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Rice (Oryza sativa) is a staple food of more than half of the population of the world and provides food security and livelihoods for millions of population. Direct seeding of rice (DSR) refers to the process of direct sowing the seeds in the field rather than by transplanting seedlings from the nursery. Direct seeded rice is an age old practice and before the introduction of green revolution in India. Rainfed rice was often broadcasted into moist soil and crops were highly prone to weed competition resulted into low yield. Rice ecosystems and establishment methods determined the weed spectrum and degree of infestation in rice field (DSR). Weeds are considered as a major biological constraint in direct seeded rice. In direct seeded rice, weed management depend on weed flora, critical period of weed control, availability of water and method to be adopted. Integrated weed management (IWM) is essential to achieve the long term, sustainable and economic management of weeds in direct seeded rice. The literature regarding the direct seeded rice, critical period of crop weed competition, different types of weed flora and different methods for the effective and sustainable management of weeds in direct seeded rice are reviewed in this paper. [ABSTRACT FROM AUTHOR]

Purpose: The paper investigates the effects of climate change along with ecological and carbon footprint on rice crop production in India during 1982–2016. Design/methodology/approach: The autoregressive distributed lag (ARDL), canonical cointegration regression (CCR) and fully modified ordinary least square (FMOLS) models are used in the paper. Findings: A long-run relationship is found between climate change and rice production in India. Results report that ecological footprint and carbon footprint spur long-term rice production. While rainfall boosts rice crop productivity in the short term, it has a negative long-term impact. Further, the findings of ARDL models are validated by other cointegration models, i.e., the FMOLS and CCR models. Research limitations/implications: This study provides insights into the role of ecological footprint and carbon footprint along with climate variables in relation to rice production. Originality/value: In the literature, the effects of ecological and carbon footprint on rice production are missing. Therefore, this is the first study to empirically examine the impact of climate change along with ecological footprint and carbon footprint on rice production in India. [ABSTRACT FROM AUTHOR]

Large-scale private real estate projects in the past few decades in vast areas of increasingly varied scales have been created that were once sparsely inhabited agricultural land and wetlands in the remote locations of these urban areas. This paper examines the reasons for India's peripheralization of real estate megaprojects. Such projects are typically constructed on agricultural land, notably paddy fields and wetlands. Developers' site selections are mostly influenced by the low cost of land and future development potential. In contrast to the disarray of existing urban spaces, "bypass urbanism" creates restricted and unique city spaces that allow more contented or high-status lifestyles. They avoid large parts of the city area as part of their daily lives, reinforcing socio-economic isolation, peripheralization, and uneven urban development. With the help of two case studies, this paper explores how peripheralization has created a restricted and exclusive space that facilitates middle-class life while bypassing and neglecting existing urban areas. This massive bypass urbanism constitutes a new quality of urban growth with far-reaching and uncountable repercussions, resulting in the creation of islands and the reshuffling of the entire metropolitan region. [ABSTRACT FROM AUTHOR]

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Rice is the major food grain for many countries in this world, in particular South Asian countries such as Pakistan, India, Bangladesh, Sri Lanka, Myanmar, Thailand, etc. India is one of the leading producers of rice, with agriculture contributing 14% to 15% to the Gross domestic product (GDP). Detection of paddy field requires constant monitoring of a region throughout the year. Hence, we use dual-polarized Sentinel-1 Synthetic Aperture Radar (SAR) data with 20 m resolutions for our study. In this paper, we propose a semi-supervised algorithm that detects paddy fields in various seasons. The technique is divided into two parts, unsupervised and supervised. Feature extraction layers of the Visual Geometry Group (VGG16) model are used to segregate patches into five clusters using an entropy-based loss function. Depending on the availability of the ground truth, data is sampled (stratified sampling), and only a certain amount of data is further used for the supervised section. Clusters showing higher similarity (Jaccard/Tanimoto test) with the paddy or nonpaddy classes are connected to a three-layer neural network used for the supervised method. This has been tested on two study sites using 10 data sets, five from 2018 to 2019, each. The highest accuracy reported for 2018 and 2019 is 85.61% and 84.92%, respectively. The two sites are selected from different districts of West Bengal, India. Our model has also shown higher generalization capability against the conventional-supervised models. [ABSTRACT FROM AUTHOR]

Crop yield predictions are important for crop monitoring and agronomic management. The traditional methods for yield predictions are complicated and resource consuming. With the availability of affordable handheld imaging and computing devices, the image processing-based yield prediction methods are gaining popularity. In this work, RGB images of rice panicles are captured using DSLR camera with simple background and processed to determine the panicle area in terms of number of pixels. A machine learning-based model is developed to make predictions for rice yield. The model is trained to make predictions on unseen data. Various machine learning-based regression algorithms including decision tree, random forest, support vector machine, and convolution neural network are tested. The experiments are performed on a publically available dataset from China as well as on a self-acquired dataset in India. The results have shown that image processing and machine learning-based methods can make yield predictions satisfactorily as evident from the coefficient of determination ( R 2 ) that ranges 0.80–0.97 for different cultivars. The prediction error is determined in terms of root mean square error (RMSE) and mean absolute error (MAE). RMSE for different methods lies between 0.14 and 0.40, whereas MAE varies from 0.11 to 0.30. Among the tested algorithms, linear regression achieved the best precision with R 2 = 0.97, RMSE = 0.14, and MAE = 0.11. [ABSTRACT FROM AUTHOR]

This study aimed to check how herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) affects the production of EPS and its composition, growth, and biomass, as well as morphology in a cyanobacterial species isolated from a rice field in Meghalaya, India. Compared to the control cells, the growth of the organism measured in terms of chlorophyll concentration increased after being exposed to 10 and 20 ppm 2,4-D. However, cultures treated with 30 and 40 ppm experienced a decrease in their growth. Likewise, the biomass content of the organism experienced a minuscule increase in content upon exposure to 10 and 20 ppm 2,4-D but was compromised upon exposure to higher doses. When exposed to 10 ppm, the total EPS content, which includes the RPS and CPS content, showed a substantial increase. Maximum EPS production was seen at 20 ppm 2,4-D. However, exposure to 30 and 40 ppm 2,4-D, EPS production in the organism experienced a significant reduction, respectively. All components of EPS, such as uronic acid, neutral sugar, and proteins, individually showed an increase in 10 and 20 ppm 2, 4-D. A similar trend was seen in the organism's bio-flocculating activity, which increased when exposed to 10 and 20 ppm, respectively. However, this activity in cells exposed to 30 and 40 ppm 2,4-D was severely reduced. Not only the content of EPS but the rate of EPS production was also enhanced in lower concentrations of 2,4-D. Although exposure to 30 ppm 2,4-D, the rate of EPS production was not significantly compromised, 40 ppm exposure adversely affected the rate of EPS production. Furthermore, visualization using scanning electron microscopy revealed the morphological changes induced by the herbicide 2,4-D. [ABSTRACT FROM AUTHOR]

In winter, the paddy residues become wet during morning and late evening due to dew, which restricts the operation of sowing machines (Happy Seeder and Super Seeder) into paddy residues, as wet residues do not slide on furrow openers/tines. A PAU Smart Seeder (PSS) was developed and evaluated for a four-wheel tractor that can sow wheat with optimum crop establishment in combined harvested rice fields. The PSS were evaluated for its performance under varying straw load, forward speed, and rotor speed in terms of fuel consumption, field capacity, seed emergence, and grain yield. The crop establishment and wheat yield of PSS was also compared with the existing straw management machines Happy Seeder (HS) and Super Seeder (SS) under heavy paddy residue conditions. The effect of the straw load was more pronounced on dependent variables than the effect of the speed index. PSS performance was best at a forward speed of 2.6 km h−1, rotor speed of 127.5 rpm, and a straw load of 6 t ha−1. Average fuel consumption using PSS was lower than SS but higher than HS. Wheat emergence was higher by 15.6 and 25.7% on the PSS plots compared to HS and SS, respectively. Average wheat grain yield in PSS plots was significantly higher by 12.7 and 18.9% than SS and HS, respectively in one experiment, while the grain yield was similar for both PSS and HS in other experiments. PSS has a novel mechanism to manage paddy straw and simultaneously sow wheat into a heavy straw load (> 8 t ha−1) mixture of anchored and loose straw. In conclusion, PSS showed promise for in-situ management of rice straw as it eliminates most of the operational problems encountered by the existing seeders (HS and SS). [ABSTRACT FROM AUTHOR]

Introduction: The seeds of jackfruit are often overlooked and discarded globally, leading to the underutilization of this valuable resource. This study explored the potential of utilizing underutilized jackfruit seeds as an alternative source of human subsistence by investigating the availability of jackfruit, the utilization and underutilization of seeds at the household level, and the types of subsistence activities in the community. Methods: We used a case study of Byse village in Karnataka, India, to understand this topic. A mixed research approach was used. First, a descriptive research design was employed to collect and describe the data, while a correlation design was used to examine the relationships among variables related to jackfruit seed utilization. Second, a bibliometric analysis was conducted to explore global trends in jackfruit seed utilization. Results and Discussion: The findings indicated that agriculture, particularly arecanut farming followed by paddy rice cultivation, was the primary means of subsistence in the community. While human consumption of jackfruit seeds is statistically significant, it has a detrimental effect on seed utilization in the community (r = -0.295, p = 0.008). The study also revealed that consuming jackfruit seeds in a semidry form had a positive and significant influence (r = 0.345, p = 0.002) compared to eating them in a fresh form. Consequently, more focus could be placed on encouraging the consumption of semidry jackfruit seeds as a preferred option among residents. Despite the abundance of jackfruits, their seeds are rarely used, with a mean utilization score of 1.77. Since jackfruit seeds are limited in their application and are readily available, they could be utilized as an alternative source for sustainable human subsistence. sustainable human subsistence. [ABSTRACT FROM AUTHOR]

In the context of climate change, the Indian agricultural sector treads in a certain duality between promoting food security in response to the increasing population, but at the same time in ensuring environmental sustainability, and sustained economic growth, especially in developing countries like India. The concept of Climate Smart Agriculture (CSA) emerged from the recognition of this duality. Using the Indian Social Accounting Matrix (SAM) 2017–18, the economy-wide effects arising out of agricultural interventions were estimated, keeping accord with the impacts on sectoral outputs and household incomes from the adoption of varying CSA interventions such as Conservation Agriculture, System of Rice and Wheat Intensification (SRI-SWI) and Natural Farming, fitting the three-pillared criterion of CSA—(1) Productivity (2) Adaptation and (3) Mitigation. Additionally, a shift in cropping patterns from Paddy and Wheat to less emission-intensive crops was also studied. Results show that SRI-SWI provides the highest economy-wide impacts while accounting for lower GHG and water footprint. Alternative crops such as Maize, Sorghum, and Millet have minimal increase in income and output effects while having lower water and carbon intensity compared to rice and wheat. The current study would sensitize policymakers to prioritize suitable policy and institutional measures for upscaling climate smart interventions in India. [ABSTRACT FROM AUTHOR]

Purpose: The study unravels the effects of climate-induced variations in staple crop yields on various migratory inflows in India while adjusting for seasonal weather and sociodemographic factors. Design/methodology/approach: The instrumental variable approach is used to assess the potential effects of climate and nonclimate parameters on various migration types, exploiting panel data at the district level from the 2001 and 2011 Census years, with agriculture acting as the mediator. Findings: As weather-driven variations in rice and wheat yield increase by 10%, the share of migration within and between districts to population decreases by 0.017 and 0.002, respectively. However, rice and wheat yields increase by 494.60 and 524.40%, respectively, with a marginal increase in the share of migration within states to population. Also, the elasticities of disadvantaged groups, literate locals and agricultural workers vary for different relocations. Originality/value: The current study affirms climate migration through the agricultural channel at a finer spatial scale, asserting the sensitivity aspect of disparate movements to periodic weather and heterogeneous clusters. This is critical for effectively implementing targeted public policies in the face of increasing climate risks. Peer review: The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-10-2022-0710 [ABSTRACT FROM AUTHOR]

Rice is a staple food for the vast majority of the world's population and one of the world's largest consumers of freshwater. Unfortunately, climate change will further worsen the demand for blue water demand, particularly for rice cultivation needs to be closely monitored. Our study assessed the spatial water footprint (WF) of rice for the valley region of Manipur using Moderate Resolution Imaging Spectro-radiometer Evapotranspiration (MOD16) and Climate Hazards Group Infrared Precipitation with Station (CHIRPS) datasets. In addition, rice's economic water productivity of green and blue water was evaluated. Results showed an average spatial WF ranging from 772.14 to 1456.23 m3/tonne. According to data comparing the national average, 90% of the valley area has a lower WF value than the country as a whole. The green and blue WF of rice ranges from 596.62 m3/tonne to 673.42 m3/tonne and 65.79 m3/tonne to 767.65 m3/tonne, respectively. The spatial variation of the blue WF is due to the amount of rainfall and irrigation application within the study area. The green economic water productivity is getting lower than the blue economic water productivity due to green water's lesser economic scarcity than blue water. This study can help plan crop allocation in favour of water availability by water management authorities on economic value calculations. [ABSTRACT FROM AUTHOR]

The Taliye landslide, a hill slope debris flow, is one of the recent large-scale landslides in India in terms of mortality and socio-economic predicaments. In general, the Taliye area exhibits a moderately dissected plateau relief, and the landslide was initiated from a north-westerly slope of a west trending major ridge and flowed through a paddy field to bury houses located just below it. The landslide had a total runout of 563 m and maximum width of 230 m at the toe. The heavy rainfall and presence of a narrow stream may be the prime triggering factors, but the affected area had also been exposed to human interference for farming as well as for habitation. Given its socio-economic relevance and landslide proneness of this area, a post-event engineering geological investigation and numerical modelling of this landslide have been carried out to have a closer look at its type, causes of failure, back calculation of run-out characteristics, as well as to calibrate frictional parameters for this area. The numerical modelling package, rapid mass movements (RAMMS) was used to undertake back analysis of this debris flow by referring the original flow shape. For the precise preference of Voellmy frictional parameters, dry-Coulomb friction (µ) and viscous-turbulent friction (ξ) coefficients, this study applies the popular receiver operative characteristics (ROC) technique as the model validation tool. The landslide may have initiated as a talus or translational failure of shallow soil on the hillock, but later might have transformed into a debris flow by entraining materials from the paddy field. Amongst the different combinations of frictional parameters, the model with µ of 0.06 m/s2 and ξ of 1450 m/s2 has emerged as the best with an area under the curve (AUC) value of 0.883 for the ROC assessment. With these calibrated frictional parameters, the maximum flow velocity of this debris flow was simulated to be in the order of 5.26 m/s taking place at the middle reaches, and the maximum flow velocity and pressure were derived as 21 m/s and 0.92 kPa, respectively, concentrated in the hillock zone. Although it was a rain-induced failure, the investigation suggests that improper slope management practices might have amplified its magnitude and got manifested as devastating landslide. Therefore, human activities in these hilly regions shall be supported with systematic landslide hazard evaluation, and here in this case, the calibrated frictional parameters may be useful for debris flow modelling and landslide risk reduction in the area. [ABSTRACT FROM AUTHOR]

The presence of heavy metals (HM) and trace elements (TE) in soil and rice can be either beneficial or harmful. Hence, assessment of the HM and TE present in them is of prime importance for proper health risk management. As a first-hand report, an assessment of the TE and HM in paddy fields and rice grains was undertaken to evaluate health-related issues after consuming local rice grains from Champhai, North Vanlaiphai, and Kolasib of Mizoram, India. The concentrations of TE and HM in paddy fields could be ranked in the order Fe > Zn > Mn > Cu > Ni > As, and no trace amounts of Cd and Pb were found. In soils and rice, all the elements were determined to be below permitted limits. A significant difference (p < 0.05) was found when the concentration of HM and TE in the soil and rice were compared. The Health Risk Index (HRI) value of rice consumers for all the study sites was less than 1 in all cases except for Ni from Champhai rice (1.6) suggesting cultivars from Champhai might pose some negative impacts on health and sought for better management system. [ABSTRACT FROM AUTHOR]

The main food crop in India is rice; it is typically farmed using poor plant nutrition management, mostly in flood-prone areas. In order to maximize crop and water productivity against the backdrop of dwindling water resources, crop science research has recently made strides that are focused on water saving rice technology and appropriate nutrient management strategies employing locally accessible, affordable fertilizer sources. This is done to ensure the sustainability of agriculture and the environment. Presently, the growing rice in aerobic conditions is significant challenge due to limited nutrient availability. With reduced soil moisture, nutrient uptake is hindered by lower rates of delivery to the roots through mass flow and diffusion. Nitrogen, being one of the most essential nutrients, plays a critical role in enhancing the growth and yield of aerobic rice and also the Indian soil already deficit of nitrogen. However, applying too much or too little nitrogen is ineffective, particularly under alternate wetting and drying conditions. To maximizing the rice growth, root development, yield, and nitrogen uptake in aerobic systems through the method, timing and quantity of nitrogen application must be carefully considered. Based on discussed reviews on different studies, it is concluded that applying of nitrogen is an optimum quantity with three to four equal splits can maximize the plant height, leaf area index, crop growth rate, dry matter production, number of tillers/ m², root length, root volume, number of panicles/m², number of filled grains/panicle, panicle length and yield of aerobic rice. [ABSTRACT FROM AUTHOR]

To feed the burgeoning population, the cultivation of rice is exploited on low fertility soils, which are otherwise not fit for its cultivation. To enhance the fertility status of such soils, the nutrient-enriched bio-compost play vital role in maintaining the soil productivity and yield sustainability. Field experiments were conducted on sandy loam soil for two years (2016–2017 and 2017–2018) to evaluate the impact of different combinations of N (nitrogen)-, P (phosphorus)-, and K (potassium)-enriched bio-compost with inorganic nitrogen, phosphorus and potassium fertilizers (NPK) on crop productivity, nutrient uptake, and soil fertility by rice under rice-wheat system. The results reported that growth parameters, yield attributing characters, grain and straw yield of rice improved significantly by different NPK-enriched bio-compost treatments. Rice grain yield increased significantly, that is, 4350 kg ha−1 with the application of 150% NPK over recommended fertilizer (3360 kg ha−1). Also, plant growth parameters and yield attributing characters improved with application of bio-compost applied @ 4 t ha−1. The NPK content in grains and their buildup in soil were significantly higher in treatments where 25% NPK were substituted through NPK-enriched bio-compost and 75% NPK through inorganic fertilizers. Overall, it is concluded that integrated use of 25% nutrients through NPK-enriched bio-compost and 75% nutrients through NPK inorganic fertilizers is the best option for the maintenance of soil health and sustainable rice yield. [ABSTRACT FROM AUTHOR]

The present study describes the allotype of Conocephalus (Anisoptera) hilliFarooqi & Usmani, 2019, for the first time from India. The species C. (Anisoptera) hilli was collected along with C. maculatus and C. longipennis in the rice fields from Uttar Pradesh states of India. A brief diagnosis of the genus, subgenus and species and key to species is provided. Digital images and distribution map of the species are also provided. All specimens are deposited in the Department of Zoology, Aligarh Muslim University, Aligarh for posterity. [ABSTRACT FROM AUTHOR]

103 bacterial isolates obtained from 8 ethnomedicinal plants in Manipur, India were studied for antifungal and plant growth promoting (PGP) activities. Forty-six (46), out of 62 antifungal isolates, showed potent activities against R. solani. Since R. solani (RS), a sheath blight pathogen, threatens rice yields worldwide, the present study was aimed at discovering promising bioinoculants with anti-RS and PGP potential on rice. Twenty-nine (29) endophytic isolates exhibiting promising anti-RS and PGP activities were subjected to seed vigor assays on rice (var. Jatra) and 16 were found to enhance rice seedling vigour by 70% or more over the control. Four (4) strains, Streptomyces sp. (AcRz21), Alkalihalobacillus sp. (PtL11), Bacillus sp. (TgIb5), and Priestia sp. (TgIb12) with the highest vigor indices were studied for growth promotion of rice in field conditions under pathogen-challenged and pathogen-free conditions. These bioactive strains were able to significantly enhance root and shoot biomass and reduce lesion heights caused by R. solani. [ABSTRACT FROM AUTHOR]

The study aims to understand the species composition and habitat preferences of the spiders of the family Tetragnathidae in rice agroecosystem of Kuttanad. Surveys were carried out for a period of five months from July to November 2020. A total of thirteen tetragnathid species were collected from paddy fields and their nearby areas following organic way (do not use any pesticide) and a total of nine species collected from rice fields with its surroundings which use chemical pesticides. It was observed that the ecological guild structure of these spiders was based on foraging behaviour in relation to the height of the rice plant. [ABSTRACT FROM AUTHOR]

The purpose of this work is to assess the soil fertility for Tulaipanji rice cultivation in Kaliyaganj C.D. Block using the Analytic Hierarchy Process (AHP) and Machine learning algorithms along with the field survey data and GIS. A total of 40 soil samples from Tulaipanji rice fields (from 0 to 40 cm depth) have been randomly collected for the analysis of the soil health condition. For the purpose of assigning ratings to the parameters, ten experts' opinions were taken into account. The final soil fertility map indicates that 18.01% of the land is in excellent health condition to support Tulaipanji cultivation. The artificial neural networks (ANN), support vector machine (SVM), and Bagging models-based suitability analysis was also done using geo-spatial and soil data for Tulaipanji cultivation. Nevertheless, the ANN is the more appropriate model for locational analysis of Tulaipanji cultivation. The ANN-based findings show that areas of 25.8% (77.89 sq. km) are excellent for growing Tulaipanji rice, about 22.01% (66.45 sq. km) are highly suitable, 19.84% (59.90 sq. km) are moderately suitable, 21.19% (63.97 sq. km) are low suitable and 11.16% (33.69 sq. km) are not suitable for Tulaipanji rice cultivation. The receiver operating characteristic (ROC) curve depicts that the applied models have a high degree of accuracy. This endeavour will aid much in the soil fertility and site suitability assessment that will aid local government officials, academics, and the framers, to utilize the lands in a scientific way. [ABSTRACT FROM AUTHOR]

Two Commelinaceae weeds, Commelina benghalensis L. and Murdannia nudiflora (L.) Brenan, are abundant in rice fields of India. Larvae and adults of Lema praeusta (Fab.) (Coleoptera: Chrysomelidae) voraciously consume these two weeds. Synthetic herbicides are applied to control both weeds, but applications of these substances have harmful effects in environment and beneficial organisms. So, it is necessary to use native biocontrol agent to control these weeds. Hence, an attempt has been made to find volatile organic compounds (VOCs) from both weeds causing attraction of L. praeusta. Behavioural responses of L. praeusta towards volatile blends from undamaged (UD), insect‐damaged (ID: plants after 6 or 48 hr of continuous insect feeding) and mechanically damaged (MD) plants were conducted by Y‐tube olfactometer bioassays. Benzyl alcohol was predominant in VOCs of UD plants and M. nudiflora after 48 hr of insect feeding. Benzyl alcohol and cuminaldehyde were both predominant in VOCs of C. benghalensis after 48 hr of insect feeding. Females were more attracted towards volatile blends from plants after 48 hr of insect feeding compared to undamaged plants. Females showed attraction towards a synthetic blend of seven compounds—7.28 µg (Z)‐3‐hexen‐1‐ol, 0.93 µg trans‐isolimonene, 19.18 µg benzyl alcohol, 0.16 µg undecane, 1.07 µg 1‐nonanol, 1.23 µg 1‐undecanol and 0.47 µg 1‐eicosene resembling the amounts released by C. benghalensis after 48 hr of insect feeding during 1 hr or a synthetic blend of six compounds—18.10 µg benzyl alcohol, 0.25 µg undecane, 0.56 µg 1‐nonanol, 1.37 µg 1‐undecanol, 0.35 µg 1‐eicosene and 2.19 µg phytol resembling the amounts released by M. nudiflora after 48 hr of insect feeding during 1 hr. This study concludes that both blends could be used to attract the biocontrol agent during early vegetative period of these two weeds, which could lead to eradication of weeds from rice fields. [ABSTRACT FROM AUTHOR]

Aims: To characterize the geo‐distinct isolates of Ustilaginoidea virens for morpho‐molecular and mating‐type locus diversity. Methods and Results: Sixty‐one isolates of U. virens collected from Southern India exhibited significant diversity in mycelial width (3·45–5·50 µm), colony colour (yellow, pale yellow, and white), and growth pattern (thick leather mat, raised‐fluffy, flat‐fluffy, and raised). Field‐borne chlamydospores of each isolate were significantly smaller in size (3·34–5·26 µm2) compared to those formed on culture media (18·6–100·89 µm2). The phylogenetic study based on internal transcribed sequences revealed two clusters; however, most isolates (n = 54) were grouped in cluster‐I, indicating common ancestral origin. We also identified 42 haplotypes; among them, Hap_3 has the highest number of isolates (n = 19). Mating‐type locus (MAT1) analysis revealed all sixty‐one isolates as heterothallic, wherein 37 and 24 isolates belonging to MAT1‐1‐1 and MAT1‐2‐1 heterothallic mating types, respectively. The microsynteny analysis of MAT1 loci of one of the Indian strain (Uv‐Gvt) along with Uv‐8b (China) strain revealed synteny conservation at MAT1 locus, which is flanked by conserved genes SLA2 and a hypothetical protein in the upstream and APN2, COX12 and APC5 in the downstream of the locus. Conclusions: Morpho‐molecular study revealed the significant diversity among geo‐distinct isolates, and MAT1 loci analysis indicated the distribution of heterothallic mating types in south Indian paddy fields. And also, complete synteny conservation between Indian and Chinese strain was observed at the MAT1 locus. Significance and Impact of the Study: This is the first report describing the sexuality of Indian strains of the U. virens, which would help better understand the genetic diversity of the U. virens prevailing in Southern India and aid in developing resistant rice cultivars against this pathogen population. [ABSTRACT FROM AUTHOR]

Carbon (C) occluded in phytoliths is stable and an important source of long-term C storage into the agroecosystems. As a silicon (Si) accumulator crop, rice produces a large amount of phytolith occluded carbon (PhytOC) and which plays a crucial role in the coupled biogeochemical cycle of C and Si. In this study, we sampled above ground biomass from 22 intensively cultivated rice ecosystems to evaluate the rate of C sequestration through phytoliths. Depending on the rice varieties there exist a great variability in PhytOC content (0.12–0.26%) across the rice ecosystems. The collected samples were further classified into three groups: viz., long (>140 days), medium (125–140 days) and short duration (<125 days). The above-ground net primary productivity (ANPP) varied from 5174 to 13,394 kg ha−1 and recorded significantly (p < 0.05) higher in the relatively long duration variety compared to medium and short duration variety. The collected rice varieties showed a strong positive correlation (p < 0.05, R2 = 0.45) between ANPP and crop duration. With the increase in varietal duration, phytolith content was non-significant (p > 0.05) whereas, the PhytOC content found to be significant (p < 0.05). The long-duration (>140 days) varieties showed 69.7% and 164.0% higher PhytOC sequestration flux over medium and short-duration varieties, respectively. Our results suggest that the Indian rice ecosystems sequester 0.95 Tg CO2 yr−1 through Phytoliths, which is equivalent to the 15.5% of PhytOC sink in the global rice field. Considering the PhytOC flux of relatively higher PhytOC accumulating long duration varieties, the annual PhytOC sink rate in the Indian rice ecosystems can be increased to ∼4 folds over the current rate. It was revealed that the selection of higher PhytOC accumulating long duration varieties can enhance the phytolith C sequestration. [ABSTRACT FROM AUTHOR]

For gauging suitability of zygopteran odonates as bioindicators of ecosystems, an attempt was made to record the seasonal diversity of damselflies from seven different types of habitats in Paschim Medinipur District, West Bengal covering 14 land use sites. The study revealed existence of 19 species of damselflies belonging to 10 genera under two families. While the riparian zone had maximum number of species (15), paddy field had the lowest number (six). Ceriagrion coromandelianum and Agriocnemis pygmaea were the most common species. C. coromandelianum was eudominant in grassland and wetland-forest interface, whereas A. pygmaea was eudominant in fish pond and paddy field. Six species, viz., Paracercion calamorum, P. malayanum, Pseudagrion australasiae, P. decorum, P. spencei, and P. microcephalum were confined only to the riparian zone. Maximum abundance of damselflies was found in the riparian zone and minimum in the paddy field. Damselflies exhibited a distinct peak in March–April and a lesser peak in September–October. Most of the land use patterns exhibited similar zygopteran faunal composition. Species diversity index was moderate (1.4–2.5) and evenness index was on the higher side (0.76–0.94). Dominance Index ranged from 26.2 to 64.6. Riparian zone appeared to be the least stressed and most equitable habitat with highest diversity and evenness index and lowest dominance index. Paddy field seemed to be the harshest habitat for damselflies with least diversity and highest dominance index. The present study suggests that community analysis of damselflies can be quite useful in the assessment of the quality of any ecosystem. [ABSTRACT FROM AUTHOR]

The present study aimed to assess water footprint in the production and export of rice in India. From recent few years, the water footprint conception in full swing to inward detection around the world. The amplified attention in the water footprint has impelled the trade of commodities between countries. Water footprint in the rice field is a sign of water use that exhibits direct and indirect water usage in the rice field. Rice is an important food crop in India. It accesses the flows of water virtually between countries/regions of the world to illustrate the dependency of countries/regions on water resources with other countries/regions under diverse feasible futures. Hence, it is gaining consequence to calculate the water foot print in production as well as export of rice. The Indian rice production and export of rice was calculated by using international trade and domestic production data. The study results indicated that the global footprint of rice production was 235774 Mm3 per ton which was 53 % of green water footprint, 41 % of blue water footprint and 6 % of grey water footprint for 2018-19. The virtual water flowed in trade was 24354 Mm3/year and the percolation was 16924 Mm3/year since rice is a more water consuming crop. The share of basmati and nonbasmati trade accounted was 16 % and 42 %, respectively. Virtual water trade in rice can be minimized by exporting less water demand and high-value crops, proper water harvesting structures and other agronomic practices. [ABSTRACT FROM AUTHOR]

Integrated fish polyculture and poultry rearing, directly in the transplanted rice fields, through the Annamalai Rice + Fish + Poultry design was upscaled for participatory on-farm research. This model was adopted in 200 m2 area of individual holdings by 300 wetland rice farmers in Tamil Nadu. Three model clusters, each comprising three villages with 100 farmers were formed in Tamil Nadu. The results proved that the livelihoods of farmers increased by 80 per cent (INR 25,516). On an average, manurial addition by poultry to rice was around 8 tonnes/ha/season displacing the use of fertilizers and pesticides. Additional employment generation was 219 mandays/year. A total of 5,46,500 kg of broiler meat and 1,67,500 kg of fish were produced from these clusters in a three year duration. The average rice productivity for the 300 farm holdings from three districts increased by 9.38 percent. [ABSTRACT FROM AUTHOR]

Correction: Tabassum Abbasi et al., Modelling Methane and Nitrous Oxide Emissions from Rice Paddy Wetlands in India Using Artificial Neural Networks (ANNs). [Extracted from the article]

Evapotranspiration (ET) is one of the major water exchange processes between the earth's surface and the atmosphere. ET is a combined process of evaporation from open water bodies, bare soil and plant surfaces, and transpiration from vegetation. Remote sensing‐based ET models have been developed to estimate spatially distributed ET over large regions, however, many of them reportedly underestimate ET over semi‐arid regions (Jamshidi et al., Journal of Hydrometeorology, 2019, 20, 947–964). In this work, we show that underestimation of ET can occur due to the open water evaporation from flooded rice paddies ignored in the existing ET models. To address the gap in ET estimation, we have developed a novel approach that accounts for the missing ET component over flooded rice paddies. Our method improved ET estimates by a modified Penman‐Monteith algorithm that considered the fraction of open water evaporation from flooded rice paddies. Daily ET was calculated using ground based meteorological data and the MODIS satellite data over the Krishna River Basin. Seasonal and annual ET values over the Krishna Basin were compared with two different ET algorithms. ET estimates from these two models were also compared for different crop combinations. Results were validated with flux tower‐based measurements from other studies. We have identified a 17 mm/year difference in average annual ET over the Krishna River Basin with this new ET algorithm. This is very critical in basin scale water balance analysis and water productivity studies. [ABSTRACT FROM AUTHOR]

Ludwigia adscendens (L.) Hara, Ludwigia parviflora Roxb., and Ludwigia octovalvis (Jacq.) Raven (Onagraceae) are abundant weeds in rice fields in India. These weeds compete with rice for resources in fields and this results in reduction of grain yield. Altica cyanea (Weber) (Coleoptera: Chrysomelidae) is a biocontrol agent of the three rice‐field weeds. Hence, it is relevant to study host preference of A. cyanea using volatile cues of these three weeds. Therefore, we attempted to identify volatiles from leaves of the three Ludwigia species attracting A. cyanea, which could be used as an attractant during early emergence of the weeds in rice fields. In Y‐tube olfactometer assays, A. cyanea females were more attracted to natural volatiles of plants after 48 h of feeding by adults than to volatiles of undamaged plants. The volatile organic compounds from undamaged plants, and plants after 6 and 48 h of feeding by A. cyanea were identified and quantified by gas chromatography and mass spectrometry (GC–MS) and GC‐flame ionization detection (FID), respectively. In total, 25, 29, and 29 volatile compounds were detected in headspaces of undamaged L. adscendens, L. parviflora, and L. octovalvis, respectively, whereas 32, 35, and 34 compounds, respectively, were detected after 48 h of feeding by A. cyanea. Methyl jasmonate predominated among the volatile compounds in all treatments, but this compound was not attractive to A. cyanea. Females were attracted by synthetic blends of 3‐hexanol, α‐pinene, linalool oxide, and phytol in amounts mimicking those in each of the three Ludwigia species after 48 h of feeding by A. cyanea. The blends mimicking L. adscendens and L. parviflora included geraniol, whereas the blend mimicking L. parviflora also included 1‐tridecanol. These synthetic blends may be helpful to monitor A. cyanea in biocontrol programmes. [ABSTRACT FROM AUTHOR]

Distributed widely across the rice growing regions of India, the rice leaf and bud nematode (Aphelenchoides besseyi Christie 1942) can cause substantial yield loss in rice. Whitening of leaf tips is the characteristics damage symptom of this nematode and therefore it is popularly referred to as the rice white tip nematode (RWTN). While information on the damage severity of RWTN is available from others parts of the country, to date, no information is available from the state of Jharkhand. In order to generate a detailed information on spatial distribution of this nematode and to identify infestation hotspots, extensive field sampling was conducted across the Giridih district of Jharkhand. In total, 163 samples with each sample consisting of 30 randomly chosen panicles from three nearby rice fields were collected across the district. Moran’s I spatial autocorrelation test confirmed the presence of significant spatial clustering among the sampling locations. Optimized hotspot analysis found the presence of one significant hotspot in Dumri block and cold spots in adjoining areas of Gawan, Tisri, and Dhanwar blocks. Spatial interpolation techniques like inverse distance weighting (IDW) and ordinary kriging (OK) were employed to predict the population density at unsampled locations. Both IDW and OK resulted into generation of similar kind of maps where population density was found to be higher in Dumri, Giridih, Bengabad and some other pockets of the district. Finally, indicator kriging approach was employed which resulted into identifying both risk and nematode free areas. In risk areas, where the probability of the population density exceeding the economic threshold limit is high, immediate quarantine measures should be taken to prevent further dissemination of contaminated seeds. Our study provided a scientifically based decision method to devise preventive and curative protection measures against A. besseyi, a neglected pest of quarantine significance of rice in India. [ABSTRACT FROM AUTHOR]

Two-year field experiments were conducted at Tamil Nadu Rice Research Institute, Aduthurai, Tamil Nadu, India, to evaluate the effect of continuous flooding (CF) and alternate wetting and drying (AWD) irrigation strategies on rice grain yield and greenhouse gas emissions from double-cropping paddy rice. Field observation results showed that AWD irrigation was found to reduce the total seasonal methane (CH4) emission by 22.3% to 56.2% compared with CF while maintaining rice yield. By using the observed two-year field data, validation of the DNDC-Rice model was conducted for CF and AWD practices. The model overestimated rice grain yield by 24% and 29% in CF and AWD, respectively, averaged over the rice-growing seasons compared to observed values. The simulated seasonal CH4 emissions for CF were 6.4% lower and 4.2% higher than observed values and for AWD were 9.3% and 12.7% lower in the summer and monsoon season, respectively. The relative deviation of simulated seasonal nitrous oxide (N2O) emissions from observed emissions in CF were 27% and −35% and in AWD were 267% and 234% in the summer and monsoon season, respectively. Although the DNDC-Rice model reasonably estimated the total CH4 emission in CF and reproduced the mitigation effect of AWD treatment on CH4 emissions well, the model did not adequately predict the total N2O emission under water-saving irrigation. In terms of global warming potential (GWP), nevertheless there was a good agreement between the simulated and observed values for both CF and AWD irrigations due to smaller contributions of N2O to the GWP compared with that of CH4. This study showed that the DNDC-Rice model could be used for the estimation of CH4 emissions, the primary source of GWP from double-cropping paddy rice under different water management conditions in the tropical regions. [ABSTRACT FROM AUTHOR]

Paddy fields, which are shallow man-made wetlands, are estimated to be responsible for ~11% of the total methane emissions attributed to anthropogenic sources. The role of water use in driving these emissions, and the apportioning of the emissions to individual countries engaged in paddy cultivation, are aspects that have been mired in controversy and disagreement. This is largely due to the fact that methane (CH4) emissions not only change with the cultivar type but also regions, climate, soil type, soil conditions, manner of irrigation, type and quantity of fertilizer added—to name a few. The factors which can influence these aspects also encompass a wide range, and have origins in causes which can be physical, chemical, biological, and combinations of these. Exceedingly complex feedback mechanisms, exerting different magnitudes and types of influences on CH4 emissions under different conditions, are operative. Similar is the case of nitrous oxide (N2O); indeed, the present level of understanding of the factors which influence the quantum of its emission is still more patchy. This makes it difficult to even understand precisely the role of the myriad factors, less so model them. The challenge is made even more daunting by the fact that accurate and precise data on most of these aspects is lacking. This makes it nearly impossible to develop analytical models linking causes with effects vis a vis CH4 and N2O emissions from paddy fields. For situations like this the bioinspired artificial intelligence technique of artificial neural network (ANN), which can model a phenomenon on the basis of past data and without the explicit understanding of the mechanism phenomena, may prove useful. However, no such model for CH4 or N2O has been developed so far. Hence the present work was undertaken. It describes ANN-based models developed by us to predict CH4 and N2O emissions using soil characteristics, fertilizer inputs, and rice cultivar yield as inputs. Upon testing the predictive ability of the models with sets of data not used in model development, it was seen that there was excellent agreement between model forecasts and experimental findings, leading to correlations coefficients of 0.991 and 0.96, and root mean square error (RMSE) of 11.17 and 261.3, respectively, for CH4 and N2O emissions. Thus, the models can be used to estimate CH4 and N2O emissions from all those continuously flooded paddy wetlands for which data on total organic carbon, soil electrical conductivity, applied nitrogen, phosphorous and potassium, NPK, and grain yield is available. [ABSTRACT FROM AUTHOR]