Paddy Fields Research Articles

Exploring sustainable crop residue management practices: farmers’ perceptions in north India

ABSTRACT Purpose This research examined farmers’ adoption of Sustainable Crop Residue Management (SCRM) practices by validating the Protection Motivation theory (PMT) and Ecological Modernisation Theory (EMT) as theoretical underpinnings. This research validated the impact of factors like Coping appraisal, Social cognitive attributes, Habit, Risk perception, Supply chain practices and Health consciousness on actual adoption. The study further empirically analysed the impact of actual adoption on perceived sustainable performance. Design/Methodology/Approach A data set of 239 farmers from North Indian states was analysed to understand the perceptions of farmers. Only those farmers who were engaged in paddy and wheat cultivation were considered in this research. Partial Least Square Structural Equation Modeling (PLS-SEM) was applied to access and validate the hypothesized relationships. Findings Coping appraisal and supply chain practices emerged insignificant. Actual adoption had a significant and strong impact on perceived sustainable performance. Practical implication Based on the fact that farmers still need to adopt SCRM practices, the study provides significant pointers to the government, policymakers, and agricultural departments of North Indian states. Based on this study government needs to implement some focused policies had to be developed to boost farmers’ adoption. For example, targeted subsidies for machinery should be given to encourage farmers to adopt such practices. Theoretical Implications First, this research validates both PMT and EMT together in the context of SCRM practices. In addition, this research-validated a few other variables like Governments’ facilitative interventions, supply chain practices and perceived sustainable performance that previous studies failed to analyse, leading to a comprehensive model. Secondly, it creates a theoretical association among risk perception, social cognitive attributes, habit, government facilitative interventions, and supply chain practices. Originality/Value Due to the multitude of factors associated with paddy stubble burning, this research is an earnest effort to empirically analyse the variables influencing farmers’ decisions concerning the actual adoption of SCRM practices. This research is indeed a very initial attempt to comprehend the view-points of farmers to understand the reasons which make them go to crop residue burning despite awareness of the harmful effects of burning on human health and the environment.

Rainwater-Derived Reactive Oxygen Species Diminish Environmental Risk from Arsenic in Paddy Rice Systems.

It has been previously observed that rainwater input into paddy rice soils reduced the level of grain-borne arsenic, and it is hypothesized that a Fenton-like reaction triggered by interaction between rainwater-borne hydrogen peroxide and ferrous iron in paddy soils is responsible for microbially mediated impediment of As uptake by rice plants. However, this hypothesis remains untested. This study tested the hypothesis through mesocosm experiments, confirming that rainwater-borne hydrogen peroxide triggered hydroxyl radical (•OH) generation, elevating soil redox potential, and oxidizing arsenite to less phytoavailable arsenate in soil porewater, thereby reducing As uptake by rice and As accumulation in rice grain. Comparison between two crops of rice cultivation with different fluxes of rainwater-borne hydrogen peroxide confirms that seasonal rainfall variation has an impact on accumulation of rice grain-borne arsenic, with paddy soil receiving more rainfall having a lower arsenic concentration in the rice grain compared to that receiving less rainfall. Using China's major rice-producing region as an example, it is demonstrated that spatial variation in rainfall regime could impact the geographical distribution of rice grain-borne As at a national scale. The findings have implications for the assessment and management of the environmental risk from arsenic-contaminated rice grains.

KOMUNITAS SERANGGA DAN VEGETASI PENUTUP TANAH PADA LAHAN SAWAH TADAH HUJAN DI KUTAI KARTANEGARA: EFEK VARIASI KETINGGIAN TEMPAT

Variations in altitude create significant differences in environmental conditions, such as temperature, humidity, and nutrient availability, which profoundly affect the structure of vegetation and insect communities. These variations influence biodiversity levels and the patterns of interactions between vegetation and insects within ecosystems. Therefore, this descriptive exploratory study was conducted to analyze the diversity of ground-dwelling insect communities and the structure of ground cover vegetation in Gedagai Putih rice fields across different altitudinal gradients. Insect sampling was carried out using the pitfall trap method, while vegetation observations were conducted using 60 cm x 80 cm plots. The results of the study indicate that altitudinal variations significantly influence the composition and dominance of insect and ground cover vegetation species. The highest dominance level of insect Genus was observed for Entomobrya (IVI = 67.48) in Zone III (300 m a.s.l), while the lowest dominance was recorded for Alydus and Leptocorisa (IVI = 1.55) in Zone I (108 m a.s.l). For plant species, the highest dominance was observed in Paspalum conjugatum (IVI = 133), while the lowest dominance was recorded for Alocasia sp (IVI = 7) in Zone I.

Rice Fields and Aquatic Insect Biodiversity in Italy: State of Knowledge and Perspectives in the Context of Global Change

Rice Fields and Aquatic Insect Biodiversity in Italy: State of Knowledge and Perspectives in the Context of Global Change

Field Ridge Segmentation and Navigation Line Coordinate Extraction of Paddy Field Images Based on Machine Vision Fused with GNSS

Field Ridge Segmentation and Navigation Line Coordinate Extraction of Paddy Field Images Based on Machine Vision Fused with GNSS

Variations in the N2 Fixation and CH4 Oxidation Activities of Type I Methanotrophs in the Rice Roots in Saline-Alkali Paddy Field Under Nitrogen Fertilization

The root-associated methanotrophs contribute to N2 fixation and CH4 oxidation in paddy fields under N-limited conditions. However, the impact of nitrogen inputs on N₂ fixation and CH₄ oxidation by methanotrophs is largely unknown, especially in saline-alkali paddy fields with higher nitrogen application. This study explored the impact of nitrogen fertilization on N₂ fixation and CH₄ oxidation by root-associated active diazotrophic and methanotrophic communities in a saline-alkali paddy field using 15N–N2 and 13C–CH4 isotope feeding experiments along with RNA-based sequencing. The 15N and 13C isotope feeding experiments showed that the CH₄ oxidation-dependent nitrogen fixation rate of methanotrophs (15N and 13C) in the roots of two rice cultivars was significantly higher than the CH₄ oxidation-independent nitrogen fixation rate of heterotrophic diazotrophs (only 15N) under nitrogen fertilization (SN) in a saline-alkali environment (P < 0.05). For Kongyu131 rice, the CH₄ oxidation-dependent nitrogen fixation rate ranged from 1.17 to 4.15 μmol/h/g, while the CH₄ oxidation-independent nitrogen fixation rate was determined to be 1.10 to 3.17 μmol/h/g. In J3 rice, these rates were 7.30 to 9.22 μmol/h/g and 5.76 to 4.85 μmol/h/g, respectively (P < 0.05). Moreover, both N2 fixation and CH4 oxidation rates of methanotrophs in the roots of salt-alkali tolerant J3 cultivar (9.22 μmol/h/g for N2 fixation; 0.09 μmol/h/g for CH4 oxidation) were significantly higher than those in the roots of the common rice cultivar Kongyu131 (4.15 μmol/h/g for N₂ fixation; 0.03 μmol/h/g for CH₄ oxidation) under nitrogen fertilization (P < 0.01). Thus, methanotrophs associated with J3 rice roots demonstrated improved N2 fixation and CH4 oxidation activities under saline-alkali stress in the presence of nitrogen fertilizer. Even heterotrophic diazotrophs in J3 rice roots showed enhanced N2 fixation with (SN) or without (LN) nitrogen inputs. The RNA-based amplicon sequencing showed that nitrogen fertilizer had a greater influence on diazotrophic and methanotrophic communities than the differences between rice cultivars. Further, active Methylomonas (type I methanotrophs) dominated the root-associated diazotrophic (9.8–20.9%) and methanotrophic (46.8–80.3%) communities. Within these, Methylomonas methanica (13.3 vs. 3.8%) and Methylomonas paludis (8.8 vs. 27.4%) were determined as the common genera in the diazotrophic and methanotrophic communities, respectively, with both proportions undergoing significant shifts under SN conditions. Whereas the LN condition led to high CH4 oxidation activity and a relatively high abundance of Methylocystis (26.0%) in the roots of Kongyu131 rice, which sharply decreased under the SN condition (0.3%). The findings revealed that CH4 oxidation-dependent N2 fixation and CH4 oxidation activities of root-associated type I methanotrophs were significantly affected under nitrogen fertilization, with a more pronounced effect in the salt-alkali tolerant J3 rice cultivar compared to Kongyu131. This study highlights the potential of aerobic diazotrophic methanotrophs in enhancing symbiotic diversity and environmental adaptability while contributing to CH4 emission reduction and bioavailable nitrogen accumulation in saline-alkali paddy fields.

Numerical simulation of the residence time distribution dynamics of a restored agricultural wetland under varying environmental conditions

Numerical simulation of the residence time distribution dynamics of a restored agricultural wetland under varying environmental conditions

Development of a real-time dynamic inundation risk assessment approach on paddy fields during typhoons: Exploration of adaptation strategies and quantification of risks.

Development of a real-time dynamic inundation risk assessment approach on paddy fields during typhoons: Exploration of adaptation strategies and quantification of risks.

Implementasi Indeks Pertanaman 400 untuk Meningkatkan Produksi Padi Indonesia: Studi Kasus Kabupaten Sukoharjo

Sukoharjo Regency, Central Java, is an example of successfully implementing rice planting using the Planting Index 400 (IP-400). This study aimed to analyze the difference in total farming costs between IP-400 and non-IP-400 rice varieties and their sustainability. Farmers in Sukoharjo have succeeded in planting rice three to four times a year in rice fields with technical irrigation. This activity was carried out in five stages, i.e. 1) a Discussion with the Head of the Sukoharjo Regency Agriculture and Fisheries Service, Central Java and his staf; 2) Focus Group Discussion (FGD) with the Head of the Sukoharjo Regency Agriculture and Fisheries Service, Heads of Farmer Groups and their members, Delegates from the Directorate General of Food Crops, Ministry of Agriculture, as well as related parties; 3) Field visits to rice seed entrepreneurs; 4) Field visits to "integrated farming" entrepreneurs who implement IP-400 rice cultivation; and 5) Field visits and interviews with farmers accompanied by extension workers and the Department of Agriculture as farmer advisors. Socialization and discussions have effectively increased stakeholders’ understanding of the implementation of IP-400 rice planting. This success is due to adequate technical support and infrastructure and close cooperation between farmers, local governments, and other related parties. By continuing these efforts and adapting to local conditions, the IP-400 program can become a model for other regions to sustainably increase rice production

Pelatihan Good Farming Practises, dan Good Manufacturing Practises untuk Meningkatkan Daya Saing UKM Abinisa Serang Banten

UKM Abinisa is a leading producer in the duck egg processing industry in Serang, Banten. To maintain competitiveness, SME need to focus on product innovation and implement Good Manufacturing Practices (GMP) and Good Farming Practices (GFP) to ensure product safety. This community service program aimed to provide training related to GMP and GFP. Socialization and training activities were held on the same date in Sujung Village, Tirtayasa Subdistrict, Serang Regency, Banten. The steps of the activity included: a) pre-activity preparation, b) internal coordination, c) implementation, and d) evaluation. The activity began with a visit to a duck farm owned by one of UKM Abinisa's farmer partners. The first training session covered techniques for proper and effective feeding, disease prevention, and maintaining healthy living conditions for ducks. Practical sessions included duck herding or releasing them onto post-harvest rice fields, a method well-suited to the extensive rice fields around Sujung Village. This method is known as the rice-duck integration system. The evaluation results showed a high level of participant satisfaction, with the highest-rated material being Material 1: Duck Farming, scoring 69.57%. Material 3 scored similarly at 65.22%. Material 2: Introduction to GMP received the lowest score, likely because of the complexity and detailed nature of the regulations, which were unfamiliar to all participants.

Soil pH and Rice Chlorophyll Content as Indicators of Grain Productivity and Microbial Community in Acid-Exposed Paddy Mesocosms.

The objective of this study was to evaluate the applicability of soil pH and chlorophyll content as predictive indicators of damage in paddy fields affected by HCl spills, based on causal relationships. Five doses of HCl (e.g., 1, 50, 100, 200, and 500-fold of PNEC) were added to the paddy mesocosm during the rice heading stage. In the 7th week after the acid addition, rice grain quality (e.g., 1000-grain weight and filled grain ratio), soil microbial diversity (e.g., Operational Taxonomic Units (OTUs) and Shannon index), and soluble nutrients (e.g., NH4+, NO3-, SiO2, P2O5, and basic cations) were measured. Causal relationships among variables were analyzed using the Partial Least Square Path Model (PLS-PM). At the dose of 500×PNEC, all rice plants lodged when pH < 4. At 100×PNEC and 200×PNEC, the number of immature grains increased, resulting in a reduction in grain quality of over 18%. At 200×PNEC, the microbial OTUs and the Shannon index decreased by 30%. Notably, the proportion of Planctomycetes, the dominant phylum in the control soil, decreased. The reduction of Planctomycetes led to excessive NH4+ accumulation in the soil, which leads to an undesirable increase of chlorophyll content thereby deteriorating grain quality. The causal relationship suggests that information of soil pH and leaf chlorophyll can aid us in predicting damage for grain quality and microbial diversity.

Biochar application using recycled annual self straw reduces long-term greenhouse gas emissions from paddy fields with economic benefits.

Paddy fields are major contributors to agricultural greenhouse gas emissions. Applying ~1% biochar by topsoil weight (high single, HS) effectively reduces greenhouse gas emissions from paddy fields, but long-term impacts are unclear. Here we present 8-year field experiments showing HS reduces CO2 equivalent per hectare by 59% and yields a net benefit of US$1,810 per hectare. However, its effectiveness declines over time due to the decreased soil carbon content and methanotrophic activity triggered by higher soil ammonium concentrations. To counteract this, the annual-low method, involving yearly biochar recycling, surpasses the HS approach with a 52% CO2 reduction and yields a net benefit of US$2,801 (35%) per hectare-highlighting the economic and environmental viability of annual-low biochar use in sustainable paddy field management practices.

Diversity, infection dynamics, and environmental drivers of gastropods in the rice field-lakescape of Lake Mainit, Philippines: implications for snail-borne diseases and integrated management strategies.

Rice fields near Lake Mainit, Philippines, serve as ecological hotspots for gastropod diversity and parasitic infections, particularly schistosomiasis. This study examined the cascading effects of soil and water parameters on snail diversity and abundance, as well as the influence of environmental factors on the infection status of dominant gastropod species. A total of ten gastropod species from six families were identified across six stations, with Melanoides maculata as the most abundant (32%). Oncomelania hupensis quadrasi, the snail intermediate host of Schistosoma japonicum in the Philippines, was present at all stations, with varying cercarial infection rates. Soil analysis revealed compositions of 25% clay, 20% pebbles, and varying sand and gravel proportions, with acidic conditions (pH 3.04 in Matin-ao). Nickel concentrations exceeded safety thresholds in Magpayang (162 ± 45.1ppm) and Matin-ao (148 ± 1.67ppm), alongside elevated calcium, magnesium, manganese, and copper levels in Alipao, Cuyago, and San Isidro. Principal component analysis (PCA) identified sodium, calcium, potassium, pH, and temperature as key environmental drivers, though they influenced site differentiation more than snail species and abundance. To assess parasite transmission, a chi-square test of independence revealed a significant association between snail species and infection rates across sites. Oncomelania hupensis quadrasi exhibited consistently high deviation values in Magpayang, Cuyago, San Isidro, and Alegria, indicating localized infection patterns. These findings highlight the interplay between physico-chemical factors, gastropod communities, and parasite transmission, providing baseline data crucial for targeted snail control and schistosomiasis prevention in Philippine rice fields. Further investigation is needed to understand how environmental contamination from infected bovines sustains schistosome transmission in unfavorable rice field conditions.

Chromatic Diagnostics: Enhancing Paddy Disease Detection with Filter-Based Feature Transformation

Currently, this research advances on improvement of diagnostic methods for diseases that affect plants within the paddy fields to improve crop management and subsequently the efficiency of agricultural production. The research also presents a new method that addresses the problem through filter-based feature transformation methods which enhance the input features fed to disease detection models. All these transformations are geared towards increasing the accuracy and efficiency of the existing paddy disease identification systems. This investigation will also show a dramatic increase in the accuracy of detection as one of the key results. Interestingly, if such transformed features are fed into the K-Nearest Neighbour (KNN) classifier, a most frequently used classifier in the field of machine learning for classification, a balanced accuracy of 90% is obtained. From this the proposed method is quite viable and powerful enough to provide accurate and genuine diagnosis of disease in the paddy crops. Therefore, the novelty and practical use of the findings of this research is not limited merely to theoretical implications but rather it provides practicing real and tangible values in various aspects of sustainable agriculture and crop science. Improvement of disease diagnosis frequency and reliability helps farmers to promptly start an effective fight against infectious diseases, thus decreasing yield losses and contributing to food safety. Conclusively, this project represents a significant progress in applying complex computational techniques for tackling real life issues in agriculture. Filter based feature transformation is reported to pose an effective technique that can be adopted to enhance disease detection systems and consequently enhance paddy farming across the world. Introduction: The paper investigates methods to improve paddy crop disease diagnostics which aims at enhancing farming management practices along with agricultural productivity rates. The research introduces novel filter-based technology which enhances the quality of features that feed disease detection models. The new system designs work to improve both speed and precision of paddy disease identification systems currently in use. The research delivers major advancements in detection accuracy as giving proper disease diagnoses at right times minimizes agricultural damage and improves food safety in farming operations. Objectives: This research aims to improve both paddy disease detection system precision and system reliability through its main objectives. The aim of applying filter-based feature transformation is to enhance K-Nearest Neighbour (KNN) classifier performance by optimizing the input features. This research aims to develop a practical detection system that combines features for paddy disease identification while addressing diseases so paddy farmers can achieve sustainable food security. Method: The study utilizes filter-based feature transformation as a preprocessing method for data preparation before feeding it to detect diseases in paddy crops. The model uses transformed features to test them within the K-Nearest Neighbour (KNN) classifier which stands as a popular machine learning model used for classification operations. The method undergoes assessment regarding its capability to enhance detection accuracy and achieve optimal sensitivity and specificity balance. The investigation examines different approaches to transform features while studying their influence on model effectiveness and demonstrates practical field applications of the results in agricultural settings.. Results: When K-Nearest Neighbour (KNN) classifier processes the transformed features the analysis shows a 90% accuracy in disease detection. The proposed filter-based feature transformation method demonstrates its effectiveness at boosting disease detection systems for paddy crops according to this result. Disease diagnosis efficiency combined with more accurate tools gives farmers better options to detect diseases at an early stage for effective decision-making and timely responses to disease outbreaks that reduce crop yield damages. Conclusion: This study marks considerable advancement in using computational methods to solve genuine agricultural problems. The filter-based feature transformation system establishes itself as an effective technique to enhance disease detection protocols while supporting eco-friendly farming and better food quality assurance systems. The research confirms that sophisticated machine learning algorithms provide farmers with sustainable tools to fight infectious diseases in their paddy fields. A timely correct disease diagnosis stands fundamental to protect global food supply and sustainable agriculture.

Single cell protein production potential of enriched microbial populations from rice paddy soils and roots: Insights into protein yield enhancement by Methylophilaceae.

Single cell protein production potential of enriched microbial populations from rice paddy soils and roots: Insights into protein yield enhancement by Methylophilaceae.

Agricultural water infiltration tank (Awit): a flood-suction device for rice fields

In 2022, the Philippines experienced severe tropical cyclones that caused significant agricultural damage, impacting over 46,000 farmers. Despite government aid, long-term floodwater management remained unaddressed. This study explores the potential of floodwater recycling systems, particularly the Agricultural Water Infiltration Tank (AWIT), to improve agricultural resilience and sustainability. Using a Randomized Complete Block Design (RCBD), the study assesses AWIT's effectiveness as a flood-suction device. The AWIT incorporates multi-stage filtration, including granular filtration, chemical treatment, sedimentation, reverse osmosis, and UV light disinfection. Results demonstrate that AWIT effectively removes contaminants, improving water quality for agricultural use. The system provides a sustainable water source, reducing water procurement costs and supporting farmers during droughts. Recommendations include further field testing, optimization of chemical dosing, and integration of automation for real-time monitoring. With government support, AWIT has the potential to be a scalable solution for floodwater management and agricultural water sustainability.

A state of art review on carbon, nitrogen, and phosphorus cycling and efficient utilization in paddy fields

A state of art review on carbon, nitrogen, and phosphorus cycling and efficient utilization in paddy fields

Anaerobic Digestion of Rice Straw as Profitable Climate Solution Reduces Paddy Field Greenhousegas Emissions and Produces Climate-Smart Fertilizer Under Carbon Trading Mechanisms

Continuous incorporation of rice straw has caused significant CH4 emissions from the paddy field production system in East China. Anaerobic digestion (AD) of the rice straw has been considered as a promising approach that could not only mitigate the land-based CH4 emissions, but also generate low-carbon electricity and high-quality organic fertilizer. However, this approach, in many circumstances, is unable to be cost-competitive with other straw treatment processes or power sources. To understand the potential incentives that recently launched carbon trading schemes, the China Carbon Emission Trade Exchange (CCETE) and Chinese Certified Emission Reduction (CCER), could bring to the rice straw utilization value chain, we conducted a cradle-to-factory gate life cycle assessment and economic analysis of a small-scale AD system with rice straw as the main feedstock in East China. The results indicate that, depending on the choice of allocation method, the climate change impact of the bioenergy generated through the studied small-scale AD system is 0.21 to 0.28 kg CO2eq./kWh, and the digester fertilizer produced is 6.88 to 22.09 kg CO2eq./kg N. The economic analysis validates the financial sustainability of such small-scale AD projects with rice straw feedstock under carbon trading mechanisms. The climate mitigation potential could be achieved at the marginal reduction cost of 13.98 to −53.02 USD/t CO2eq. in different carbon price scenarios.

Ecological risk evaluation of heavy metals based on hyperspectral: a case study of rice paddy soil in Xiangtan County, China

Heavy metal pollution in agricultural soils pose significant risks to food safety and human health, necessitating effective monitoring and assessment techniques. Recognizing characteristic spectral features is essential for accurately assessing the ecological risks associated with heavy metal pollution. To explore the potential of utilizing the hyperspectrum to evaluate ecologial risks of heavy metals pollution in paddy soil, the study investigated ecological risks and spectral characteristics (350 ~ 2500 nm) of heavy metals (Cd, Pb, Cr, Cu) in rice paddy soil in Xiangtan County, Hunan Province, China. Potential ecological risk index (RI) was employed to evaluate pollution level, and derivative transformations (first derivative R′ and second derivative R″) were applied to eliminate the hyperspectral noise. Results identified Cd as the primary pollutant in the paddy soil of Xiangtan County, followed by Pb, Cu, and Cr. Serious heavy metal pollution concentrated in riverine and cropland areas. After applying spectral transformations, the correlation between spectral reflectance and ecological risks significantly improved. The R″ transformation demonstrated the highest correlations for Cd (r = 0.95) at 2046 nm in high ecological risk category, while the R′ transformation exhibited the strongest negative correlation for Cd (r = − 0.94) at 2059 nm. This study highlights the potential of hyperspectral analysis as an effective tool for estimating ecological risks posed by heavy metal pollution in rice paddy soils. The findings provide valuable insights for improving monitoring practices and informing risk management strategies in agricultural environments.

Analysis of the Potential Index for Rice Agricultural Land Using Geographic Information Systems in Bandung Regency

Currently, one of the main problems in the agricultural industry is the conversion of irrigated rice fields. The potential for irrigated rice fields in Bandung Regency is needed to help overcome agricultural problems. This study aims to find out how to analyze the potential index of irrigated rice fields and land that is not rice fields but in Bandung Regency by mapping the potential index of rice fields using the Geographic Information System. The GIS analysis used was using scoring and overlay on the parameters used. The results of the overlay of each parameter produced an index of irrigated rice field potential which showed that rice fields in Bandung Regency were most planted on land that had IPL with a medium class, which was 697.99 Km² with a percentage of 39%. Land that is not a rice field and has the potential to become a new rice field is 5 classes, namely very high with an area of 42.34 Km2 consisting of 12 sub-districts, land with a high category has an area of 321.44 Km² consisting of 14 sub-district areas, in the medium potential class, which is the most dominating Bandung Regency, which is 633.79 Km2 which covers 20 sub- district areas, the distribution of low-class potential land covers 24 sub-districts covering an area of 355.36 Km2, while in the very low land potential class spread across 20 sub-districts covering an area of 98.21 Km2. As a recommendation, rice fields with high potential should be maintained as rice fields, and rice fields with low potential should be processed more optimally.