and photosynthetic performance. However, microbial association at the root surface does not establish internal colonisation, and improved physiological performance does not identify a particular long-distance signal. The available evidence supports a framework in which endophytes modify endogenous plant signalling and physiological processes, with potential systemic consequences under water deficit. Direct causal links among recruitment, internal establishment and root-to-shoot signalling remain insufficiently resolved. Further research integrating spatially verified colonisation with temporal signalling measurements and realistic drought treatments is needed to test this proposed continuum.

Micro-Irrigation in Rice (Oryza sativa L.): A Review of Advances, Challenges and Future Prospects

Thu, 05 Nov 2026 00:00:00 +0000

Rice (Oryza sativa L.) is a major staple crop, but continuous flooding in conventional production systems requires substantial irrigation water and can contribute to greenhouse gas emissions. This narrative review examines the applicability of micro-irrigation technologies in rice cultivation, focusing on surface drip, subsurface drip, sprinkler and micro-sprinkler systems. It also considers rice establishment methods, irrigation scheduling, crop performance, water productivity, nutrient management, environmental effects and economic feasibility. The reviewed literature indicates that controlled irrigation may reduce irrigation water use under suitable conditions, although effects on grain yield and water productivity differ according to soil characteristics, climate, crop establishment and scheduling. Approaches based on irrigation water-to-cumulative pan evaporation ratios, soil moisture thresholds and sensors may support more precise water application. Fertigation and leaf-based nitrogen management tools may further assist nutrient supply when appropriately calibrated. Reduced periods of soil saturation may lower methane emissions, but environmental effects require assessment alongside other greenhouse gases and local management conditions. Adoption is constrained by installation and maintenance costs, potential emitter clogging, energy requirements and limited technical support. Major research needs include longer-term field studies, region-specific irrigation recommendations and economic assessment for smallholder farmers. Nanobubble technology and automated scheduling warrant further field evaluation. Overall, micro-irrigation may improve water productivity in suitable rice systems, but its effectiveness and practicality cannot be generalised across all production environments.

Smart Irrigation through Automated Alternate Wetting and Drying for Sustainable Paddy Ecosystems

A. P. Archana, S. Sajeena — Fri, 06 Nov 2026 00:00:00 +0000

Rice (Oryza sativa L.) is a major staple food crop worldwide, particularly in Asia, where its cultivation plays an important role in food security and agricultural livelihoods. However, conventional continuous flooding requires considerable irrigation water and promotes methane emissions from paddy soils. Alternate Wetting and Drying (AWD) is a water-saving irrigation technique that reduces unnecessary water application by allowing the field to dry periodically before re-irrigation. Although AWD can improve water-use efficiency and reduce greenhouse gas emissions, its manual implementation requires regular field monitoring and timely irrigation. Automated Alternate Wetting and Drying (AAWD) offers a promising solution by integrating sensors, microcontrollers, Internet of Things (IoT) technology and automated pumping systems to regulate irrigation according to predetermined water-level thresholds. This review examines the principles of paddy water management, irrigation requirements, AWD practices, sensor-based monitoring technologies and automation strategies for sustainable rice cultivation. It also discusses the effects of AWD and AAWD on irrigation water use, crop productivity, water-use efficiency and greenhouse gas emissions, particularly methane (CH₄) and nitrous oxide (N₂O). Previous studies have demonstrated that AWD can substantially reduce irrigation water consumption and methane emissions while generally maintaining rice yield under appropriate management conditions. However, excessive soil drying, variations in soil properties, increased nitrous oxide emissions, equipment costs and unreliable water supplies may limit its effectiveness. Sensor-based automation can improve irrigation precision, reduce labour requirements and support consistent implementation of AWD. The review highlights the potential of AAWD to promote efficient water management, maintain crop productivity and reduce the environmental impacts of paddy cultivation. Further research is required to improve system affordability, field-level reliability and adaptability under different agroclimatic conditions.

Apis cerana indica as Integrative Bioindicator of Environmental Pollution

K. Kirubhavathy, V. S. Amritha — Wed, 11 Nov 2026 00:00:00 +0000

Environmental pollution is spatially heterogeneous and temporally dynamic, creating a need for monitoring approaches that capture both contaminant concentrations and their biological availability. Honey bees offer such an integrative approach because repeated foraging connects colonies to vegetation, soil, water and atmospheric compartments across the surrounding landscape, and contaminants they encounter may be transported and redistributed among bees and hive products.

This review evaluates the potential of honey bees, with particular emphasis on the indigenous Apis cerana indica, as integrative environmental bioindicators. It develops a framework linking landscape structure, floral resources, foraging behaviour, contaminant exposure, accumulation in hive matrices and colony-level responses.

Pesticides, heavy metals and trace elements, industrial and traffic emissions, biomass-burning products and soil-derived contaminants may reach bees through multiple pathways. Detection alone, however, does not establish source, dose or biological effect; brood development, food storage, foraging activity, hive weight and temperature provide complementary evidence of stress, and interpretation is strengthened when these are linked with landscape, floral composition, weather and colony condition.

Analytical reliability depends on representative sampling, matrix-specific extraction, appropriate instrumental analysis, quality assurance and careful treatment of detection limits and background concentrations. Most evidence comes from Apis mellifera, whereas species-specific baselines, exposure kinetics and biological thresholds remain limited for A. cerana indica. Repeated, landscape-stratified, multi-matrix monitoring supported by melissopalynology, environmental reference measurements and standardized colony observations could establish this species as a regionally relevant biomonitor across heterogeneous South Asian landscapes.

Seed Priming in Chickpea (Cicer arietinum L.): A Review of Physiological and Biochemical Mechanisms, Stress Tolerance and Crop Productivity

Lokesh Kumar, Sucheta Dahiya, Mohinder Singh, Om Pal Singh Khola — Wed, 11 Nov 2026 00:00:00 +0000

Chickpea (Cicer arietinum L.) is an important pulse crop with a major role in food and nutritional security, particularly in semi-arid regions where water availability and soil fertility often limit crop productivity. Improving crop establishment at the early growth stage is therefore essential for achieving stable yields under both normal and stressful growing conditions. Seed priming is a simple and relatively low-cost technique that can improve the physiological performance of seeds before sowing. The present review discusses the role of seed priming in improving germination, seedling establishment, growth, yield and stress tolerance in chickpea, with emphasis on the underlying physiological and biochemical processes. Priming treatments such as hydropriming, osmopriming, halopriming, biopriming, nutrient priming, hormonal priming, nanopriming, on-farm priming and matrix priming have been discussed. Controlled hydration during priming activates important metabolic processes before germination, including membrane repair, respiration, enzyme activation and mobilization of stored food reserves. Increased activity of enzymes such as α-amylase, protease and dehydrogenase supports rapid energy supply and early seedling growth, while enhanced antioxidant activity helps reduce oxidative damage under stressful conditions. Different priming approaches have also been reported to improve germination uniformity, seedling vigour, root development, nutrient uptake, nodulation and crop establishment. The benefits are particularly relevant under drought, salinity, delayed sowing and other marginal growing conditions. Overall, seed priming offers a practical approach for strengthening early crop establishment and improving the resilience and productivity of chickpea. Its simplicity, relatively low input requirement and compatibility with sustainable farming practices make it a promising component of climate-resilient chickpea production.