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Agro-based pulp and paper mills in India are one of the most polluting industries; in addition, they are high consumers of raw water. Growing scarcity of high quality freshwater as well as stringent regulatory standards is compelling these units to explore appropriate water management options. Based on data obtained through a questionnaire survey and plant visits, this work provides an overview of the water use and effluent treatment status in Indian agro-residue and recycled pulp and paper mills. The challenges faced by this sector are reviewed and practices adopted by progressive units to minimize freshwater use are illustrated through case studies.

Agricultural transformation in Punjab, spurred by the Green Revolution of the mid-1960s, has led to significant shifts in land use patterns, crop diversification, and cropping dynamics. This transformation has profound implications for sustainability and economic resilience. This study delves into the complex relationship among agricultural growth, instability, and environmental sustainability in Punjab. It examines the growth and instability in the state's key crops' area, production, and yield/productivity over 56 years, from 1966-1967 to 2021-2022. Using secondary data, this study employs an assortment of methodologies, including compound annual growth rate, simple linear regression, diversity indices such as the Herfindahl index and Simpson diversity index, instability analysis, and decomposition analysis. The results indicate an increase in cropping intensity, indicating agricultural intensification, with a shift towards wheat and rice monoculture from once diverse cropping patterns. The instability analysis reveals that wheat and rice emerge as the most stable crops in their area, production, and yield, while others exhibit instability, raising concerns about diminishing crop diversity and its implications for Punjab's natural resources. The study emphasizes the urgent necessity for sustainable agricultural practices and policies to counteract monoculture's adverse effects and ensure long-term agricultural resilience., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The study attempted to evaluate the agricultural soil quality using the Soil Quality Index (SQI) model in two Community Development Blocks, Ausgram-II and Memari-II of Purba Bardhaman District. Total 104 soil samples were collected (0-20 cm depth) from each Block to analyse 13 parameters (bulk density, soil porosity, soil aggregate stability, water holding capacity, infiltration rate, available nitrogen, available phosphorous, available potassium, soil pH, soil organic carbon, electrical conductivity, soil respiration and microbial biomass carbon) in this study. The Integrated Quality Index (IQI) was applied using the weighted additive approach and non-linear scoring technique to retain the Minimum Data Set (MDS). Principal Component Analysis (PCA) identified that SAS, BD, available K, pH, available N, and available P were the key contributing parameters to SQI in Ausgram-II. In contrast, WHC, SR, available N, pH, and SAS contributed the most to SQI in Memari-II. Results revealed that Ausgram-II (0.97) is notably higher SQI than Memari-II (0.69). In Ausgram-II, 99.72% of agricultural lands showed very high SQI (Grade I), whereas, in Memari-II, 49.95% of lands exhibited a moderate SQI (Grade III) and 49.90% showed a high SQI (Grade II). Sustainable Yield Index (SYI), Sensitivity Index (SI) and Efficiency Ratio (ER) were used to validate the SQIs. A positive correlation was observed between SQI and paddy ( R 2  = 0.82 & 0.72) and potato yield (R 2  = 0.71 & 0.78) in Ausgram-II and Memari-II Block, respectively. This study could evaluate the agricultural soil quality and provide insights for decision-making in fertiliser management practices to promote agricultural sustainability., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Population in South Asia is increasing ever than a faster rate, subsequently; food security, climate change, and capital intensive agro farming techniques are the prevailing challenges in this region. This is a tri-country penal analysis, Pakistan, India, and Bangladesh, and the study covers the data throughout (1973-2020). This study has used modern farm input data besides demographic variables in the study. In this study, we use panel data set, ARDL (PMG) approach, autoregressive distributed lag model pooled mean group, which is an extensively dynamic modeling technique for heterogeneous data. The results of the study explore that transition in the demographic pattern in Pakistan, India, and Bangladesh is the real cause of low crop productivity and land intensification. Technology innovation is the only ray of hope to fulfill the food demand of the future ahead and climate agriculture practices can hamper the further deterioration of the small farmlands., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Our study aimed to assess the soil quality in Punjab's Hoshiarpur district through a meticulous analysis of nutrient and elemental composition. Using a variety of analytical techniques, including Neutron Activation Analysis (NAA), external Particle-induced Gamma-ray Emission (PIGE) an Ion beam analysis Technique, and energy-dispersive X-ray fluorescence (ED-XRF), we delved into soil characterization for 22 agricultural soil samples in the Punjab region. Within the NAA framework, utilizing the Pneumatic Carrier Facility and the self-serve facility at Dhruva reactor in Mumbai, a brief 1-min irradiation procedure identified pivotal elements-Na, Mg, V, Al, Mn, and K. Conversely, an extended neutron irradiation process of approximately 4 h within the self-serve facility enabled the estimation of nearly 12 elements, including Rare Earth Elements (REEs), Transition elements, and other significant elements. The external PIGE technique quantified low Z elements (Na, Mg, Al, and Si), contributing to our analytical arsenal. Rigorously validating both NAA and PIGE methodologies, we compared results meticulously against established geological standard reference materials-specifically USGS RGM-1 and USGS AGV-1.Instrumental in elemental analysis, ED-XRF spectroscopy fortified our investigative endeavors by quick assessment of ten crucial elements. The elemental analysis revealed notable accumulations of Mn and Zn in the soil, surpassing the suggested permissible limits, whereas Co, Cr, and Pb were found to be within the recommended thresholds set by WHO/UNEP. Beyond elemental profiling, our study extended to estimate the accumulation levels of various elements utilizing ecological risk factors such as Contamination Factor, Potential Ecological Risk Index, Pollution Load Index, and Geoaccumulation Factor. Our findings highlighted significant accumulation of REEs including La, Sm and Yb.. This evaluation sheds new light on the interplay between soil composition and environmental health, emphasizing the need for advanced accessible agricultural technologies to prevent and forecast contaminant discharge in arable soil. This commitment aligns with our broader goal of advancing sustainable practices in soil management., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Actinomycetes are a suitable microbial group for the synthesis of lignocellulose-degrading enzymes. Enzymes that may degrade organic material, including cellulose, hemicellulose, and lignin, are released by actinomycetes. The aim of this research was to isolate actinomycetes from Rajkot, Gujarat, India’s soil and evaluate the activity of their cellulase and Xylanase enzymes. Starch Casein Agar (SCA) was used to identify a total of 30 isolates of actinomycetes. A qualitative plate assay (CMC-Na, Congo red) revealed that the highest zone of catalysis for MMD1 was 36 mm. Five strains were discovered to be effective for quantitative quantification of endoglucanase utilising filter paper and CMC as substrates: MMD1, MMD2, MMD3, MMD4, and MMD8. Following MMD 1 (endoglucanase 5.4 IU; FPase 4.4 IU), MMD 2 (endoglucanase 4.5 IU; FPase 3.4 IU) has demonstrated considerable endoglucanase and FPase activity. Beechwood xylan was used to treat sugarcane bagasse in order to test Xylanase, and 45% of the xylan (hemicellulose) fraction was obtained. MMD1 and MMD2 measured the xylanase enzyme activity (4.8IU and 4.2IU) in quantitative and qualitative assays (34 mm and 22 mm for BWX and 32 mm and 14 mm for agro-waste xylan). The strain MMD1 was identified as Streptomyces chartreusis through morphological, biochemical, and finally molecular characterization by 16S rRNA sequencing. It was then submitted to NCBI GenBank with the accession number MT254830. [ABSTRACT FROM AUTHOR]

Flash floods in mountainous regions like the Himalayas are considered to be common natural calamities. Their consequences often are more dangerous than any flood event in the plains. These hazards not only put human lives at threat but also cause economic deflation due to the loss of lands, properties, and agricultural production. Hence, assessing the impact of such hazards in the existing agricultural system is of utmost importance to understand the probable crop loss. In this paper, we studied the efficiency of the remotely sensed microwave data to map the croplands affected by the flash flood that occurred in July 2023 in Himachal Pradesh, a mountainous state in the Indian Himalayan Region. The Una, Hamirpur, Kangra, and Sirmaur districts were identified as the most affected areas, with about 9%, 6%, 5.74%, and 3.61% of the respective districts' total geographical area under flood. Further, four machine learning algorithms (random forest, support vector regressor, k-nearest neighbor, and extreme gradient boosting) were evaluated to forecast maize and rice crop production and potential loss during the Kharif season in 2023. A regression algorithm with ten predictor variables consisting of the cropland area, two vegetation indices, and seven climatic parameters was applied to forecast the maize and rice production in the state. Amongst the four algorithms, random forest showed outstanding performance compared to others. The random forest regressor estimated the production of maize and rice with R 2 more than 0.8 in most districts. The mean absolute error and the root mean squared error obtained from the random forest regressor were also minimal compared to the others. The maximum production loss of maize is estimated for Solan (54.13%), followed by Una (11.06%), and of rice in Kangra (19.1%), Una (18.8%) and Kinnaur (18.5%) districts. This indicated the utility of the proposed approach for a quick in-season forecast on crop production loss due to climatic hazards., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Uncertainty and uneven distribution of monsoonal rainfall and its consequences on crop production is a matter of serious concern in India, specifically, in the Indo-Gangetic plain region. In this study, drought patterns were investigated through standardised precipitation index (SPI) of varying timescales, using the India Meteorological Department (IMD) precipitation data (1901-2021). We analysed the spatio-temporal pattern of different drought characteristics (frequency, duration, severity, intensity) of the Indian Gangetic basin using run theory. The bivariate copula method has been incorporated to combine two drought properties (severity and duration). Copula integrates multivariate distribution and considers the dependency rate among the variables. The five most widely used copulas from various copula families, elliptical (normal, t-copula) and Archimedean (Clayton, Gumbel, Frank), were estimated for modelling, and the best fit copula was selected. The study revealed that seasonal drought is more frequent and intense in the Upper and Middle Gangetic Plain, whereas annual drought is quite scattered in nature. It is worthy to mention that downward drought trends were observed in this agricultural belts significantly after 1965; specifically, in the Upper, Middle, and Trans Gangetic Plain regions. With increasing drought duration and severity, the drought return period raised, but the frequency decreased gradually. Most of the droughts characterised by less duration and severity occurred with a return period below 10 years for the whole region. The major 100 + years return period droughts were to be found after 1960 and their frequencies were significantly higher after 2000. The most recent remarkable droughts with more than 100 years of return occurred during 2008-2011 and 2016-2018 in the Upper and Middle Gangetic plains, whereas in the Lower Gangetic plain, a hundred-year return period drought was occurred during 2010-2013. This study provides agroclimatic-zones-wise significant information of drought characteristics and its nature of occurrence in the Indian Ganga Basin. The results enhance the understanding of drought management and formulation of adaptive strategies to mitigate the adverse impact of droughts., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Climate-induced extreme events with fluctuations in climatic indicators like temperature and precipitation highly influence crop productivity. This study deals with quantitative analysis of climatic variability and crop production (1990-2018) using panel data regression analysis. The focus is on variability of three crops, i.e., paddy, maize, and wheat in the Rangit river basin of Sikkim Himalaya, India. Meterological data were acquired from the Indian Meteorological Department, agricultural data from the state agricultural department and a field survey were also conducted with the farmers, using a structured questionnaire, focused group discussion, and key informant observations. The acquired data was analyzed with the help of correlation and multiple linear regression analysis to analyze the relationship between climatic variability and crop production. The result of the study shows that all three crops are dependent on rainfall; however, paddy was the most sensitive to climatic variability. It was found that the overall grain production had an inverse relation to temperature, but it had a positive correlation with rainfall. It was observed that there was a continuous decline in the overall production of paddy and wheat. During deficiency years, it was found that when - 11.33% rainfall was deficient, paddy yield declined by - 1.52%. Further, a deviation of - 13.48% led to a decline of - 54.78% in wheat. The study advocates that timely policy interventions and strategies shall reduce climatic shocks and improve productivity. This would strengthen the livelihood security of the local communities, overcome the challenges of food security, and ensure long-term sustainability of Rangit River basin., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Background: A simulation study was performed for assessing climate change impact on maize under Representative Concentration Pathways (RCPs 2.6 and 8.5) for Punjab, India. The study area comprised five agroclimatic zones (AZs) including seven locations. The bias corrected temperature and rainfall data from four models (CSIRO-Mk-3-6-0, FIO-ESM, IPSL-CM5A-MR and Ensemble) were used as input in CERES-Maize model which was run with constant management practices for two Punjab maize hybrids (PMH 1 and PMH 2). The maize yield for upcoming 70 years (2025-2095) was simulated and its deviations from the baseline (2010-2021) yield were computed under optimized sowing (early-May to early-July) and current sowing (end-May to end-June) period., Results: With current sowing dates, the maize yield declined under both RCP 2.6 and RCP 8.5 scenarios, respectively in all the AZs, that is, by 4-23% and 60-80% in AZ II, by 5-60% and 60-90% in AZ III, by 9-30% and 50-90% in AZ IV and by 13-40% and 30-90% in AZ V. Though yield decline was lesser under RCP 2.6 as compared to RCP 8.5, but still it indicates that adaptive strategy such as shifting of sowing dates may be helpful in stabilizing the maize yield., Conclusion: The results for iterative combinations of sowing period revealed that early June sowing in AZ II for both the hybrids, mid- to end-June (Ludhiana and Amritsar) and end-May to mid-June (Patiala) sowings for PMH 1 were able to nullify the negative impact of climate change. Maize cultivation in AZ IV and AZ V would not be a suitable venture for farmers of the region. © 2023 Society of Chemical Industry., (© 2023 Society of Chemical Industry.)

Flooding events are determining a significant amount of damages, in terms of economic loss and also casualties in Asia and Pacific areas. Due to complexity and ferocity of severe flooding, predicting flood-prone areas is a difficult task. Thus, creating flood susceptibility maps at local level is though challenging but an inevitable task. In order to implement a flood management plan for the Balrampur district, an agricultural dominant landscape of India, and strengthen its resilience, flood susceptibility modeling and mapping are carried out. In the present study, three hybrid machine learning (ML) models, namely, fuzzy-ANN (artificial neural network), fuzzy-RBF (radial basis function), and fuzzy-SVM (support vector machine) with 12 topographic, hydrological, and other flood influencing factors were used to determine flood-susceptible zones. To ascertain the relationship between the occurrences and flood influencing factors, correlation attribute evaluation (CAE) and multicollinearity diagnostic tests were used. The predictive power of these models was validated and compared using a variety of statistical techniques, including Wilcoxon signed-rank, t-paired tests and receiver operating characteristic (ROC) curves. Results show that fuzzy-RBF model outperformed other hybrid ML models for modeling flood susceptibility, followed by fuzzy-ANN and fuzzy-SVM. Overall, these models have shown promise in identifying flood-prone areas in the basin and other basins around the world. The outcomes of the work would benefit policymakers and government bodies to capture the flood-affected areas for necessary planning, action, and implementation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The unpredictability of the climate has drawn a lot of interest worldwide, especially that of the annual mean temperatures and rainfall. In this study, non-parametric tests such as the LOWESS curve method, Mann-Kendall (MK), SNHT test, Pettitt's test (PT), and Buishand range test (BRT) were used to evaluate long-term (2000-2020) rainfall data series to examine rainfall variability. The Dakshina Kannada district has the highest average rainfall is 3495.6 mm with a magnitude change% of about 26.2, while the Koppala district has the lowest average rainfall roughly about 530.4 mm, with a magnitude change % of about 11.49 mm in a year. The statistics from the fitted prediction line were utilized to determine the maximum coefficient determination (R 2  = 0.8808) in the Uttara Kannada region. Because of the commencement of the present rising era, 2015 is the shift year in rainfall with the highest potential of being a change point in the state's Western Ghats region. It was also revealed that the majority of the districts exhibit positive trends before the change point and vice versa. The current research can be used to plan for and minimize the agricultural and water resource challenges in the state of Karnataka. To link observable patterns to climate variability, the next inquiry must identify the source of these changes. Overall, the study's findings will help organize and improve drought, flood, and water resource management techniques in the state., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Demand planning plays a very strategic role in improving the performance of every business, as the planning for a whole lot of other activities depends on the accuracy and validity of this exercise. The field of agriculture is not an exception; demand forecasting plays an important role in this area also, where a farmer can plan for the crop production according to the demand in future. Hence, a system which could forecasts the demand for day-to-day food harvests and assists the farmers in planning the crop production accordingly may lead to beneficial farming business. This paper would experiment by forecasting the demand using multiple linear regression (EMLR-DF) for different food commodities and implements the model to assists the farmers in demand based constructive farming. Implementation results have proved the effectiveness of the proposed system in educating the farmers in producing the yields mapping to the demand. Implementation and comparison results have proved the proposed EMLR-DF is more effective and accurate.

Background: Protecting crops from various threats, including vermin, pests, animals and rodents, is essential for sustaining agriculture. In India, especially in regions like Rajasthan, animal attacks result in significant crop losses, up to 40%. This section underscores the importance of safeguarding crops against these threats. Methods: According to our sustainable agriculture assessment and cognition of the primary issue of the community that was conducted across multiple rural sites within the Sawai Madhupur district of Rajasthan from 2020 to 2023. This paper employs a comparative method to conduct a comprehensive review of animal-repellent systems, along with delving into interdisciplinary research in related fields to identify key factors influencing their effectiveness and proposes a novel holistic farm protection solution system. Result: The proposed system offers robust crop protection while aiding environmental conservation and preserving local wildlife in Rajasthan, India. This paper underscores the importance of adopting IoT-based technologies for sustainable agriculture. It is a valuable resource for researchers, agronomists and various agriculture stakeholders to implement these advancements. This system holds promise for enhancing crop security, minimizing resource waste and ensuring food chain stability for generations to come. [ABSTRACT FROM AUTHOR]

Holistically, after the green revolution, India has been a global agricultural powerhouse of various crops and in present most of the farmers adopt the traditional irrigation methods but challenging task is in utilizing minimum water resource for more productivity per crop in diversified Indian environmental conditions. Water is a precious & scarce resource in many areas of the country due to traditional agricultural irrigation & industrial use. Hence, to limit water loss & wastage in farming it is important for maximum water application efficiency. Indeed, Systematic Irrigation System (SIS) for farming is need of hour and hence, attempt is made for development of SIS using computational device, and NodeMCU & Sensor technology are illustrated in this article. The SIS prototype has developed deploying ESP8266 Wi-Fi SoC development board and various sensors such as humidity, temperature, soil moisture, PIR & rain sensor . Graphic User Interface is developed in Blynk platform. This prototype has been tested in the laboratory successfully for application efficiency and has found good performance as expected. [ABSTRACT FROM AUTHOR]

Purpose: This paper gives a model of collusion formation and a method of measuring the degree of it among the traders/bidders in the agricultural commodity markets in India. The important assumption is that the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. The paper is based on full information in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data. Design/methodology/approach: The paper used the standard theory of optimization and the theory of auction and probability statistics. Findings: This is a complete information model of cartel formation. The bidding is repetitive and continues forever in discrete time. Hence bidders behavior is observable. Using the proposed method, if the APMC measures for each market and publishes on a periodic basis, say weekly basis, then it will be easier to break the collusion in the market where relative collision is present. For example, if a farmer has three options to sell in three different markets, then the published data would help them to select the market where the degree of collusion is relatively lower. Moreover, the undesirable loss can be avoided based on the right choice of market. As a result, transaction costs will be optima. Originality/value: The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation with the help of real-life data. [ABSTRACT FROM AUTHOR]

A fundamental necessity in advancing sustainable crop production lies in the establishment of a reliable technique for assessing soil health. Soil health assessment is a challenge considering multiple interactions among dynamic indicators within various management strategies and agroecological contexts. Hence a study was conducted to determine the soil health variables, quantify the soil health index (SHI), and validate them with the productivity of rice (Oryza sativa L.)-wheat (Triticum aestivum L.) system for the Indo Gangetic basin of Bihar, India, under four contrasting agro-climatic zones (ACZ-I, II, IIIA & IIIB). For this study, 100 soil samples (0-15 cm) from each ACZ with a total of 400 soil samples were obtained for analyzing 20 soil health variables (soil physical, chemical, and biological properties). To identify SHI and important soil health variables, principal component analysis (PCA) was employed. Apart from specific variables, soil pH, soil organic carbon (SOC), available Zn and available water capacity (AWC) were identified as common indicators for the four ACZs. Results revealed that under the rice-wheat cropping system, ACZ-IIIB soils had a higher SHI (0.19-0.70) than other ACZs. SHI of ACZ-IIIB was significantly influenced by SOC (19.32 %), available P (10.52 %), clay (10.43 %), pH (10.80 %), and soil respiration (9.8 %). The strong relationship between SHI and system productivity of the rice-wheat (R 2  = 0.79) system indicates that the selected soil health variables are representative of good soil health. It is concluded that ACZ-specific SHIs are a promising strategy for evaluating and monitoring soil health to achieve the United Nations' Sustainable Development Goal of 'zero hunger' by 2030., Competing Interests: Declaration of competing interest The authors declare that there are no known competing financial interests or personal relationships that could have influenced this paper's findings., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Drought is an extended shortage of rainfall resulting in water scarcity and affecting a region's social and economic conditions through environmental deterioration. Its adverse environmental effects can be minimised by timely prediction. Drought detection uses only ground observation stations, but satellite-based supervision scans huge land mass stretches and offers highly effective monitoring. This paper puts forward a novel drought monitoring system using satellite imagery by considering the effects of droughts that devastated agriculture in Thanjavur district, Tamil Nadu, between 2000 and 2022. The proposed method uses Holt Winter Conventional 2D-Long Short-Term Memory (HW-Conv2DLSTM) to forecast meteorological and agricultural droughts. It employs Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data precipitation index datasets, MODIS 11A1 temperature index, and MODIS 13Q1 vegetation index. It extracts the time series data from satellite images using trend and seasonal patterns and smoothens them using Holt Winter alpha, beta, and gamma parameters. Finally, an effective drought prediction procedure is developed using Conv2D-LSTM to calculate the spatiotemporal correlation amongst drought indices. The HW-Conv2DLSTM offers a better R 2 value of 0.97. It holds promise as an effective computer-assisted strategy to predict droughts and maintain agricultural productivity, which is vital to feed the ever-increasing human population., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The characteristics of cropland development and the dynamics of food production in China and India, the world's largest agricultural and most populous countries, are of great importance to global food security. However, there is a notable lack of a thorough comparison between China and India in this regard. Here, we systematically compare the differences between China and India using cropping intensity and crop production data, including cropland area, harvested area, total staple crop (i.e., cereal crops, tuber crops and pulse crops) production and yield capacity. The results are mainly as follows: (1) Both China and India experienced an increasing trend in cropland area and harvested area from 2001 to 2021, especially notable in India. In China, the cropland area and harvested area increased by 11.76 % and 14.36 %, respectively, while in India, they witnessed a more substantial increase of 31.10 % and 49.32 %, respectively. (2) The cropping intensity underwent significant transformations, primarily shifting between non-cropland, single-cropping, and double-cropping. Northwestern China exhibited a clear trend of non-cropland converting to single-cropping, whereas northeastern China showed a distinct pattern of single-cropping changing to non-cropland. The interconversion between single-cropping and double-cropping was also frequently observed in the main food-producing regions. In India, the cropland expansion and the adoption of double-cropping are highly pronounced, extending widely across most of the country. (3) From 2001 to 2021, the total staple crop production in China and India increased by 34.12 % and 55.81 %, respectively. Despite the rapid growth in India's total staple crop production, it still amounts to only about half of China's. The major crops production also showed different trends, China's cereal crops production increased significantly, while tuber and pulse crops production declined, and India's production of cereal, tuber, and pulse crops has all increased (4) China's yield capacity has increased by 17.28 %, while India's has only grown by 4.35 %. Despite the rapid increase in India's total staple crop production, the yield gap with China has widened. The boost in China's total staple crop production mainly resulted from improved yield capacity, whereas India relied more on the cropland area expansion, especially the increase in harvested area. Our comprehensive comparison of China and India in cropland development and staple crop production contributes to a deep understanding of the differences in agricultural production between the two countries, and provides lessons for global food security and sustainable agricultural development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The paper attempts to include land as an input in the KLEMS-type production function and estimate agricultural total factor productivity growth (TFPG) for India. For doing so, land quality is accounted for by assigning weights to different land types: irrigated, rainfed and fallow. The estimates suggest that the rate of agricultural TFPG was 0.8 per cent per annum between 1980 and 2019 without accounting for land. However, it increased to 2.0 per cent and 1.8 per cent per annum with the inclusion of land and land quality, respectively. The growth accounting decomposition shows that the contribution of TFPG to agricultural output growth increased from 48 per cent in the 1980s to 78 per cent in the 2010s. Examination of the drivers of agricultural TFPG through an Autoregressive Distributed Lagged (ARDL) model suggests that public gross capital formation (GCF) stock, research and development, mechanisation in agriculture, and favourable terms of trade significantly improve agricultural productivity in India. [ABSTRACT FROM AUTHOR]

This study was carried out to understand the pattern of surface energy fluxes over a periodical scale and energy balance closure using Large Aperture Scintillometer and Micrometeorological tower. The standalone technique as 'Scintillometry' which observes the structure parameter of refractive index based on Monin-Obukhov Similarity theory, has the potential to measure the sensible heat flux precisely. This paper discusses the surface energy balance components and energy balance closure over a period of August 2017 to June 2018. The maximum mean energy fluxes Rn, G, H and LE were observed in September (98.6 Wm-2), May (13.9 Wm-2), June (53.3 Wm-2) and August (82.1 Wm-2), respectively. The overall mean ET was observed at the rate of 1.36 mm day-1 during the study period. This scintillometry technique may further use in evapotranspiration modelling from polar orbiting satellite to geostationary satellite over a heterogeneous and undulated landscape. [ABSTRACT FROM AUTHOR]

The average annual income of farmers in India is well below the poverty line, primarily due to off-season agriculture and a lack of awareness about optimal farming techniques and crop management. This research paper presents an AI-based web application designed to address these challenges and improve farmers' financial and mental well-being. Our solution, comprised of a farming tools leverage system and a collaborative farming forum, empowers farmers with the knowledge and tools needed to make informed decisions and increase their income. The system leverages MongoDB, asynchronous calling, and Fast API for efficient data management and real-time interactions. AI/ML services assist with crop recommendations, crop disease detection, and price predictions. Load balancing ensures optimal performance, and Pusher JS enables real-time communication. Billing services and a dashboard provide income insights, while geographic data enhances machine learning recommendations. In conclusion, this research contributes to alleviating poverty and enhancing the livelihoods of farmers in India by providing a comprehensive solution to the challenges they face. [ABSTRACT FROM AUTHOR]

Hydroponics technology offers an environmentally sustainable alternative to conventional farming for urban food needs. It attracts technologists, non-farmers, retailers, restaurants, and consumers. However, the environmental impact of hydroponics-based urban farming models is yet to be quantified. This study assesses the environmental impact of hydroponics-based urban farming models and makes suggestions to improve their adoption. The methodology involves the use of the Product-Service Systems perspective to categorise the hydroponics-based urban farming models and the Life Cycle Assessment (LCA) method to quantify their environmental impact from a cradle-to-gate perspective. The analysis focuses on the lettuce crop in the state of Tamil Nadu, India. The results from the study suggest that that greenhouse farming (BM1) is more environmentally sustainable than indoor farming (BM2), Cabinet selling and remote monitoring (BM3), and conventional farming. It outperforms other models in terms of GHG emissions, Human Toxicity, and fossil fuels per unit of product, with BM3 having high environmental impacts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

We investigated methane (CH 4 ) and nitrous oxide (N 2 O), two important greenhouse gases (GHGs) emissions using the closed chamber method from a flooded rice field in Brahmaputra valley of Assam, northeast part of India. We tried to understand the factors responsible for the emission and identify appropriate agro-technologies for their mitigation. Various factors like water level, drainage management, soil organic carbon management, crop management, fertilizer amendment, cultivar type etc. affect the GHG production and emission from the flooded rice soil. In this study, six treatments were employed, namely, farmer's practice (FP), recommended fertilizer dosage (RDF), direct seeded rice (DSR), intermittent wetting drying (IWD), use of efficient methanotrophs (MTH), and use of ammonium sulfate as a nitrogen source for real-time nitrogen management using leaf color chart, (AS). GHG flux was measured through the static closed chamber technique. Soil temperature, pH, and redox potential (Eh) and other soil physico-chemical and biological properties that have a potential role in GHG emission were also assessed. The lowest CH 4 flux was observed in IWD treatment. The highest CH 4 but lowest N 2 O flux was observed in RDF thus portraying a tradeoff relationship among these two GHGs. The highest N 2 O flux was observed in AS. Changes in Eh strongly altered CH 4 and N 2 O emissions. The CH 4 flux for the growing season varied from 62.5 to 86.3 kg ha -1 with an average of 72.4 kg ha -1 . The average N 2 O flux was 0.89 kg ha -1 with values fluctuating between 0.72 - and 1.08 kg ha -1 . The findings of this study could assist in understanding the factors affecting the source, production, and sink of these two important GHGs. IWD, along with judicious N-based fertilizer use, could provide significant respite from GHG emissions in rice-based agriculture. These climate-smart strategies not only reduce emissions but also have the potential to improve yield., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Extensive global dependency on rice and wheat crops has necessitated the adoption of intensive cultivation practices, thereby compelling to closely monitor the potential yield-limiting factors, among which, boron (B) deficiency stands out to be a prime concern. The present study explores the effects of B fertilization strategies within the Rice-Wheat Cropping System (RWCS) in the Tarai region of North-West India. A comprehensive six-year field experiment was conducted (2013-2019) at G.B. Pant University of Agriculture and Technology, Uttarakhand, India. The experiment tested graded B doses (0.5, 1.0, 1.5, and 2.0 kg ha -1 ) at varied frequencies (single, alternate, and annual) in a factorial design. The study revealed significant impacts of alternate B application at 1.5 kg ha -1 on crop yields and the Sustainable Yield Index (SYI). The System Rice Equivalent Yield (SREY) exhibited an increase of 6.7% with B supplementation over B-deprived plots, highlighting the pivotal role of B fertilizer in enhancing productivity within the RWCS. The economic optimum B dose was found to be 1.422 kg ha -1 using a linear plus plateau model, resulting in a calculated annual SREY of 9.73 t ha -1 when applied alternately to the cropping system. Continuous application and higher B rates demonstrated substantial increases in various B fractions, while the mobility factor remained within 10%, depicting safe ecological limits. The distribution of fractions in B-treated plots on average followed the order: residual B > organically-bound B > oxide bound B > specifically adsorbed B > readily soluble B. Similarities in the distribution patterns of B fractions between B-treated plots and the control indicated potential influence of biotic or abiotic processes on B fraction dynamics, even in the absence of external B application. To sum up, B application in alternate years at 1.5 kg ha -1 was most sustainable in enhancing the SREY, SYI, available soil B, and B fractions and lowering the environmental hazards., Competing Interests: Declaration of competing interest The author(s) declared no potential conflict of interest that could have appeared to influence the work reported in the present paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Crop residue management has become more challenging with intensive agricultural operations. Zero tillage and crop residue returns, along with the enhancement of in-situ residue decomposition through microbial intervention, are essential measures for preserving and enhancing soil quality. To address this problem in view of stubble burning, field experiments were conducted in rice-rice (variety Swarna) cropping systems under lowland conditions, wherein the following different residue management practices were adopted viz., conventional cultivation (CC), residue incorporation (RI @ 6 t paddy straw ha -1 ), residue retention (RR @6 t paddy straw ha -1 ), and zero tillage (ZT). In this experiment, two microbial products i.e. solid microbial consortium (SMC) at 2.0 kg ha -1 ) and capsule (10 numbers ha -1 ), were evaluated in both Rabi (dry) and Kharif (wet) seasons under different residue management practices. The results on soil microbial properties showed that application of either SMC or capsule based formulation could significantly improve the soil organic carbon (SOC) content in ZT (9.51 g/kg), followed by RI (9.36 g/kg), and RR (9.34 g/kg) as compared to CC (7.61 g/kg). There were significant differences in the soil functional properties (AcP, AkP, FDA, and DHA) with microbial interventions across all residue management practices. SOC was significantly positive correlated with cellulase (R 2  = 0.64, p < 0.001), β-glucosidase (R 2  = 0.61, p < 0.001), and laccase (R 2  = 0.66, p < 0.001) activity; however, the regression coefficients varied significantly with microbial intervention. Moreover, the availability of N, P, and K in soil was significantly (p < 0.05) improved under microbial treatments with either RR or RI practices. Among the different methods of residues management practices, RI with microbial intervention registered a consistent yield improvement (8.4-17.8%) compared to conventional practices with microbial intervention. The present findings prove that the application of decomposing microbial consortia for in-situ rice residue management under field conditions significantly enhances soil quality and crop yield compared to conventional practices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This paper revisits the debate on the relationship between farm size and utilisation of agricultural land. Since the 1960s, a large number of studies have been examining this relationship and suggesting possible explanations supporting their thoughts. Three significant hypotheses exist in the literature forwarded by different scholars in this regard: an inverse relationship, a positive and a U-shaped one. Using the recent data from the Agriculture Census of India, this paper attempts to analyse the spatio-temporal trends of the relationship between farm size and land utilisation and examine the hypotheses and explanations already advanced, taking a state-level analysis in India. We found an inverse relationship where smaller farms are more fully and intensively used compared to the larger farms; however, the increasing share of unutilised land among the small and medium farms in the recent decade of 2005–2006 to 2015–2016 indicates a losing ground of small farmers because of ongoing agrarian distress. [ABSTRACT FROM AUTHOR]

The two main avenues via which agricultural produce is gathered, distributed, and resold in rural India are the regulated markets set up by the State Governments and the sporadic marketplaces that have developed naturally and are unregulated. Under the auspices of extensive regulations that have been formulated and amended periodically by the corresponding state Agricultural Produce Marketing Regulation Act, agricultural produce market committees have been established to promote equitable trade. Since their inception, regulated markets have assisted in reducing market disadvantages; yet, the competitive market structure was not well-foreseen by their legal framework. In an environment of liberalized trade, this paves the way for the market committee to become more manageable and sustainable. Given the dependence of other sectors on agriculture, India has viewed it as a valuable tool for economic progress. The regulated markets are regarded as accountable establishments that carry out all the tasks associated with the selling of products while considering the interests of all final consumers as a whole. The current paper highlights Indian agriculture, with a particular emphasis on the regulated agricultural marketing system and its development, status, and prospects. The report also emphasizes the difficulties and impact of a regulated market on farmers' socioeconomic standing. At the study's conclusion, a number of restrictions that either directly or indirectly impacted the farmers' socioeconomic standing were mentioned. To comprehend the link between the dependent and independent variables, a variety of statistical methods were employed. To arrive at the ultimate outcome, an ex post facto research design was mostly employed. [ABSTRACT FROM AUTHOR]

A conference paper about mitigation measures for weather risks in India is presented. It discusses long term analysis and trends in rainfall and temperature from 1901 to 2004 in areas including West Bengal, Central India, and coastal regions. Also explored are adaptation strategies to mitigate the impacts of climate change on agriculture.

Agriculture is one of the most important economic activities for any nation to have self-reliance and food security. Indian agriculture has unique challenges given its geographic, social and demographic variations and farming practices that tie deeply with local culture and rituals. Environmental sustainability is now a central discourse in all aspects of socio-economic development as we witness the growing adverse impact of climate. Governments and policymakers all across the world find it hard to accommodate the Millennium Sustainable Development Goals while trying to feed their growing population. A possible solution lies in large-scale adaptations of innovative farming practices that compromise neither on yield nor on the sustainability of the land. The challenge lies in trying to change traditional agricultural practices that have been used for thousands of years, which fall in the domain of behaviour change through development communication. This paper focuses on using the participatory form of development communication to help in establishing an ecosystem of integrated farming. Agricultural extension and its messaging need to be modified to imbibe the values of sustainable farming along with the dissemination of innovative technology and inputs for farming. The paper uses conceptual analysis from different sources of secondary literature to propose a set of key messages and themes around which extension workers can create a dialogue with farming stakeholders. Adapting these communication approaches may help in creating an essential connection between rural and urban aspects of Indian agriculture. [ABSTRACT FROM AUTHOR]

Pulses are an important protein source for vegetarian people across the world and they have a great potential to improve the human health, contribute to global food and nutritional security. Variety of pulses were grown in India with 25% of global production and 27% of global consumption. Though India is the largest pulses producer in the world, it imports around 3.5 million tons annually to meet the ever-increasing requirement. Less adoption of improved Agro techniques, low fertile soils and unpredictable environment conditions are major factor for low production of pulses. As a results of increasing population, the projected pulses requirement will be 32 million tons by 2030 which necessitate annual growth rate of 4.2%. With adoption of suitable agronomic strategies, the productivity has to be enhanced to meet the demand. This review work was done at Department of Agronomy, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu, India. Collected review and research papers were screened from various data base like TNAU e library, ARCC journals, google scholar, research gate and scopus used to write this paper. This review article documented information gathered on importance of pulses, area, production and productivity of pulses. Nipping is important agronomic practices that removes the apical bud dominance and promotes the lateral growth which turn better maintenance of source and sink relationship and enhance the pulses yield. Influence of nipping on growth and yield of various pluses crops has been discussed here. [ABSTRACT FROM AUTHOR]

Purpose: Given the dominant share of India in global production of fruits and vegetables, this paper intends to analyze the export competitiveness of India and other major food exporters in the world trade. The purpose of this study is to examine export structure, substitutability and complementarity of selected fresh and processed fruits and vegetables of top ten food exporters for the period 2010-20. Design/methodology/approach: Balassa's (1965) revealed comparative advantage (RCA) index was used to measure RCA indices of selected fruits and vegetables under study. Also, revealed symmetric comparative advantage (RSCA) and normalized RCA (NRCA) indices have been calculated. Further, Spearman rank correlation coefficients were computed to analyze changes over the study period for India and other competing countries. The export data have been sourced from UN Comtrade, an electronic database of United Nations, as well as World Trade Statistical Review, a database of World Trade Organization. The analysis was undertaken at Harmonized System (HS) four-digit classification for the period 2010-20. Findings: The results disclosed an improvement in India's comparative advantage over the period of 2010-20 in HS 07 product category, whereas the advantage ceded to other competitive nations in HS 08 product category. Further, Spearman rank correlation coefficients revealed that India faces competition from countries like China, Indonesia, Brazil, Thailand, Argentina and European Union for HS 07 product category, while countries like Mexico, Indonesia, Brazil and Thailandare the major competitors of India in HS 08 product category. Originality/value: The paper expands the existing agricultural trade literature in three ways. First, it is one of the very few studies that have analyzed RCA for Indian fresh and processed fruits and vegetables using three different types of indices, namely, Balassa's RCA, RSCA and NRCA. Second, the authors provide a number of comparisons related to RCA for Indian fruits and vegetables with other top food exporters in the world for a period of 10 years (2010-20). Third, the authors contribute to agricultural trade literature by assessing the substitutability or complementarity of India in the export of fruits and vegetables with other competing nations by using Spearman rank correlation coefficients. [ABSTRACT FROM AUTHOR]

Global climate change has numerous implications for members of mountain communities who feel the impacts in both physical and social dimensions. In the Western Himalayas of India, a majority of residents maintain a livelihood strategy that includes a combination of subsistence or small-scale agriculture, seasonal pastoral migration, male out-migration, and localized natural resource extraction. Particularly under conditions of heavy male outmigration, but throughout the region, mountain women play a key role in providing labor and knowledge related to the management of local natural resources, yet often lack authority in related political and economic decision-making processes. This gap has important implications for addressing the impacts of climate change: while warming temperatures, irregular patterns of precipitation and snowmelt, and changing biological systems present challenges to the viability of these traditional livelihood portfolios throughout the region, mountain women increasingly face new challenges in their roles as household managers that have not adequately been emphasized in larger scale planning for climate change adaptation and mitigation. These challenges are complex in nature, and are shaped not only by gender issues but also interacting factors such as class, caste, ethnicity, and age (among others). In this paper, we review the main arguments behind the discursive gender/climate change nexus, discuss the implications for gendered vulnerabilities and transformation of adaptive capacities in the region, and suggest ways that researchers and policymakers seeking to promote "climate justice" can benefit from the incorporation of gender-based perspectives and frameworks. [ABSTRACT FROM AUTHOR]

A country’s growth depends on how well the citizens are able to access, avail and afford the financial services. Finance is an important aspect for a country to prosper. Agricultural finance ensures that there is a full participation by everyone and that the underprivileged or the marginalized compartment of the society is not left behind in availing the basic financial services. India having a big population often face a problem when it comes to implementing the policies that reach a wider audience. The Agricultural Banking Services in India has undergone changes with time and have been working to provide a wide range of facilities but the infrastructure, insurance, financial literacy, the digital divide and the disparity in the availability of resource in urban and rural area is evident. There is one section that avails all the benefits and others who are excluded. In this paper, we study about the status of India, when it comes to Agricultural finance, using selected indicators, and understand the basic initiatives taken by the government under the recent National Strategy Planning and the action plan and milestones set to achieve the goal of providing inclusion and financial strength to maximum citizens of India. [ABSTRACT FROM AUTHOR]

This paper examines the significant agrarian transformations in India's Himalayan region of Kashmir, which is witnessing a rapid transition into commercial farming and, simultaneously, an increasing trend of deagrarianisation. The study uses a mixed-method approach to investigate why farmers adopt commercial farming in this region and how the processes of deagrarianisation, reconfiguration of land use, and deepening commodification have become inevitable for many small and medium-scale farmers as a result of this process. In the analysis, our empirically tested theoretical model confirms that institutional factors in terms of state support work as a significant driver toward commercialisation. We then argue that combined with the stimulus of the state, a vigorous process of neo-extractivism is being promoted, which renders the substantive changes in agrarian transitions by displacing the subsistence sector. The study highlights that this contemporary commercialisation is altering the social and physical landscape and driving broader forms of dispossession and consolidation of farmlands at micro-levels. Furthermore, it raises questions about the fundamental role of the Indian state's neo-extractivist policies in a politically contested region. [ABSTRACT FROM AUTHOR]

The lives of rural households are predominantly based on agriculture and its allied activities. However, there are signs of an agricultural crisis resulting in dependence on alternative sources of income. This paper analyzes the factors that influence the decision of farm households to participate in non-farm activities for alternative income. The official data for two years on the Situation Assessment Survey of Agricultural Households are explored and a pooled probit regression model is run to examine the determinants of income diversification. Our findings reveal that farm income and irrigated land negatively influence diversification. However, diversification of those having lower access to farm holdings, socioeconomic deprivation, and improved access to education, informal credit, and crop insurance point out positive participation in non-farm enterprises. In addition, the population belonging to hilly and coastal plain regions and the age group 30–64 years are more likely to diversify. [ABSTRACT FROM AUTHOR]

The paper attempts to examine the factors that influence climate-smart adaptation (CSA) strategies. The study used binary logit and multivariate probit models to understand the dynamics and factors of agricultural households' behavioural decisions on CSA strategies. Based on the results of the binary logit model, the study indicated that factors such as access to extension services and training, gender, educational level, land ownership, access to irrigation, access to credit and crop damage level positively and significantly influenced farmers' decisions to use CSA strategies. Similarly, the results of the multivariate probit model reveal that factors such as educational level, access to extension services and training, and land ownership had significant impacts on the adoption of the majority of CSA strategies. To improve the intensity of CSA strategies, the study recommends expanding training and extension services to farming masses, the expansion of irrigation facilities and weather information at the farm level. [ABSTRACT FROM AUTHOR]

Artificial Intelligence is quickly emerging as a technological solution for the agriculture industry to surmount its classical challenges. Artificial Intelligence is facilitating farmers to refine their products and alleviate unfavourable impacts due to the environment. The central concern of this paper is predictive analytics to develop a machine learning model to identify and predict crop yield based on multiple environmental factors. In this paper, a hybrid learner 'RaNN' is proposed that combines the feature sampling and majority voting technique of Random Forest in-combination with the multilayer Feedforward Neural Network to predict the crop yield. Research has also ascertained the essential features responsible for accurate yield prediction. The proposed model works for rice yield prediction, one of the chief grains of India. The region chosen for the work is Punjab, which is among the largest producer states of India for rice. The dataset consists of 15 attributes comprising the weather and agriculture data collected from the Indian Meteorological Department Pune, and Punjab Environment Information System (ENVIS) Center, Government of India. The study has also made a comparative assessment of 'RaNN' with machine learning methods like Multiple Linear Regression, Random Forest, Decision Tree, Boosting Regression, Support Vector Machine Regression, Ensemble Learner, and Artificial Neural Network. Our model RaNN has listed a better prediction accuracy with minimal error among the other techniques providing a 98% correlation between the actual and the predicted yield. Abbreviations: AI – Artificial Intelligence; ANN – Artificial Neural Network; BR – Boosting Regression; Chem Fert – chemical fertilisers; DT – Decision Tree; EL – Ensemble Learner; ENVIS – Punjab Environment Information System; GBM – Stochastic Gradient Boosting Method; GPS – Global Positioning System; HMAX – highest maximum temperature in degrees C; IMD – Indian Meteorological Department; L1 – Lasso regression; L2 – Ridge regression; LMIN – lowest minimum temperature; ML – Machine Learning; MAE – Mean Absolute Error; MEVP – mean evaporation in mm; MLR – Multiple Linear Regression; MMAX – mean maximum temperature in degrees C; MMIN – mean minimum temperature in degrees C; MSSH – Mean sunshine duration in hours; MWS – mean wind speed in km/h; P1 – number of days with precipitation (0.1–0.2 mm); P2 – number of days with precipitation (greater than or equal to 0.3 mm); RaNN – Hybrid RF-ANN model; RMSE – Root Mean Squared Error; $${R^2}$$ R 2 – Coefficient of determination; RD – number of rainy days; RF – Random Forest; SVM Reg – Support Vector Machine Regression; TMRF – total rainfall per month in mm [ABSTRACT FROM AUTHOR]

The objective of the present research paper is to evaluate the efficacy of crop insurance schemes in India, with a specific focus on their performance. The relevant statistics are collected for a period of six years, from 2018 to 2023. The descriptive statistics and CAGR are employed to evaluate the farmer's enrolment, sum insured, and premium collected from Farmers, state/UT, and GOI. Testing of hypotheses made with the help of one sample t-test, paired sample t-test, and correlation. The study found that farmers' enrollment is higher in the kharif season than in the rabi season, and the overall farmer's participation, and sum insured, premium of farmers, State/UT, and GOI in crop insurance schemes is reduced during the study period, which is evidenced by the negative CAGR. There is a consistent decline in farmers' participation in crop insurance schemes which is evidenced by negative CAGR and supported by hypotheses testing. [ABSTRACT FROM AUTHOR]

A comparative study of termite diversity in different ecosystems (agricultural, horticultural and silvicultural ecosystems) was carried out in mid-hills of Meghalaya to understand the species diversity, richness and abundanceof termite. A standard transect method and tissue paper bait method were used for sampling the termites.Alpha diversity was analysed by using Shannon wiener index and Margalef's D index for Species richness; and Simpson's index for Species dominance; whereas Beta diversity was analysed by using Routledge Be index, Cody Bc index, Whittaker Bw index and Wilson and Shmida Bt index. In the study, a total of 10 species of termites were identified which belonged to three subfamilies viz., Macrotermitinae, Amitermitinae and Termitinae. Macrotermitinae was the most presiding subfamily among the collected termite fauna. Individual species dominance was observed to differ in different ecosystems however, Odontotermes spp. was widely distributed across the ecosystems.The number of species recorded in silvicultural, horticultural and agricultural ecosystem were 7, 3 and 1 respectively. The termite diversity was highest in silvicultural ecosystem and lowest in agricultural ecosystem. The lowest numbers of species recorded in ecosystem may be attributed to its abrupt human disturbance. Shannon Wiener, Margalef's D and Simpson index in agricultural ecosystem, depicted less values compared to horticultural and silvicultural ecosystem. Among the ten species collected, one species i.e. Pseudocapritermis tikaderi which was sampled from silvicultural ecosystems was soil/humus feeder and the rest were wood/litter feeders. [ABSTRACT FROM AUTHOR]

Lessons learnt from past experiences push for an alternate way of crop production. One such is conservation agriculture (CA), which can be seen as a new way forward for conserving resources and enhancing productivity to achieve goals of sustainable agriculture. In recent past, progressive and significant efforts are made to develop, refine and disseminate conservation-based agricultural technologies across globe. Tremendous efforts on zero-till practices and surface management with crop residues for crop production were reviewed. This work was done at Department of Agronomy, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai-625 104, Tamil Nadu, India. A systematic cum integrative review of research work done in different parts of World, particularly in India was comprehended. Literature search was done during 2020. About 200 review and research papers were screened from various databases like TNAU e-library, ARCC journals, google scholar, research gate and scopus and 84 papers were used. This review article comprehensively documents major principles of CA along with extent and spread of CA across the globe. It also highlights CA in Indian perspective. Various merits and demerits were also discussed with literature support. This review paper discusses rising concerns of conventional agriculture systems with regard to its adoption, positives and negatives of conservation agriculture in promoting conservation agriculture in tropics. [ABSTRACT FROM AUTHOR]

India is an agricultural country; wherein about 70% of the population depends on agriculture. Agriculture has changed more in the past century than it has since farming began many millennia ago. Research in agriculture is aimed towards increase of productivity and food quality at reduced expenditure and with increased profit. Current crop production practices, often called Precision Agriculture (PA), benefited from all earlier revolutions in crop production. Many times expert advice may not be affordable, majority times the availability of expert and their services may consume time. Image processing along with availability of communication network can change the situation of getting the expert advice well within time and at affordable cost since image processing was the effective tool for analysis of parameters. Image processing techniques in agriculture are mainly used for image categorization based on shape, size, color and texture for decision-making. This leads to agricultural input rationalization and environmental damage reduction by adjusting the agricultural practices like fertilizer and pesticide application to the site that demands and profit maximization. This paper intends to focus on the survey of application of image processing in agriculture field such as imaging techniques, weed detection and fruit grading. This paper presents a survey on some of the existing image processing techniques in agriculture. [ABSTRACT FROM AUTHOR]