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In India, agriculture serves as the backbone of the economy, and is a primary source of employment. Despite the setbacks caused by the COVID-19 pandemic, the agriculture and allied sectors in India exhibited resilience, registered a growth of 3.4% during 2020–2121, even as the overall economic growth declined by 7.2% during the same period. The improvement of the agriculture sector holds paramount importance in sustaining the increasing population and safeguarding food security. Consequently, researchers worldwide have been concentrating on digitally transforming agriculture by leveraging advanced technologies to establish smart, sustainable, and lucrative farming systems. The advancement in remote sensing (RS) and machine learning (ML) has proven beneficial for farmers and policymakers in minimizing crop losses and optimizing resource utilization through valuable crop insights. In this paper, we present a comprehensive review of studies dedicated to the application of RS and ML in addressing agriculture-related challenges in India. We conducted a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and evaluated research articles published from 2015 to 2022. The objective of this study is to shed light on the application of both RS and ML technique across key agricultural domains, encompassing "crop management", "soil management", and "water management, ultimately leading to their improvement. This study primarily focuses on assessing the current status of using intelligent geospatial data analytics in Indian agriculture. Majority of the studies were carried out in the crop management category, where the deployment of various RS sensors led yielded substantial improvements in agricultural monitoring. The integration of remote sensing technology and machine learning techniques can enable an intelligent approach to agricultural monitoring, thereby providing valuable recommendations and insights for effective agricultural management. [ABSTRACT FROM AUTHOR]

Centella asiatica is well known for its miraculous therapeutic properties in various systems of traditional medicine across the world. However, significant variation in its pharmacological activities has been reported due to the unavailability of quality raw material and non-standardized formulations. A number of research papers have been published on the collection of C. asiatica plants from different regions for the identification of a suitable agroclimate with elite germplasms. Efforts have been made to standardize production and post-harvest practices for the availability of quality raw material with a high centelloside content. The ecological niche modeling approach revealed that the Indian subcontinent has high climatic suitability for the production of C. asiatica, and genotypes with a high content of centelloside were predominantly found in the Western Ghats, North East, Eastern Himalaya and Western Himalaya in India. Open cultivation of C. asiatica is more suitable in these agroclimatic zones in India. Cultivation under shade is also suitable in the plains of Central India. Hydroponic and tissue culture of C. asiatica has also been successfully established for the enhanced production of centelloside using supplements and elicitors such as sucrose, auxins, cytokinins, kinetin, methyl jasmonate, etc. Freeze drying has been identified as the most efficient post-harvest method for the high pharmacological activities of C. asiatica extracts. [ABSTRACT FROM AUTHOR]

The sweet oranges [C. sinensis (L.) Osbeck] produced in India are mainly consumed fresh as a table fruit and in the form of freshly extracted juice. Currently, a fraction of the fruit is processed into products like orange juice, concentrates, pulp, and other value-added products. Seedless varieties are preferred both by the consumers and by the processing industry; however, indigenously developed seedless sweet orange cultivars are not available. Citrus triploids are usually seedless due to their abnormal meiosis and embryo abortion. A research study was undertaken at CCRI Nagpur to develop triploid seedless plants of the local sweet orange cultivar Mosambi through endosperm culture in the shortest possible time by dovetailing various techniques. Various steps, viz., endosperm excision, standardization of media for callus initiation, somatic embryogenesis, shoot/root differentiation, mini-grafting, and validation of the triploid status through flow cytometry, chromosome counting, and other morphological parameters, were standardized, and seven confirmed triploid plants were finally produced. An evaluation of fruit quality parameters during the 2022 and 2023 fruiting seasons revealed that the fruits of the triploid sweet orange trees were commercially seedless. This is the first reported comprehensive study on the successful development of commercially seedless plants of the sweet orange cultivar Mosambi. The fruits of the triploid plants showed desirable fruit quality parameters in terms of their seed number (3 to 5.9/fruit), higher vitamin C content (34.4 to 42.66 mg), and lower limonene content (7.77 to 11.34 µg/mL). These triploid plants have the potential to gain recognition as a distinct variety. [ABSTRACT FROM AUTHOR]

Pre-harvest sprouting (PHS) is a condition triggered by environmental factors, particularly prevalent in humid conditions, leading to substantial yield losses in black gram. While the potential for genotypic PHS tolerance exists, it has not been thoroughly assessed in black gram. Hence, the present study aimed to delve into the genetic variation for PHS tolerance in diverse black gram (Vigna mungo (L.) Hepper) germplasm, and also to comprehend the impact of various physical and physiological traits on PHS. A diverse set of 112 black gram accessions collected across the phytogeographical zones of India were examined for their seed and pod characteristics. Water absorption by pods and seeds and fresh-seed germination was calculated by following the standard procedure given by the International Seed Testing Association. The alpha-amylase activity was measured on dry seeds (0 h), 24 h, 48 h, and 72 h after germination of each accession, using a UV-VIS spectrophotometer, and hard-seededness was measured using a texture analyzer machine. The results showed a wide range in PHS tolerance and FSG, and 13 accessions were found to be PHS-tolerant (PHS value < 10%). An indicator of PHS, seed germination in a pod, ranged from 2.75% in IC485641 (highly tolerant to PHS) to 95.85% in IC530501 (highly susceptible to PHS). Correlation and multivariate analysis revealed that PHS was positively correlated with water imbibition by pod and seed, fresh-seed germination and alpha-amylase activity. PHS-tolerant accessions showed a slow increase in alpha-amylase activity, in contrast to PHS-susceptible accessions. The utilization of alpha-amylase activity as a biochemical marker has the potential for evaluating PHS tolerance across various black gram accessions. The identified PHS-tolerant accessions can be used as donors in crop improvement programs aimed at developing PHS-tolerant black gram varieties. [ABSTRACT FROM AUTHOR]

Nagpur mandarin is a popular table fruit across India and is exported to various countries. Only 1% of the total production is processed into various products. The development of seedless cultivars will boost agricultural incomes by enhancing the potential for export and processing. At present, only a couple of commercially seedless varieties are available, but these have yet to become popular. A research study was undertaken to quickly develop a high-quality seedless variety of Nagpur mandarin by combining the available technologies, viz., endosperm rescue, somatic embryogenesis, and mini-grafting, at CCRI, Nagpur. Complete plantlets of C. reticulata Blanco cv. Nagpur mandarin was successfully regenerated from hybrid endosperm tissue via somatic embryogenesis after attempting various permutations and combinations of media at various stages of regeneration, right from the primary callus to complete plantlet production. Maximum response (93.33%) and survival (91.67%) for primary callus induction were obtained in Murashige and Tucker (MT) + Malt Extract (ME) + Casein Hydrolysate (CH) (500 mg/L) +2,4-dichlorophenoxyacetic acid (2,4-D) (2 mg/L) medium. Maximum stimulation for embryogenesis and morphogenesis occurred in 2MT + CH (500 mg/L) + adenine sulfate (ad.s) (2 mg/L) + Benzyl Adenine (BA) (0.25 mg/L). The highest response (95.84%) for shoot differentiation occurred in MT + adenine sulphate (2 mg/L) + Gibberellic Acid (GA3) (1 mg/L) + BA (1 mg/L) (94.85%). The surviving plantlets were tested for ploidy status through flow Cytometry, chromosomal counting/cytogenetic technique, leaf morphology, stomatal characteristics, and the appearance of prominent thorns. In initial evaluation trials, the fruits of the triploid field-planted trees were found to be commercially seedless. These results demonstrated the recovery of stable triploids from the hybrid endosperm via somatic embryogenesis, which is the first of its kind in the field of Citrus triploid breeding in India. [ABSTRACT FROM AUTHOR]

The global COVID-19 pandemic has hit the agriculture sector hard around the world. A study was conducted to assess the impact of the pandemic on cropping patterns, crop management, usage of chemical inputs and their organic alternatives, harvesting, and marketing avenues through a survey approach in the two states of Kerala and Tamil Nadu in India. A total of 250 farmers participated in the study, the data was analyzed by Chi-square test and Kruskal–Wallis test. The assessment of the impact of COVID-19 on some aspects was undertaken by dividing the study period into three phases. Though a smaller number of people were infected with COVID-19 in the initial phase of the pandemic compared to the later phases, farm operations and the procurement of inputs were significantly affected at this phase as there was a sudden disruption in transportation due to COVID-19-induced movement restrictions. During the entire study period, commodities such as rice, bananas, vegetables, coconuts, and flowers suffered maximum crop loss compared to pulses, groundnuts, cotton, and rubber. Among fertilizers, the maximum shortage was observed for chemical fertilizers (46%) and biofertilizers (30%) compared to cow dung (18%) and poultry manure (6%), indicating that farmers tended to use more local materials that could be easily procured and accessed compared to shop-based inputs. A rise in the cost of cultivation, scarcity of farm workforce, and difficulty in hiring farm machinery all have contributed to the loss of profit during the pandemic period. As a response to COVID-19, growers initiated post-harvest processing of commodities, and cropping systems remained the same during the period. The paper also discusses some remedial measures to be adopted by households in the future, to minimize the impacts of such pandemics in the agrarian sector. [ABSTRACT FROM AUTHOR]

Optimizing nitrogen (N) inputs is crucial for maximizing wheat yield and ensuring environmental sustainability. Wheat's economic significance in India calls for a comprehensive evaluation of its ecological implications to develop a resilient production system. This study aimed to identify and evaluate ten wheat cultivars for their yield and N-use efficiency under varying nitrogen inputs (control (N0), half of the recommended nitrogen (N75), and the recommended nitrogen (N150)) using the surface application of neem-oil-coated urea. All N inputs were applied in three splits, basal, crown root initiation, and tillering stages, and an experiment was conducted in a split-plot design. The application of N150 gave the highest dry matter accumulation (DMA) at harvesting stage (AHS) (871 g m−2), seed/spike (60), grain yield (GY = 7.4 t ha−1), straw yield (SY = 8.9 t ha−1), harvest index (HI = 45.2%), protein (12.5%), and total uptake of N (TUN) (223 kg ha−1) by the cultivar 'HD 3249', being closely followed by the cultivar 'HD3117'. Six cultivars ('HD 3298', 'HD 3117', 'HD 3249', 'PBW 550', 'HD 3086', 'HD 2967') out of the ten cultivars evaluated responded well to different input treatments with respect to the grain yield efficiency index (GYEI ≥ 1). Regarding N input, N75 and N150 recorded the highest increases in plant height, AHS (16.5%; 21.2%), dry matter accumulation (DMA) at 30 days after sowing (DAS) (37.5%; 64%), DMA-60 DAS (42%; 53%), DMA-90 DAS (39.5%; 52.5%), TILL-30 DAS (19.8%; 26.4%), TILL-60 DAS (33.3%; 44%), TILL-90 DAS (37.2%; 47.2%), seed/spike (8%; 10%), 1000-grain weight (7.8%; 12.2%), and protein content (23.3%; and 33%) when compared with N0. Furthermore, the application of N75 and N150 improved GY (72.1%; 142.6%), SY (61.1%; 110.6%), BY (65.5%; 123%), and HI by 4.4% and 9%, respectively, over N0. Nitrogen addition (N75 and N150) also significantly increased total nitrogen uptake (104.7%; 205.6%), respectively, compared to N0. The correlation analysis revealed a positive association among most of the crop parameters. Overall, our research results suggest that the cultivars 'HD 3249' and 'HD 3117' have the potential to be effective options for improving N utilization efficiency, grain yield, and GYEI in North-West India. [ABSTRACT FROM AUTHOR]

Optimizing nutrient management strategies is crucial for enhancing the growth, yield, and nutritional quality of fodder maize (Zea mays) while minimizing environmental impacts. This study investigated the effects of innovative nitrogen (N) and zinc (Zn) management approaches on fodder maize production. Different combinations of nitrogen fertilizers, including conventional urea and nano-urea, were applied in conjunction with targeted foliar sprays of zinc sulfate (ZnSO4) and nano-zinc. The experiment was carried out in a Factorial Randomized Block design with four nitrogen management strategies (control N, 100% recommended nitrogen dose RDN through urea, 50% RDN through urea + two sprays of nano-urea at six and ten leaves stages, and 33.33% RDN through urea + two sprays of nano-urea at six and ten leaves stage) and four zinc management strategies (control Zn, soil application of ZnSO4, foliar application of ZnSO4, and foliar application of nano-Zn) which were replicated thrice. The study revealed that applying 50% of RDN through urea, along with dual foliar sprays of nano-urea, achieved comparable productivity to the 100% RDN through urea only. Among the Zn managements, both foliar and soil applications of conventional ZnSO4 recorded similar green and dry fodder yields, although foliar application of ZnSO4 was observed to be superior in terms of qualitative attributes. Maize subjected to the integrated nitrogen and zinc management strategy exhibited elevated protein content and reduced fiber fractions. These findings highlight the potential of nano-urea and foliar zinc application in enhancing both productivity and nutritional quality, while reducing dependence on conventional chemical fertilizers. [ABSTRACT FROM AUTHOR]

An integrated forage-legume cropping system has immense potential to address the issue of land degradability. It provides a critical understanding of the capacity of diversified species mixes vs. monocultures to boost forage production and the dynamics of soil organic carbon (SOC) and phosphorus (P). In this study, we assessed the performance of Napier Bajra Hybrid (NBH) (Pennisetum glaucum × P. purpureum) + cowpea (Vigna unguiculata) and tri-specific hybrid (TSH) (P. glaucum × P. purpureum × P. squamulatum) + cluster bean (Cyamopsis tetragonoloba) as compared to monocultures of NBH and TSH. The legume equivalent yield of NBH + cowpea and TSH + cluster bean intercropping systems were found −31% and −23% higher than monoculture systems. The SOC increased by −5% in the NBH + cowpea system as compared to NBH monoculture. The carbon mineralization rates under NBH + cowpea and TSH + cluster bean were −32% and −38% lower than the NBH and TSH monoculture cropping systems, respectively. It was found that the legume intensification with the forage significantly improved the soil's P status. The research suggested that coalescing diverse crops (e.g., grass and legume) poses enormous potential for sustaining soil health and productivity in semi-arid regions of India. This study advances the research on characterizing the crucial factors of grass-legume-based cropping systems and helps in assessing the impact of these factors on long-term sustainability. [ABSTRACT FROM AUTHOR]

The cultivation of pearl millet in India is experiencing important transformations. Here, we propose a new characterization of the pearl millet production environment using the latest available district level data (1998–2017), principal component analysis, and large-scale crop model simulations. Pearl millet cultivation environment can be divided in up to five environments (TPEs). The eastern part of the country (Rajasthan, Haryana, Uttar Pradesh) emerges as the only region where pearl millet cultivation has grown (+0.4 Kha/year), with important yield increase (+51 kg/ha/year), and potential surplus that are likely exported. Important reductions of pearl millet cultivated area in Gujarat (−4.5 Kha/year), Maharashtra and Karnataka (−4 Kha/year) are potentially due to economy-driven transition to other more profitable crops, such as cotton or maize. The potential rain increase could also accelerate this transition. With R 2 ∈ [0.15–0.61], the tested crop models reflected reasonably well the pearl millet production system in the A1 (North Radjasthan) and AE1 (South Rajastan and Haryana) TPEs covering the largest area (66%) and production share (59%), especially after the use of a new strategy for environment and management parameters calibration. Those results set the base for in silico system design and optimization in future climatic scenarios. [ABSTRACT FROM AUTHOR]

The existing resistance genes against white rust disease are often ineffective due to racial variation of the causal fungal pathogen, Albugo candida. Therefore, new sources of resistance effective against multiple races are needed for durable resistance. Large-scale phenotyping of advanced introgressed (ILs), mutant, and resynthesized (RBJ) lines of Brassica juncea L., under artificial inoculation at cotyledonary and true leaf stages, against thirteen diverse isolates of Albugo candida and simultaneously at the adult plant stage under multi-location field evaluation from 2019–2022, revealed significant differences in white rust reactions. Amongst 194 introgressed lines, three lines, namely ERJ 39, ERJ 12, and ERJ 15, and three lines among 90 resynthesized and 9 mutant lines, including RBJ 18, DRMR 18-36-12, and DRMR 18-37-13, were identified as potential sources of resistance against multiple isolates at all three developmental stages of the plant. Furthermore, correlation and principal component analysis revealed a positive correlation between white rust resistance at true leaf and adult plant stages for ILs as well as mutant and RBJ lines. These novel sources of host resistance will play vital roles are required for the mustard improvement program and to establish a strong genetic and molecular foundation for identifying white rust resistance linked marker(s), QTLs, or gene(s) for sustainable disease management in India. [ABSTRACT FROM AUTHOR]

The System of Rice Intensification (SRI) developed in Madagascar has spread to many parts of the world, including India. This study assessing insect pest prevalence on rice grown with SRI vs. conventional methods at multiple locations in India was prompted by reports that SRI-managed rice plants are healthier and more resistant to pest and disease damage. Field experiments were conducted under the All-India Coordinated Rice Improvement Project over a 5-year period. The split-plot design assessed both cultivation methods and different cultivars, hybrids and improved varieties. Across the eight locations, SRI methods of cultivation showed a lower incidence of stem borer, planthoppers, and gall midge compared to conventional methods. Whorl maggots and thrips, on the other hand, were observed to be higher. Grain yield was significantly higher with SRI management across all locations. Higher ash, cellulose, hemicellulose, as well as silica content in rice plants under SRI management could explain at least in part the SRI plants' resistance to pest damage. Analysis of guild composition revealed that in SRI plots, there were more natural enemies (insect predators and parasitoids) present and fewer crop pests (phytophages). A meta-analysis that considered other published research on this subject revealed a lower incidence of dead hearts, white ear-heads, and leaf folders, along with higher grain yield, in SRI plots. [ABSTRACT FROM AUTHOR]

Inappropriate agricultural practices consume more input energy and emit higher greenhouse gases (GHGs) which cause global warming and climate change, thereby threatening environmental sustainability. To identify energy and carbon-efficient varieties and nutrient management practices, the present study was undertaken during the kharif season of 2018 and 2019 in a split-plot design with three varieties of fodder maize (African Tall, J-1006 and P-3396) and four nutrient management practices such as N0: Absolute control, N1: 100% recommended dose of fertilizers (RDF), N2: 75% RDF + plant growth promoting rhizobacteria (PGPR) + Panchagavya spray and N3: 50% RDF + 25% farmyard manure (FYM) + PGPR + Panchagavya spray). Results indicated that variety J-1006 and applying 75% RDF + PGPR + Panchagavya spray produced significantly higher dry fodder yield. Among the varieties, J-1006 recorded the highest total energy output (224,123 MJ ha−1), net energy (211,280 MJ ha−1), energy use efficiency (17.64), energy productivity (0.98 kg MJ−1), energy profitability (16.64), and lowest specific energy (1.03 MJ ha−1). Regarding nutrient management, 75% RDF + PGPR + Panchagavya spray fetched the highest total energy output (229,470 MJ ha−1) and net energy (215,482 MJ ha−1). However, energy use efficiency, energy productivity, and energy profitability were significantly higher with integrated nutrient management (N2 and N3) over 100% RDF. Concerning the carbon estimation, J-1006 resulted in a significantly higher carbon output (5479 kg CE ha−1), net carbon gain (5029 kg CE ha−1), carbon efficiency (12.46), carbon sustainability index (11.46), and significantly lower carbon footprint per unit yield (CFy) (131.3 kg CO2-e Mg−1). For nutrient management, the application of 75% RDF + PGPR + Panchagavya spray showed significantly higher carbon output (5609 kg CE ha−1) and net carbon gain (5112 kg CE ha−1). However, significantly higher carbon efficiency, carbon sustainability index, and lower CFy were reported with integrated nutrient management over 100% RDF. Overall, selecting the J-1006 variety and applying 75% RDF + PGPR + Panchagavya spray for fodder maize cultivation could be the most productive in terms of dry fodder production, energy, and carbon efficiency approach. [ABSTRACT FROM AUTHOR]

The agrarian communities of South Asia are dominated by small and marginal farmers (<2.0 ha operational holdings) and are confronted with manifold challenges of lower productivity, income, and resource degradation. For optimized and efficient resource use, a shift from business as usual towards green economy is imperative. Therefore, a study to address these challenges, through integrating diverse crops and allied enterprises under an integrated farming system (IFS) model was carried out. We hypothesized that a standardized IFS model with appropriate location-specific modules will have higher system output, income, and lesser environmental footprints. Vegetable cultivation (VC), protected vegetable cultivation (PVC), field crops (FC), mushroom production (MP), and beekeeping (BK) were evaluated under the IFS model, with objectives to optimize the coherent use of available farm resources with enhancing system productivity and profitability. Among the FC module, the system productivity increased from 21–247% of different cropping systems, over the predominant rice–wheat system (RWS). The integration of different components, viz., VP + PVC + FC + AHS + MP + BK + VC in M10 resulted in achieving the maximum water productivity (6.72 kg/m3), energy productivity (1.50 kg/MJ), net return (9446 USD/ha), employment opportunities (792 man-days), sustainable livelihood index (70.2%), and nutrient cycling (138.12, 67.9, and 381.6 kg/ha of nitrogen, phosphorus, and potassium, respectively). These findings can be a scientific basis for the optimization and sustainable management of natural resources under different modules of IFS for the less-endowed small and marginal farmers. [ABSTRACT FROM AUTHOR]

The multi-faceted benefits of growing crops under protected cultivation are gradually establishing it as a promising technology for vegetable cultivation in India. However, the adoption of successive cropping patterns in soil-based closed structures is leading to the buildup of soil-borne pathogens and pests, which are becoming a major hindrance to the sustainable production of these crops, particularly in the northern plains. Root-knot nematodes (RKNs) are a critical threat to protected cultivation and farmers are required to contribute a significant amount of time and money for their management. To reduce the overdependence of chemicals, the present study explored the potential of plant-based by-products as amendments for the management of RKN in cucumbers grown under a plastic greenhouse. A pot trial was conducted to assess the efficacy of different plant-based amendments against nematodes in cucumber plants. The pot trial results revealed that the application of mustard cake (MC) and neem cake (NC) at 1 t ha−1 either alone or as a combined application with farmyard manure (FYM) of 2.5 t ha−1 was effective against RKN infestation, reflecting the improved plant growth parameters of cucumber. Based on the results of the pot trials, treatments with plant-based amendments and FYM i.e., T1: MC 1 t ha−1; T2: NC 1 t ha−1; T3: FYM 2.5 t ha−1; T4: MC 1 t ha−1 + NC 1 t ha−1 + FYM 2.5 t ha−1, along with the treated check carbofuran 3 G 2 kg (a.i.) ha−1 (T5) and untreated check (T6), were evaluated in multi-locational field trials. The results revealed that the combined application of MC 1 t ha−1 + NC 1 tha−1 + FYM 2.5 t ha−1 exhibited promising results in decreasing RKN infestation (56–58%) in all of the three RKN-infested polyhouses, with significantly enhanced yields at all of the three locations. Soil organic carbon also increased significantly in the amended plots, indicating improved soil health. The results of the present work hold good promise for the management of RKN in the protected cultivation of cucumber with an environment friendly approach, along with the additional incentives of improved soil health. [ABSTRACT FROM AUTHOR]

Clay–organic complexes (COC) impart chemical and physical protection to soil carbon (C). In the present study, the aim was to assess the long-term effects of different organic amendments on C stability in COC, distribution of the aggregates, C concentration in the aggregates and labile organic C fractions in the inceptisols located at the research farm situated in the semi-arid sub-tropical climate of India. The results showed that the COC, the percentage of large macroaggregates (LMA) (>2 mm) and the C associated with the aggregates decreased through the soil depths, whereas the other size fractions of soil aggregates (<2 mm) showed an increasing trend. The COC was significantly higher (4.4 times) in soil treatments where farmyard manures (FYM), green manure (GM) and biofertilizers (BF) were applied together (FYM + GM + BF). The organic amendments increased the proportion of LMA over control (no application of organic amendments) to a magnitude of 83 to 101% and the C associated with LMA to a magnitude of 0.48 to 9.8% over control in surface soil. On average, the combined application of FYM, GM and BF exhibited higher C accumulation in almost all soil aggregate fractions, except microaggregates (mA), i.e., (0.25–0.053 mm) size fractions, where application of FYM alone recorded the highest value. Averaged over soil depths, the particulate organic C (POC), dissolved organic C (DOC) and potassium permanganate oxidizable C (POXC) were significantly higher under integrated organic treatments than individual amendments. The significantly higher correlation between COC and the percentage of LMA and aggregate-associated C implied their direct role in soil aggregate formation and their stability. The carbon stability, i.e., retention time of humus in soil, was significantly correlated with soil organic carbon, dissolved organic carbon, particulate organic carbon, potassium permanganate oxidizable C, C mineralization (Cmin), glomalin-related soil protein (GRSP), macroaggregate (MA)-associated C and rice equivalent yield (REY). Overall, the data suggest that the combined application of FYM + GM + BF promotes soil quality under rice–wheat rotation in inceptisols in semi-arid sub-tropical India. [ABSTRACT FROM AUTHOR]

Modern agricultural farming techniques employ the usage of chemical supplements to improve crop yield in terms of quantity and quality. This practice has brought down the fertility of the soil and has led to secondary impacts and necessitates a significant financial investment. Awareness of the side effects of artificially enriched food has made people move towards organically grown food, and the consumption has also increased significantly. One of the ancient organic fertilizers used in India is panchagavya. As the name implies, pancha means five and gavya means cow. The five products of the cow are combined as per the compositions and procedure described in the literature, to provide economical and meaningful value to organic farming. The objective of this work is to design, develop, and implement an automated system to manufacture panchagavya with reduced operator assistance. The system implements an ATmega 328 microcontroller to automate the entire process by interfacing sensors such as pH, moisture, temperature, and pressure. The system is also provided with a SIM900A GSM modem to provide information to the user regarding the status of the process. The developed pilot scale design discussed in this work has several advantages in the world of farming technologies in terms of enriching the soil, thereby improving the crop yield. This technology will benefit the farmers as this natural fertilizer can be mass-produced and turn them into entrepreneurs, which benefits society at large. [ABSTRACT FROM AUTHOR]

The tea industry is the second most organized industry after rubber in Tripura, India and is gravid with immense potential that can offer inclusive and sustainable growth to the state's economy directly and indirectly. The industry went through a series of troubles ranging from insurgency to ethnic clashes over the last six decades. Despite the challenges, the Tripura Tea Development Corporation (TTDC) returned to the profit path in 2018. The marketing opportunities for the tea gardens have been rudimentary, depriving the tea growers of their due recognition and better returns on investments; however, TTDC's Tripureswari brand of tea has successfully positioned itself with a strong appeal and quick acceptance by the masses. The public distribution supply chain supported by the co-operative societies helps reduce the shipment cost and ensures the availability of tea at affordable prices for common people. The purpose of this study was to explore the nuances of the tea industry in Tripura and to consider how re-engineering can turn this industry into a profit-making public sector. To understand the turnaround strategy of this research, the authors have used a mixed method approach where secondary data were collected, discussed, and gathered from interviews with area experts. The findings of this research indicate that the state-owned Tripura Tea Development Corporation Ltd. (TTDC) transformed itself through re-engineering the supply chain. Furthermore, coupling with branding exercises has instilled confidence, even among the small tea growers, thereby offering social security and inclusion. Further, TTDC has taken the socially excluded people under its ambit through plantation activities using the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA). [ABSTRACT FROM AUTHOR]

Little is known about how Indian farming practices affect German chamomile (Matricaria chamomilla L.). This study examines the effects of the sowing date and spacing of plants on flower productivity, essential oil concentration, and the composition of German chamomile grown in the arid zone of Rajasthan, India. In a factorial randomized block design (FRBD), the treatments consisted of four sowing dates (15 and 25 October, 5 and 15 November) and three spacings of plants (20 × 10 cm, 30 × 10 cm, and 40 × 10 cm). The dried flower yield (Kg ha−1), fresh flower yield (Kg ha−1), and number of flowers per plant of chamomile crop were significantly affected by the varying spacing of plants and the date of sowing. The highest values for dry weight, fresh weight, and number of flowers were obtained from the second date of sowing (25 October) with 40 × 10 cm geometry. Likewise, the highest values for total oil (12.44%) and essential oil (0.94%) contents were also obtained from the D2P3 combination (D2—sowing date 25 October, P3—40 × 10 cm spacing of plants). GC/MS analyses of the samples showed that p-menth-1-en-4-ol, acetate, cis-alpha-farnesene, anethole+estragol, 1,4-cyclohexadiene,1-methyl-4-(1-methylethyl)- and 3,6-dihydro-4-(4-methyl-3-pentenyl)-1,2-dithiin were the main identified compounds in the essential oil of chamomile fresh flowers. The treatments altered the quality profile of the essential oils in general. The principal components of chamomile essential oil were significantly affected by the D2P3 treatment. The findings of this study add to our understanding of how to grow high-quality chamomile flowers in arid regions. [ABSTRACT FROM AUTHOR]

Accurate and consistent information on the area and production of field crops is vital for national and state planning and ensuring food security in India. Satellite-based remote sensing offers a suitable and cost-effective technique for regional- and national-scale crop monitoring. The use of remote sensing data for crop yield estimation has been demonstrated using a semi-physical approach with reasonable success. Assimilating remote sensing data with the DSSAT model and spectral indices-based regression analysis are promising methods for spatially estimating rice crop yields. Rice area and yield in the Cauvery delta zone of Tamil Nadu, India was estimated during samba (August–January) season in the years 2020–2021 using Sentinel 1A Synthetic Aperture Radar satellite data with three different spatial yield estimation methods, namely a spectral indices-based regression analysis, semi-physical approach, and integrating remote products with DSSAT crop growth model. A rice area map was generated for the study area using a rule-based classifier approach utilizing parameterization with a classification accuracy of 94.5% and a kappa score of 0.89. The total classified rice area in Cauvery Delta Region was 379,767 ha, and the Start of Season (SoS) maps for samba season revealed that the major planting period for rice was between 22 September and 9 November in 2020. The study also aimed to identify promising spatial yield estimation techniques for optimal rice yield prediction over large areas. Regression models resulted in rice yields of 3234 to 3905 kg ha−1 with a mean of 3654 kg ha−1. The net primary product was computed using the periodical PAR, fAPAR, Wstress, Tstress, and maximum radiation use efficiency in a semi-physical approach. The resultant rice yields ranged between 2652 and 3438 kg ha−1 with the mean of 3076 kg ha−1. During the integration of remote sensing products with crop growth models, LAI values were extracted from dB images and utilized to simulate rice yields in the range of 3684 to 4012 kg ha−1 with the mean of 3855 kg ha−1. When compared to the semi-physical approach, both integrating remote sensing products with the DSSAT crop growth model and spectral indices-based regression analysis had R2 greater than 0.80, NRMSE of less than 10%, and agreement of more than 90%, indicating that these two approaches could be used for spatial rice yield estimation. [ABSTRACT FROM AUTHOR]

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

Red-fleshed dragon fruit offers an array of bioactive compounds. Its cultivation is gaining momentum in India, including in arid and semi-arid conditions. Among various factors, the fruit developmental stages and climatic conditions of locations greatly influence the biosynthesis and actual contents of different bioactive compounds and mineral contents of the fruit. The changes in physical attributes, and bioactive and mineral content in red-fleshed dragon fruit grown in semi-arid conditions in India were assessed and quantified at six developmental stages. Significant changes occurred in the physical attributes of the fruit and the bioactive compounds and mineral content during the fruit maturation stages of the red-fleshed dragon fruit. The fruit physical characteristics, such as fruit size, fruit and pulp weight gain, peel thickness, and fruit firmness, along with eating quality parameters, such as soluble solids, sugars, acidity and soluble proteins, were observed at optimum at 35 days after anthesis (DAA). The decrease in total phenolics (29.96%), total flavonoids (41.06%), and vitamin C (75.3%) occurred throughout the fruit development stages, whereas the content of betalains, which was detected initially at 25 DAA, increased (48.6%) with the progression of the fruit development stages. However, the antioxidant capacity and free radical scavenging activity demonstrated variable trends throughout the fruit maturation period. There was an increasing trend in all the minerals up to 35 days, followed by a slight decrease, except for phosphorus content, which increased until the last stage of evaluation. The colour characteristics, in conjunction with the bioactive and antioxidant potential determined in the present study, suggest that red-fleshed dragon fruit can be harvested at 35 DAA for long-distance transportation, and from 35 to 40 DAA for local marketing. [ABSTRACT FROM AUTHOR]

A field experiment on green pea (Pisum Sativum L.) was conducted under drip irrigation to determine the irrigation schedule based on real-time soil moisture measurements with irrigation treatments (main plots) and fertilizer treatments (sub-plots) in a split-plot design with three replications. Main plots consisted of fourirrigation levels at different matric potential ranges (I1: −20 kPa; I2: −30 kPa; I3: −35 kPa; and I4: −40 kPa), while the sub-plots consisted of three fertigation levels (F1: 120%, F2: 100% and F3: 80%) of recommended dose of fertilizers (40:60:50 kg/ha of NPK). The tensiometer with digital pressure transducer transferred the soil matric potential data to the irrigation controller, which activated the solenoid valves for irrigation. Observations were collected on plant growth parameters, pod yield, and quality parameters. Descriptive statistics of different plant growth parameters were made. The higher SMP threshold (−20 kPa) and lower SMP threshold (−40 kPa) greatly reduced the yield and water-use efficiency. Considering the results, real-time soil moisture-based irrigation at the soil matric potential threshold level of −30 kPa with 120% of recommended dose of fertilizers through fertigation was recommended for attaining maximum green pea pod yield and water-use efficiency under semi-arid Inceptisols. [ABSTRACT FROM AUTHOR]

Pesticide treatment dramatically reduces crop loss and enhances agricultural productivity, promoting global food security and economic growth. However, owing to high accrual and persistent tendency, pesticides could create significant ecological consequences when used often. Lately, the perspective has transitioned to implementing biological material, environmentally sustainable, and economical strategies via bioremediation approaches to eradicate pesticides contaminations. Microalgae were regarded as a prominent option for the detoxification of such hazardous contaminants. Sustainable application and remediation strategies of pesticides pollutants in the agriculture system by microalgae from the past studies, and recent advancements were integrated into this review. Bibliometric strategies to enhance the research advancements in pesticide bioremediation by microalgae between 2010 and 2020 were implemented through critical comparative analysis of documents from Scopus and PubMed databases. As a result, this study identified a growing annual research trend from 1994 to 2020 (nScopus > nPubMed). Global production of pesticide remediation by microalgae demonstrated significant contributions from India (23.8%) and China (16.7%). The author's keyword clustering was visualized using bibliometric software (VOSviewer), which revealed the strongest network formed by "microalgae", "bioremediation", "biodegradation", "cyanobacteria", "wastewater", and "pesticide" as significant to the research topic. Hence, this bibliometric review will facilitate the future roadmap for many scholars and authors who were drawing attention to the burgeoning research on bioremediation of pesticides to counteract environmental impacts while maintaining food sustainability. [ABSTRACT FROM AUTHOR]

The Asian rice gall midge (Orseolia oryzae (Wood-Mason)) is a major insect pest in rice cultivation. Therefore, development of a reliable system for the timely prediction of this insect would be a valuable tool in pest management. In this study, occurring between the period from 2013–2018: (i) gall midge populations were recorded using a light trap with an incandescent bulb, and (ii) climatological parameters (air temperature, air relative humidity, rainfall and insulations) were measured at four intensive rice cropping agroecosystems that are endemic for gall midge incidence in India. In addition, weekly cumulative trapped gall midge populations and weekly averages of climatological data were subjected to count time series (Integer-valued Generalized Autoregressive Conditional Heteroscedastic—INGARCH) and machine learning (Artificial Neural Network—ANN, and Support Vector Regression—SVR) models. The empirical results revealed that the ANN with exogenous variable (ANNX) model outperformed INGRACH with exogenous variable (INGRCHX) and SVR with exogenous variable (SVRX) models in the prediction of gall midge populations in both training and testing data sets. Moreover, the Diebold–Mariano (DM) test confirmed the significant superiority of the ANNX model over INGARCHX and SVRX models in modeling and predicting rice gall midge populations. Utilizing the presented efficient early warning system based on a robust statistical model to predict the build-up of gall midge population could greatly contribute to the design and implementation of both proactive and more sustainable site-specific pest management strategies to avoid significant rice yield losses. [ABSTRACT FROM AUTHOR]

Phalaris minor Retz. (littleseed canarygrass) is the most problematic and herbicide-resistant weed in the rice-wheat cropping system in India. As such, it poses a severe threat to wheat yield and food security. A number of herbicidal and agronomic practices have been identified for the effective control of P. minor. These include crop rotation, crop establishment methods, herbicide spray technology, sowing time, weed seed harvest and effective herbicide mixtures. A population model of P. minor was built based on the life cycle of the species, herbicide resistance mechanisms and the effects of weed control practices. The model simulated the interactions of these factors and provided the best management recommendations for sustainably controlling this noxious weed species. Model results indicate that integration of chemical and non-chemical control methods was the most effective and sustainable strategy. For example, the integration of a happy seeder (a tractor-mounted mulching and sowing machine) with an effective post-emergence herbicide reduced the probability of weed control failure by 32% compared to the scenario with a rotavator and the same herbicide. Similarly, more conventional crop establishment methods such as a rotavator and conventional tillage could be accompanied by pre- or post-emergence applications of herbicide mixtures. Adoption of good herbicide spray technology and weed seed harvest delayed the onset of resistance evolution by up to four years. Furthermore, effective crop rotation such as the inclusion of sugarcane in place of rice in the summer season reduced the risk of resistance evolution by 31% within the 10 year simulation period. In addition to the scenarios using representative parameter values, the variability of model predictions was investigated based on some field experiments. The model provided a powerful tool for promoting Integrated Weed Management and the sustainable use of herbicides. Pragmatic ways of dealing with uncertainty in model prediction are discussed. [ABSTRACT FROM AUTHOR]

Agriculture is the principal basis of livelihood that acts as a mainstay of any country. There are several changes faced by the farmers due to various factors such as water shortage, undefined price owing to demand–supply, weather uncertainties, and inaccurate crop prediction. The prediction of crop yield, notably paddy yield, is an intricate assignment owing to its dependency on several factors such as crop genotype, environmental factors, management practices, and their interactions. Researchers are used to predicting the paddy yield using statistical approaches, but they failed to attain higher accuracy due to several factors. Therefore, machine learning methods such as support vector regression (SVR), general regression neural networks (GRNNs), radial basis functional neural networks (RBFNNs), and back-propagation neural networks (BPNNs) are demonstrated to predict the paddy yield accurately for the Cauvery Delta Zone (CDZ), which lies in the eastern part of Tamil Nadu, South India. The performance of each developed model is examined using assessment metrics such as coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), coefficient of variance (CV), and normalized mean squared error (NMSE). The observed results show that the GRNN algorithm delivers superior evaluation metrics such as R2, RMSE, MAE, MSE, MAPE, CV, and NSME values about 0.9863, 0.2295 and 0.1290, 0.0526, 1.3439, 0.0255, and 0.0136, respectively, which ensures accurate crop yield prediction compared with other methods. Finally, the performance of the GRNN model is compared with other available models from several studies in the literature, and it is found to be high while comparing the prediction accuracy using evaluation metrics. [ABSTRACT FROM AUTHOR]

Rice, the predominant food crop in India, is being grown traditionally with improper plant nutrient management mostly under the flooded situation. Recent advancement in research on crop science focuses on water-saving rice technologies for maximization in crop and water productivity under the backdrop of a shrinking water resource base for ensuring environmental and agricultural sustainability. Under this situation, an experiment was conducted in two consecutive years in a split-plot design keeping rice cultivation methodologies, viz., aerobic culture, System of Rice Intensification (SRI), and conventional flooded culture in main plots and integrated plant nutrient management (INM) treatments in sub-plots. The experiment was aimed at understanding the effects of different rice production systems and INM on nutrient content, uptake, and use efficiency. The change in soil quality parameters was also studied to understand the impact of crop establishment methods (CEM) and INM options. Significant reduction (p ≤ 0.05) in nutrient uptake and use efficiency was observed under aerobic culture compared to SRI and flooded method, although aerobic culture showed the highest physiological nitrogen use efficiency. Post-harvest available Fe status was significantly lower in aerobic rice (mean 10.39 ppm) compared to other crop establishment technologies; however, Zn status was higher in aerobic rice over the flooded situation. Although available potassium was not affected due to rice cultivation methods, available nitrogen and phosphorus status were influenced remarkably. Soil microbial quality was improved in aerobic rice in comparison to flooded rice. SRI proved to be the most efficient rice establishment method for enhancement in nutrient uptake, use efficiency, and enrichment of soil chemical and microbiological quality. Irrespective of crop culture, integrated plant nutrition in rice improved the nutrient uptake, use efficiency, and soil quality parameters. The study revealed that, under the alluvial soils of the Indo-Gangetic Plains of Eastern India, SRI can be considered as a water-saving rice production method. The method can also improve nutrient uptake, efficiency, and soil quality parameters if proper INM is adopted. [ABSTRACT FROM AUTHOR]

In the eastern part of India, rice as the most vital staple food crop supports as well the livelihood security of a vast population. Rice is mostly grown under conventional flooded culture without proper nutrient management. Crop performance, water productivity and economic profitability of rice cultivation need to be assessed under water-saving rice production methodologies with proper integrated plant nutrient management strategies using locally available low-cost nutrient sources. A field trial was conducted at the Adaptive Research Farm, Polba (58.57 m msl), Agriculture Department, West Bengal, India, during the rainy/wet seasons of 2014 and 2015 under aerobic culture, the system of rice intensification (SRI) and conventional flooded culture. The experiment was conducted to evaluate the influence of integrated plant nutrition and water-saving rice production methodologies on the crop performance and water productivity of rice and analyse the economic profitability of rice under different nutritional management and crop production methods such as aerobic culture, conventional flooded and SRI with an objective of sustainability in rice cultivation in the agroclimatic region. The results revealed that crop productivity significantly (p ≤ 0.05) varied from 4.68 t ha−1 (average yield recorded under aerobic culture) to 6.21 t ha−1 (average yield as achieved under SRI). Cultivation of rice under aerobic and conventional culture resulted in 24.6% and 20.9% yield reduction respectively as compared to SRI. Integrating 75% of the recommended dose of nitrogen (RDN) through chemicals with 25% RDN from vermicompost resulted in maximum crop productivity irrespective of crop culture. Aerobic rice culture registered maximum water economy in terms of both irrigation water productivity and total productivity. The study concludes that, for maximization of economic profitability, value cost ratio and partial factor productivity of nutrients the SRI method can be adopted along with integrated nutrient management (75% of RDN through chemicals with 25% RDN from vermicompost) in the lower Indo-Gangetic Plain Zone (IGPZ) of West Bengal, India. [ABSTRACT FROM AUTHOR]

Nitrogen management is vital for economic and environmental sustainability. Asynchrony of fertilizer application with crop demand along various nitrogen losses in Eastern India leads to low fertilizer efficiency in Kharif rice. At the same time, direct-sowing is gaining popularity due to water and labor scarcity. In an experiment between 2017–2018 in West Bengal, India, the main plots represented establishment methods: conventional transplanting, TPR; direct-seeded rice, DSR; and drum seeded rice, DRR; while subplots represented nitrogen management options: farmer's practice (FP), the state-recommended (SR), nutrient expert-based (NE), Green seeker-based (GS) and LCC-based (LCC) in a split-plot design with three repetitions. Plant growth, productivity, and profitability were evaluated. All indicators of growth or production were affected by establishment methods and by N-management options. The yield enhancement of TPR and DSR over DRR was 21.1 and 16.8%, respectively, while it was enhanced by 19.21, 14.71, 6.49, and 2.52% by GS, NE, LCC, and SR, respectively, over FP. The highest net return and return per rupee invested were recorded with DSR, while both GS and NE had better economics. The results suggest that the combination of DSR establishment with GS or NE requires further studies to find climate-smart management techniques in Kharif rice. [ABSTRACT FROM AUTHOR]

Annual, seasonal and intra-seasonal variations in rainfall affect crop production from land preparation to the realization of potential crop yield in a region. Particularly, the onset of the rainy season is most crucial for determining the sowing period. Statistical analysis (Modified Mann-Kendall aka MMK-test for trend and likelihood ratio test for shifting pattern) of 60 years rainfall of south interior Karnataka (SIK) inferred the presence of temporal variability in rainfall. There was a monotonic increase in rainfall of February, March, April, June and August months (a positive sign of MM-K (tau) value), with a negligible rate of change (Sen's slope towards zero). Upon seasonal analysis, there was a significant increase in winter, pre-monsoon and monsoonal rainfall as compared to post-monsoonal rainfall (higher Sen's slope for pre-monsoon), indicating a need for agronomic interventions for estimating an effective date of sowing for reducing risks of crop production. Further, the agro-climatic onset of cropping season was estimated by considering soil–crop–water relations. Earlier onset of cropping season was estimated based on thresholds of soil–crop–water relations, which highlights sowing of crops in advance (May 1st fortnight) instead of late (June 1st fortnight) to avoid crop losses due to early-season drought. [ABSTRACT FROM AUTHOR]

Sweet basil (Ocimum basilicum), a highly valuable medicinal crop, is extremely susceptible to Meloidogyne incognita infestation, leading to severe losses in yield and chemo-pharmaceutical quality. Currently, chemical nematicides are the only effective option for the disease management. However, high toxicity to non-target organisms and adverse impact on soil health motivated the look for ecofriendly alternatives. Here, bioinoculants (Bacillus megatarium ("BM"), B. subtilis ("BS")) were isolated from the rhizosphere of various medicinal and aromatic plants growing in Lucknow region, India. Their biocontrol effects were studied in O. basilicum plants that were invaded by M. incognita either in single or in consortium with Trichoderma harzianum ("TH") and their efficiency compared to chemical nematicide (carbofuran) and a microbial reference strain (Pseudomonas fluorescens). The results show that all bioinoculants enhanced the growth and oil yield production and increased the nutrient content of O. basilicum by significantly reducing M. incognita infestation by 46 to 72%. Among the strains, a consortium of BM and TH was the most potent treatment. The efficiency of these bioinoculants was not restricted to sterile soil condition but remained high also in natural soil conditions, indicating that enriching soils with rhizospheric microbes can be an effective alternative to chemical nematicides. [ABSTRACT FROM AUTHOR]

This study was conducted over 3 years in a salt-affected coastal rainfed lowland ecosystem. Farmers most commonly grow tall rice varieties in the wet season to cope with flash and/or stagnant floods, leading to large amounts of rice residue production. Most of the land remains fallow during the dry season because of increased salinity and scarcity of freshwater for irrigation. The study aims to provide options for increasing cropping intensity through management of crop residues (CR) and soil salinity, conservation of soil moisture, and reduction in production cost. The rice–maize rotation was assessed with rice as the main plot as (1) puddled transplanted rice (PTR) with CR of both rice and maize removed, (2) PTR and 40% CR of both crops retained, (3) dry direct-seeded rice (DSR) with CR of both crops removed, and (4) DSR with 40% CR of both crops retained. Maize in the dry season was supplied with different N levels as sub-plots—control (0 kg N ha−1), 80, 120, and 160 kg N ha−1. DSR, when combined with CR retention (DSR + R), reduced soil salinity. The increase in rice grain yield with CR retention (observed in second and third years) and crop establishment (higher in DSR versus PTR in the third year) was 16 and 24%, respectively. The cost of production increased by 17% (USD 605 ha−1) in PTR compared with DSR (USD 518 ha−1). CR retention reduced irrigation water requirement by 37% and N requirement by 40 kg ha−1 for hybrid maize. When CR was removed (−R), the N requirement for hybrid maize increased to 160 kg N ha−1 compared to when it was partially (40%) retained, where the requirement was 120 kg ha−1 with similar yields. Available N was highest under DSR + R (314 kg ha−1) and lowest under PTR − R (169 kg ha−1), and it also increased with increasing N application up to 120 kg ha−1 (+R) and 160 kg ha−1 (−R). The results of the study hold promise for increasing cropping intensity and farmers' incomes, with broader implications for increasing productivity on about 2.95 million hectares currently under a rice–fallow system in eastern India, and in coastal areas affected by similar conditions in South and Southeast Asia. [ABSTRACT FROM AUTHOR]

Grassland is a highly dynamic land use system and it provides vital ecosystem services, mainly consisting of carbon storage in the tropics and subtropics. The objective of this study was to delineate grassland in India according to soil characteristics and carbon pools in comparison to native forestland, and to discuss management strategies for improving soil carbon (SC) storage in grassland. A total of 675 paired datasets from studies on grassland and forestland in India generated during the period of 1990–2019 were used for meta-analysis study. The analysis shows that soil pH and bulk density (BD) in grasslands were greater by 1.1% and 1.0% compared to forestlands while soil organic carbon (SOC) declined by 36.3% (p < 0.05). Among carbon pools, labile carbon (LC), non-labile carbon (NLC), and microbial biomass carbon (MBC) were 35.5%, 35.3% and 29.5% lower, respectively, in the grassland compared to the forestland. Total carbon (TC) was 35.0% lower in the grassland than the forestland (p < 0.05). Soil carbon stocks (SCS) were 32.8% lower in the grassland compared to the forestland. In the grassland, MBC/SOC (%) from the surface layer and subsurface layer were lower by 2.4% and 8.5%, respectively compared to forestland. The percentage effect size was found to have decreased from surface soil to subsurface soil. Relative SCS loss and carbon dioxide equivalent emission from the grassland compared to forestland were 15.2% and 33.3 Mg ha−1, respectively (p < 0.05). Proper management strategies like agroforestry, legume introduction, silvipastoral system, fertilization, irrigation, and quality grass species could improve SC storage and reduce SCS loss in grassland. Overall, this study gives an idea that conversion of native forestland into grassland in India has declined the SC content and hence it is necessary to adapt proper strategies to manage the soil-atmosphere carbon balance. [ABSTRACT FROM AUTHOR]

Increasing productivity of maize while decreasing production costs and maintaining soil health are emerging challenges for the rice–maize system in South Asia. A range of integrated nutrient and weed management practices were tested in winter maize for their effects on yield, profitability, and soil health. The nutrient management treatments were a partial substitution of nitrogen with bulky (Farmyard manure; vermicompost) and concentrated organic manures (Brassicaceous seed meal, BSM; neem cake), whereas weed management practices compared chemical controls only versus an integrated approach. The N supplementation through BSM diminished the weed growth by reducing weed N uptake, and enhanced the maize crop uptake of nutrients. As compared to the sole chemical approach, atrazine-applied pre-emergence followed by hoeing reduced weed density by 58 and 67% in years 1 and 2, respectively. The N supplementation through BSM resulted in the maximum yield of maize grain (6.13 and 6.50 t ha−1 in year 1 and year 2, respectively) and this treatment increased yield in year 2 compared to N application through synthetic fertilizer. Hoeing in conjugation with herbicide enhanced the maize grain yield by 9% over herbicide alone. The maximum net return and economic efficiency were achieved with the application of BSM for N supplementation, together with the integrated weed management practice. [ABSTRACT FROM AUTHOR]

Immediate yield loss information is required to trigger crop insurance payouts, which are important to secure agricultural income stability for millions of smallholder farmers. Techniques for monitoring crop growth in real-time and at 5 km spatial resolution may also aid in designing price interventions or storage strategies for domestic production. In India, the current government-backed PMFBY (Pradhan Mantri Fasal Bima Yojana) insurance scheme is seeking such technologies to enable cost-efficient insurance premiums for Indian farmers. In this study, we used the Decision Support System for Agrotechnology Transfer (DSSAT) to estimate yield and yield anomalies at 5 km spatial resolution for Kharif rice (Oryza sativa L.) over India between 2001 and 2017. We calibrated the model using publicly available data: namely, gridded weather data, nutrient applications, sowing dates, crop mask, irrigation information, and genetic coefficients of staple varieties. The model performance over the model calibration years (2001–2015) was exceptionally good, with 13 of 15 years achieving more than 0.7 correlation coefficient (r), and more than half of the years with above 0.75 correlation with observed yields. Around 52% (67%) of the districts obtained a relative Root Mean Square Error (rRMSE) of less than 20% (25%) after calibration in the major rice-growing districts (>25% area under cultivation). An out-of-sample validation of the calibrated model in Kharif seasons 2016 and 2017 resulted in differences between state-wise observed and simulated yield anomalies from –16% to 20%. Overall, the good ability of the model in the simulations of rice yield indicates that the model is applicable in selected states of India, and its outputs are useful as a yield loss assessment index for the crop insurance scheme PMFBY. [ABSTRACT FROM AUTHOR]

Sorghum is an important dual-purpose crop of India grown for food and fodder. Prevailing weather conditions during the crop growth period determine the yield of sorghum. Hence, the crop yield forecasting models based on weather parameters will be an appropriate option for policymakers and researchers to develop sustainable cropping strategies. In the present study, six multivariate weather-based models viz., least absolute shrinkage and selection operator (LASSO), elastic net (ENET), principal component analysis (PCA) in combination with stepwise multiple linear regression (SMLR), artificial neural network (ANN) alone and in combination with PCA and ridge regression model are examined by fixing 90% of the data for calibration and remaining dataset for validation to forecast rabi sorghum yield for different districts of Karnataka. The R2 and root mean square error (RMSE) during calibration ranged between 0.42 to 0.98 and 30.48 to 304.17 kg ha−1, respectively, without actual evapotranspiration (AET) whereas, these evaluation parameters varied from 0.38 to 0.99 and 19.84 to 308.79 kg ha−1, respectively with AET inclusion. During validation, the RMSE and nRMSE (normalized root mean square error) varied between 88.99 to 1265.03 kg ha−1 and 4.49 to 96.84%, respectively without AET and including AET as one of the weather variable RMSE and nRMSE were 63.48 to 1172.01 kg ha−1 and 4.16 to 92.56%, respectively. The performance of six multivariate models revealed that LASSO was the best model followed by ENET compared to PCA_SMLR, ANN, PCA_ANN and ridge regression models because of reduced overfitting through penalisation of regression coefficient. Thus, it can be concluded that LASSO and ENET weather-based models can be effectively utilized for the district level forecast of sorghum yield. [ABSTRACT FROM AUTHOR]

Peanuts (Arachis hypogaea L.) are the world's fourth-most important source of edible oil and the third-most valuable source of high-quality vegetable protein; they also contain carbohydrates, fatty acids, vitamins, and minerals essential for good human nutrition. Peanuts area particularly valuable crop in tropical and subtropical regions. While the demand for peanuts is increasing globally, there is a significant gap in nitrogen supply and demand in peanut production systems. To alleviate this, nitrogen fertilizers are often applied indiscriminately; this practice leads to the deterioration of indigenous soil fertility and to a long-term decline in crop productivity. Considering these aspects of soil health, a field study was conducted over two consecutive winter (November–March) seasons in 2015–2016 and 2016–2017 at the research farm of the agricultural university Bidhan Chandra Krishi Viswavidyalaya in West Bengal, India. This study examined supplementing different levels of nitrogen fertilizer with rhizobium and soil mulch in an irrigated peanut crop. The effects of these management interventions were evaluated in terms of crop productivity, nutrient dynamics, soil moisture, and the soil microbial activity. Peanuts grown with the 100% recommended dose of nitrogen, which was applied with rhizobium and grown under polythene mulching, recorded the highest average pod yield (3.87 and 3.96 t ha−1 in 2015–2016 and 2016–2017) and average kernel yield (2.88 and 2.99 t ha−1) in both growing seasons. This treatment also resulted in the greatest accumulation of nitrogen, phosphorous, and potassium by the peanut plants. In contrast, the maximum soil moisture distribution and the greatest total root zone moisture content were observed in the treatment with only rhizobium under the polythene mulch (i.e., no nitrogen was applied). The populations of soil bacteria and rhizobia were highest in the treatment where nitrogen fertilizer was applied to the crop at 75% of the recommended rate combined with rhizobium and under polythene mulch. After two cropping seasons, the peanut crop grown under polythene mulch with rhizobium and with nitrogen fertilizer applied at either the full recommended rate or 75% of this rate performed best in terms of crop productivity, soil nutrient dynamics, and soil moisture. [ABSTRACT FROM AUTHOR]

The rice–wheat cropping system being the backbone of food security in South-Asia has resulted in soil health deterioration, declining water table, and air pollution affecting livability index of the region. The effect of rice residue retention (RRR), irrigation levels and foliar application of K on wheat grain yield (GY), water use efficiency (WUE) and profitability was tested over three years. RRR increased wheat GY (5224 kg ha−1), above-ground biomass (AGBM = 11.9 t ha−1), tillers per square meter (TPM = 469) and grains per meter square (GrPMS = 13,917) significantly. Relative water content (RWC = 93.8) and WUE (2.45 k gm−3) were also increased significantly by RRR. Consequently, profitability (Net return = 624.4 $ and Benefit to cost (B:C) ratio) was enhanced. Foliar application of K enhanced GY (5151 kg ha−1), AGBM (12 t ha−1), RWC (94.1), SPAD (52.2), WUE (2.40 kg m−3), net returns (625.2 $) and BC ratio (1.62) significantly. RRR increased GY (15.66%) and WUE (17.39%) with additional revenue of 151 $ with only one irrigation at the CRI stage (ICS). RRR adopted over 10% of the area can earn 187 million-US$ annually. RRR if adopted over existing practice on a large area would reduce environmental degradation with an enhanced income to small and marginal farmers. [ABSTRACT FROM AUTHOR]

This study evaluated the potential distribution of the potato tuber moth. This species severely impacts global potato production, especially in China and India, which have the world's largest potato production. We developed two indices considering host plant availability and production in addition to climatic suitability, which was simulated using the CLIMEX model. Thus, three different indices were used to project potential distribution of the potato tuber moth under a climate change scenario: (1) climatic suitability (ecoclimatic index (EI)) (EIM), (2) climatic suitability combined with host plant availability (EIN1), and (3) climatic suitability combined with host plant production (EIN2). Under the current climate, EIM was high in southern India and central to southern China, while EIN1 and EIN2 were approximately 38% and 20% lower than EIM, respectively. Under the Special Report on Emissions Scenario A1B, the potato tuber moth would probably not occur in India, but its distribution could be extended to the north, reaching N47°. The areas with the highest climatic suitability by potato tuber moth based on three indices were Sichuan and Karnataka in response to climate change. These areas require adequate pest control, such as prevention of spread through transport of potato seed or by using cold storage facilities. [ABSTRACT FROM AUTHOR]

Soils in tropical croplands are becoming degraded because of soil carbon (C) depletion. Local farmers in South India use a specific management of traditional cultivation, i.e., broadcast seeding. However, for sustainable C management, there is no quantitative data on the CO2 flux under this management. Our objectives were to (1) estimate the annual CO2 flux, and (2) evaluate the effect of traditional cultivation management (seeding rate) on the CO2 flux. Our field experiment was conducted in South India, from 2015 to 2017, including two cultivation periods with four cultivation management treatments (traditional cultivation management plot (T), fixed density plot (FD), no thinning plot (NT), and bare plot (B)). The seeding rate in the FD plot was ca. 50% of the T plot. We applied 1.1 Mg C ha−1 farmyard manure just before the experiment as a C input. We found that broadcasting, thinning, and cultivation increased soil moisture, while the CO2 efflux rate showed no significant difference between treatments throughout the experimental period. This indicates that cultivation management did not affect the CO2 flux. The total CO2 fluxes for two years were estimated at 2.2–2.7 Mg C ha−1. Our results indicate that it is necessary to apply larger or more frequent C inputs to prevent C depletion. [ABSTRACT FROM AUTHOR]