Paddy Production Research Articles

Pengelompokan Produksi Padi dan Beras Provinsi Jawa Timur dengan Metode Agglomerative Hierarchical Clustering

Paddy is a food crop that produces rice which is widely consumed for basic needs and has become a source of income for the Indonesian people. Often the need for rice continues to increase and cannot only rely on domestic production, so it is necessary to optimize paddy producing areas. Grouping rice-producing areas needs to be done to identify production potentials and areas that require improvement. This research aims to group paddy and rice production based on districts/cities in East Java Province. The method used is Agglomerative Hierarchical Clustering (AHC) with the best algorithm, namely average linkage based on the highest cophenetic correlation of 0.8478. The research results showed 4 clusters: cluster 1 (high) with 4 districts, cluster 2 (low) with 18 districts, cluster 3 (medium) with 7 districts, and cluster 4 (very low) with 9 cities. The silhouette coefficient test is 0.6347, close to 1, thus indicating good clustering. These results can be used as a reference for the government and society in optimizing paddy and rice production to maintain the country's food security

Transfer learning by VGG-16 with convolutional neural network for paddy leaf disease classification

ABSTRACT One of the most recent areas of research in agriculture is the detection along with classification of diseases from plant leaf images. Since rice is the most widely consumed staple food worldwide, it is crucial to increase paddy production’s quality and quantity. In the production of paddy, early detection of pests and diseases at various growth stages is very important. Utilising image processing scheme to spot diseases of agricultural plants will lessen the need for farmers to safeguard agricultural products. The use of VGG-16 along with a Convolutional Neural Network (CNN) for the classification and recognition of paddy leaf diseases is proposed in this work. The rice plant leaves images taken from the kaggle dataset is utilised for the purpose of image acquisition. The Gaussian filter is used in pre-processing. The clustering technique is utilised for the segmentation of the diseased part, the normal part, and the surroundings. The proposed model is then utilised for disease classification. This study classifies 10 categories of paddy images. VGG16, InceptionV3, MobileNetV2, and ResNet-152, among other transfer learning methods, are evaluated and contrasted with the experimental results. The outcome accuracy of the proposed model achieves of nearly 99.9%.

Germination and biological adaptation approaches as salt-stress tolerance process in selected paddy cultivars under salinity stress

Cultivating productive paddy crops on salty soil to maximise production is a challenging approach to meeting the world's growing food demand. Thus, determining salinity tolerance rates in specific paddy cultivars is urgently needed. In this study, the salt tolerance traits of selected paddy cultivars, ADT45 and ADT39, were investigated by analysing germination, metabolites (pigments and biomolecules), and enzymatic (Superoxide dismutase (SOD), Catalase (CAT), and Peroxidase (POD) adaptation strategies as salt-stress tolerance mechanisms. This study found that salinity-induced reactive oxygen species (ROS) were efficiently detoxified by the antioxidant enzymes Superoxide dismutase (SOD), Catalase (CAT), and Peroxidase (POD) in ADT45 paddy varieties, followed by ADT39. Salinity stress had a significant impact on pigments and essential biomolecules in ADT45 and ADT39 paddy cultivars, including total chlorophyll, anthocyanin, carotenoids, ascorbic acid, hydrogen peroxide (H2O2), malondialdehyde, and proline. ADT45 demonstrated a significant relationship between H2O2 and antioxidant enzyme levels, followed by ADT39 paddy but not IR64. Morphological, physiological, and biochemical analyses revealed that ADT45, followed by ADT39, is a potential salt-tolerant rice cultivar.

Behavioral Intention of Paddy Farmers Towards Adoption of Organic Sources for Soil Nutrient Management Consequent to Policy Decision to Ban Agro-chemicals in Sri Lanka: A Case Study

This stu dy was aimed at investigating the behavioral intention towards and factors influencing adoption of organic soil nutrient management by paddy farmers, consequent to the banning of agro-chemicals in April 2021 in Sri Lank a. A questionnaire survey, supplemented by key informant discussions was used to collect the primary data after six months of the banning when farmers were preparing for the next Maha season (starting from Novemb er 2021). Paddy farmers (N=120) from the Mahaillu ppallama irrigation block of the Mahaweli system H in Anuradhapura district were randomly selected as the respond ents. The Theory of Planned Behavior (TPB) was used as the conceptual framework of the study. The study revealed that the majority (85%) of farmers did not agree with the sudden decision of the government to ban agro-chemicals to enable a complete transformation of agriculture to one that is totally organic. Only 11% of the farmers preferred a fully organic paddy production system. The majority (58%) preferred to use both organic and inorganic fertilizers. However, 31% of the farmers preferred conventional farming as usual. Perceived difficulties were the major barriers for farmers to use organic f ertilizers. Attitude on production, age, perceived knowledge of organic agriculture, and farming income significant ly affected (P < 0.1) paddy farmers’ intention to adopt organic fertilizers. It is concluded that a scientifically designed gradual transition would be more appropriate for nutrient management in paddy cultivation.

Annual Flood Phenomenon and Fertility Status of Rice Soil in The Coastal Area of Bengkulu

[ANNUAL FLOOD PHENOMENON AND FERTILITY STATUS OF RICE SOIL IN THE COASTAL AREA OF BENGKULU]. The rice fields in Rawa Makmur Village were agricultural land that was affected by annual floods. Soil fertility status is important for increasing the productivity of paddy. The research aimed to get the fertility status of soil affected by annual flood disasters, evaluating and mapping the distribution of soil fertility status at the research location. The methods used in this research include survey and soil testing methods at the Soil Science Laboratory, Faculty of Agriculture, Bengkulu University. Further evaluation of soil fertility status is in accordance with technical instructions from the Soil Research Center, Bogor (1995). This research was conducted in June – August 2023. The soil CEC value from each sampling point was classified as high with values ranging from 28.15 me/100 g - 39.83 me/100 g. The base saturation value in the study was classified as very low to moderate with values ranging from 11.49% - 40.08%. Soil organic C at the research location from each sampling point was classified as moderate to very high with values ranging from 2.42% - 5.97%. The soil phosphorus content at the research locations observed was classified as very low to low with values ranging from 2.69 mg/100 g – 12.11 mg/100 g. The soil potassium content at each sample point at the research location observed was classified as very low with values ranging from 0.14 mg/100 g – 1.43 mg/100 g. The research results show that the flood phenomenon has a significant impact on soil fertility. The soil fertility status at the research location is classified as low. Soil fertility parameters which are limiting factors in the status of soil fertility in Rawa Makmur Village are phosphorus, potassium and pH. So it is necessary to add P and K fertilizer to improve the soil fertility status.

To analyze the technical and allocative efficiency of drill paddy cultivation in Bhandara district

The present study on paddy was undertaken in Bhandara district of Vidarbha region. The district was selected purposively. Three tehsils were selected. Out of the seven tehsil, Sakoli, Lakhandur and Pauni tehsil was selected for the study based on drill paddy cultivars. Three villages were selected purposively from each tahsil and from each village 10 farmers were selected overall 90 farmers were selected. The study revealed that how different cost components affect the profitability of production paddy crop and also proposes that at how much level of efficiency, the farmer is producing the paddy crop and how much level of efficiency is yet to be obtained. The maximum livelihood estimates of the stochastic production function revealed that fertilizer showed a negative and significant effect on paddy production. The co-efficient of the frontier profit function revealed that machine hours, seed and fertilizer shows a negative and significant impact on paddy farmer profitability. The mean technical, economic and allocative efficiency of paddy cultivation was found to be 97.49 per cent, 87.97 per cent and 89.86 per cent indicated that there is still scope for paddy farmers to increase the economical and allocative efficiency by operating at a full efficient level by proper utilization and allocation of existing resources and technology.

Comprehensive study on physico-chemical soil analysis for optimizing paddy (Oryza sativa L.) cultivation in Kamrup (Metro) district of Assam, India

Rice being the staple food in Assam, its productivity should be increased for the availability of the common people. The main objective of this study is to compare the qualities of soil samples and to correlate the results with the production (per year) of paddy (Oryza sativa) from 3 different studied areas. The soil samples were collected during March-May, 2023. The oven dry method and drying and weighing method are used to determine bulk and particle densities respectively. The electrical conductivity and pH of the soil samples are determined using a benchtop conductivity meter and pH meter. Walkley-Black chromic acid wet oxidation method and methylene blue method are used to determine the organic carbon and cation exchange capacity (CEC) of soil samples respectively. Nitrogen, phosphorus, and potassium of the soil samples are estimated using the instrument Mridaparikshak. The moisture content, bulk density, particle density, soil porosity, cation exchange capacity (CEC), pH, electrical conductivity, nitrogen, P2O5, and K2O are observed in the range of 24.69 % to 39.42 %, 1.12 g cm-3 to 1.25 gcm-3, 1.83 gcm-3 to 1.99 g/cm-3, 33 to 43, 2.8 × 10-5mol dm-3to 11.7x10-5 mol dm-3, 7.4 to 8, 0.23 dS/m to 0.40 dS/m, 0.645% to 1.49%, 213.20 kg/ha - 235.14 kg/ha, 17.92 kg/ha - 20.44 kg/ha and 148.92 kg/ha -164.45 kg/ha respectively. The soil characterized by moisture content =27.52 %, bulk density=1.25 gcm-3, particle density =1.86 g cm-3, porosity =33%, cation exchange capacity =11.7 x 10-5 mol dm-3, pH {(1:5) at 210C} = 7.9, electrical conductivity = 0.40 dS/m, organic carbon =0.825 %, organic matter =1.42 %, N =235.14 kg/ha, P2O5 = 20.44 kg/ha and K2O =164.45 kg/ha showed good yield.

Exploring rice genotypes for anaerobic germination: Towards sustainable direct seeding

Direct-seeded rice (DSR) production is the primary focus of this study, which explores the diversity of rice genotypes concerning their ability to withstand anaerobic germination conditions. Using advanced statistical analysis, a total of 250 rice cultivars were assessed for several anaerobic germination attributes. Significant variability was observed among genotypes for key traits including germination % (ARC14855, AG 387), shoot length and seedling dry weight, indicating potential donors for anaerobic germination tolerance. Trait association analysis, variability analysis, principal component analysis and cluster analysis were employed to uncover the genetic and phenotypic factors influencing anaerobic germination tolerance. The genotypes of cluster III could be used as donors for anaerobic germination studies, as the genotypes have revealed high average values for all the traits. The findings underscore the importance of genetic variability and heritability in breeding resilient rice varieties suited for DSR cultivation, offering valuable insights for enhancing rice cultivation practices in the face of challenges such as water scarcity and labour shortages. To improve the sustainability and productivity of paddy production systems, this research advances rice breeding procedures that aim to create varieties tolerant to anaerobic conditions.

Beta four parameter GLMM approach to evaluate paddy productivity

Abstract Indonesia is one of the top five counties in the world that produces rice. In average, Indonesia has a paddy productivity of 5.2 tons per hectare and continuously growing within 1.59% annual rate. Eventhough high, one of the main problems faced is that Indonesia is a vast archipelago country that has a diverse agro-climatic and socio-economic conditions which can significantly impact paddy productivity in an area. Given also that the paddy productivity in Indonesia has a certain minimum and maximum value, thus using a beta four parameter-based model is considered appropriate. We have proposed novel Beta Four Parameter GLMM that was an extension of the Beta Four Parameter regression model developed by Zou and Huang (2022). The model was applied in an empirical study based on farmers crop cutting survey in Central Kalimantan Indonesia. Results show that the proposed Beta Four Parameter GLMM has a better model fit. The model showed that pest attacks, pest handling, and resource allocation was considered the most influential variable affecting paddy productivity. Hence, it is suggested that the government must focus to construct a comprehensive strategy to improve paddy productivity by making it more resilient to pest and having more sufficient resource allocation management.

Effect of Input Subsidy Reduction on Greenhouse Emission Reduction Potential in Paddy Production Systems in Karnataka State of India

Increasing concerns and call for reduction in Greenhouse gas (GHG) emission have necessitated the search for broader and all-inclusive policy initiatives, extending into agricultural production, where high carbon energy inputs are used. One classical policy strategy for GHG emission reduction, has been taxation. However, given the critical role of agriculture, especially in developing economies, policies that directly or indirectly increase agricultural inputs costs and reduce their demand require stronger theoretical, conceptual and empirical support to ensure that while agri-environmental quality is promoted, welfare of farming households, food security and overall economic growth are not compromised. Using paddy production in Karnataka state in India, the study assessed effects of agricultural input taxation (reduction in rice input subsidy) on future demand for such inputs and their effect on GHG emission reduction, vis-a-viz production and welfare losses. In microeconomic modelling framework, we applied quadratic almost ideal demand system and stochastic efficiency functions in the analysis of the data. Data for the study, a micro-level farm data, was obtained from Cost of Cultivation Scheme (CSS) for irrigated and non-irrigated production systems, covering the period 2009 -2018 production seasons. Specifically, the study used three future tax regime scenarios- 10%, 20% and 30% input subsidy reduction rates, to model an optimum greenhouse emission reduction potential. The results revealed that inputs evaluated were normal with inelastic demand functions; many input coefficients implied significant complementary relationships; irrigated paddy production system had higher estimates of GHG emissions. Input taxation (reduction in subsidy) under all the three scenarios effectively, resulted in declined inputs consumption patterns, and subsequently led to significant decrease in greenhouse emissions. The highest GHG emission reduction potential was observed in irrigated farming system. Greenhouse emission reduction potential was optimal at moderate subsidy reduction policy rate of 10%. It is recommended that, given the inelastic estimates derived, moderate tax (reduction in subsidy) policy option on inputs would yield effective greenhouse mitigation with appropriate compensation through effective integrative schemes.

The Knowledge of Climate Change among the Paddy Farmers of Kahama District, Shinyanga Region Versus Meteorological Data

The study investigated the knowledge of the paddy farmers of Kahama District on climate versus three decades meteorological data in the District. Cross sectional research design was employed on which a randomly selected sample of 312 farm households were interviewed. The study employed a triangulation approach on which primary data were collected through household surveys, field observation and key informants’ interviews. Secondary data on the other hand were obtained from the Tanzania Meteorological Station (TMA) and were subjected to excel sheet on which linear series of rainfall and temperature were reported. The findings from primary and secondary data revealed changes in both rainfall and temperature in around three decades. The knowledge among the farmers on climate change was reported to be acquired in diverse ways including from the meteorological stations, information sharing among the farmers, NGOs and own experience. Farmers perceived a decreased in the onset and cessation of rainfall, increased pests and diseases and increased drought incidences. Secondary data obtained from the meteorological station confirmed the decreased rainfall and rising temperature in 30 years. These challenges negatively impact paddy productivity in the study area. The study recommends on upscaling of information dissemination among the farmers and across the other parties involved in paddy productivity. Further investigation on contextual-level adaptation responses is recommended as well.

A Study on the Impacts of Fertilizer Crisis on Paddy Cultivation in Five Selected Divisional Secretariat Divisions of Trincomalee District During Maha 2021/22

Rice is one of the most important cereal crops in the world. With population growth, farmers have to increase paddy production to meet existing as well as future demand. Fertilizer is the major input in rice production. Growth and yield traits of rice are affected by improper and imbalanced application of plant nutrients. Hence, suitable practices of adequate rate and timing of fertilizer application are needed to increase the rice yield. In May 2021, Imports & Exports (Control) Regulation No 07 of 2021 was issued, banning the importation of chemical fertilizers, pesticides, & herbicides in Sri Lanka. Low fertility of paddy soil created the need for adequate and constant supply of chemical fertilizers in paddy cultivation, which is a major threat to production and endangers the national food security and economy of Sri Lanka, especially in the major cropping season of Maha 2021/22. Therefore, a questionnaire survey was conducted to investigate the impact of the fertilizer crisis in major paddy-cultivating Divisional Secretariat divisions of the Trincomalee district. The random sampling method was used to select respondents for the survey, and the collected data were statistically analyzed by SPSS version 26.0 software. The results revealed that the majority of the farmers experienced a 50% yield reduction compared to the last cropping season of Maha 2020/21 in the entire five DS divisions. The seedling stage was highly affected during the fertilizer crisis in paddy cultivation in all five DS divisions. Further, the cost of production in paddy cultivation increased by more than 50% during the fertilizer crisis compared to the cost involved in Maha 2020/21. The potential for organic manure production is very poor, while the majority of farmers are interested in adopting the sustainable farming system of the Integrated Plant Nutrient System through the judicious application of chemical and organic fertilizers received on a subsidy basis, according to the present government’s fertilizer policy, which emphasizes 70% of inorganic fertilizers and 30% of organic manure application to improve sustainability in paddy cultivation in the country.

Hectareage Prediction Models for Paddy Crop of Middle Gujarat

The present investigation was undertaken with a view to identify the models for predicting the hectareage of paddy crop of the middle Gujarat region. The investigation was carried out on the basis of secondary data covering the period of nineteen years, (1998-99 to 2016-17). The District level data relating to hectareage, production, productivity and farm harvest prices of paddy were obtained from the published and compiled information by Directorate of Agriculture, Gujarat State, Gandhinagar. The linear multiple regression technique (basically Nerlovian type) was employed. The eight single equation and four simultaneous equation (SE) models were tried for paddy crop, the following models were selected on the basis of the values of adjusted coefficient of multiple determination. SE model-III for paddy is given below.HEPD = 40960.532**** - 10.414*** HEBJ + 0.784 HEMZ - 1.187**** HEPDL + 3.720*** HEBJL + 5.588**** EYPD + 0.866 EYBJ - 6.205*** EYMZ- 6.833**** EPPD + 1.502 EPBJ (R2= 0.946)HEBJ = 3261.298 - 0.061 HEPD + 0.108 HEMZ - 0.093 HEPDL + 0.337 HEBJL + 0.441 EYPD + 0.220 EYBJ - 0.619 EYMZ - 0.594 EPPD + 0.227EPBJ (R2= 0.960)HEMZ = 1816.343 + 0.028 HEPD + 0.147 HEBJ + 0.220 HEBJL + 0.649 HEMZL - 0.120 EYPD - 0.176 EYBJ - 0.092 EYMZ - 0.226 EPMZ - 0.106EPBJ (R2= 0.850)*, **, ***, **** Significant at the 20, 10, 5, 1 percent level of significance, respectivelyFor the selected crops, SE model was recommended for prediction of the current hectareage on the basis of the adjusted coefficient of multiple determination ( R 2). For Paddy hectareage the main affecting factors viz., bajra hectareage, lagged hectareage of paddy, expected yield of maize and expected price of paddy. Expected yield and expected price of paddy were determining factors of bajra hectareage.

A Season-wise Analysis of the Extent of Adoption of Popular Rice Varieties in Telangana, India

A Season-wise Analysis of the Extent of Adoption of Popular Rice Varieties in Telangana, India

A Comparative Analysis of Machine Learning Algorithms for Predicting Paddy Production

For countries with large populations, such as Indonesia, food security is a very important issue. The majority of Indonesia's population depends on rice as their main food, and paddy is one of the most widely cultivated food commodities. The very good and accurate national paddy production prediction results really support decisions regarding national paddy production targets for the coming period. Therefore, to ensure supply and price stability, paddy availability must be predicted. Many studies have used machine learning to predict crop yields. By learning important patterns and relationships from input data, machine learning can combine the advantages of other methods to make better predictions of paddy yields. The aim of this research is to conduct a comparative analysis between three machine learning algorithms, namely, random forest, decision tree, and k-nearest neighbors, in predicting paddy production. To determine which algorithm is the best, a model evaluation is carried out using the coefficient of determination (R2-score), mean absolute error (MAE), and mean squared error (MSE). This research goes through methodological stages, starting from collecting datasets, data preprocessing, training and testing split datasets, applying algorithms, and evaluating the model. From this research, results were obtained for the random forest algorithm with an R2-score of 82.38%, MAE of 261726.20, and MSE of 2.19495E+11. For the decision tree, the R2-score was 79.62%, MAE was 323257.99, and MSE was 2.49304E+11. Meanwhile, k-nearest neighbors obtained an R2-score of 76.25%, MAE of 318433.42, and MSE of 2.90577E+11. The results of this research show that the random forest algorithm is the best for predicting paddy production because it obtains a larger R2-score as well as smaller MAE and MSE results.

Adoption of Improved Paddy Cultivation Practices among the Farmers in Durg District, Chhattisgarh, India

The present study was conducted in Durg district of Chhattisgarh state during the years 2022–23 to study the farmers' adoption of improved paddy cultivation practices. One hundred twenty respondents were randomly selected based on the criteria that no previous study had been undertaken. Farmers were personally interviewed using a pre-tested interview schedule. The majority of respondents had a high (15.83%), medium (53.34%) and low (30.83%) adoption level, hence, there is a necessity to provide training programs through Krishi Vigyan Kendras (KVKs) and the Agricultural Departments to improve paddy cultivation methods so that the farmers can enhance their adoption levels of paddy production technology. The independent variables, namely age, education, annual income, farming experience, social participation, extension contacts, land holding, economic motivation and risk orientation were positively and significantly correlated with the adoption behaviour of paddy growers towards improved paddy production practices.

Effect of Windbreaks (Casuarina equisetifolia L.) on Productivity of Paddy in South Gujarat

The intentional integration of trees into an agroecosystem results in agroforestry practices such as windbreak, which simultaneously help the economy, the environment, and society. It is a crucial tool for safeguarding agricultural land and boosting crop productivity. An investigation was therefore conducted to determine the impact of windbreaks (Casuarina equisetifolia L.) on paddy productivity in South Gujarat. In the current study, we found that environmental competition caused paddy growth and production to decrease close to the Casuarina windbreak. The impact of the windbreaks on paddy growth and yield became positive, and the continuously increased distance from the windbreaks reached its maximum at 17 m (Plant height 97.34 cm, number of tillers per plant 11.17, total fresh weight plant 17,799 kg ha-1, dry straw weight 6,577 kg ha-1 and grain yield 4,103 kg ha-1) and then gradually decreased (plant height 83 cm, tillers per plant 8.17, total fresh weight plant 12,315 kg ha-1, dry straw weight 4,855 kg ha-1 and grain yield 3,101 kg ha-1). The wind velocity maximum (4.57 km hr-1) close to windbreaks exhibits an opposite tendency, decreasing continually to a minimum (3.32 km hr-1) at a distance of 17 meters from the windbreaks before increasing once again. In addition, this system's net returns (Rs. 40,619) and benefit-cost ratio (0.61) were noticeably higher than those of open fields (Rs. 34,749 and benefit cost ration 0.52). In contrast to the control, the pH of the soil beneath the windbreak was reported to be considerably closer to neutral (7.46), while electrical conductivity (0.19 dS/m) was reduced. The impact of windbreaks was found to considerably increase soil organic carbon (0.68%), accessible nitrogen (234.46 kg/ha), phosphorus (75.75 kg/ha), and potassium (398.07 kg/ha) as compared to control. According to the study's overall findings, windbreak-protected paddy fields perform noticeably better than open ones.

Development and Standardization of a Climate Vulnerability Index to Measure the Vulnerability Indices of Paddy Growers

India is prominently recognized as the foremost producer of paddy, cultivating this crop over 47.83 million hectares and generating 135.75 million tonnes of paddy, thus playing a substantial role in the worldwide paddy output. However, there is an anticipated decline in paddy production yields due to the projected effects of climate change, estimated to range from 10% to 30% by 2030. The assessment of vulnerability will give a comprehensive picture of current and future climate change risks with more stress factors to be anticipated. It will help identify opportunities arising from climate change, and provide information on how to assess adaptive capacity and cope with uncertainty. Adaptation cannot be planned based on the climate projections; information on risk and vulnerabilities is also needed to determine how the climate interacts with socio-economic issues. Against this backdrop, the proposed research seeks to fill this crucial knowledge gap by developing and constructing vulnerability indices tailored specifically for paddy growers in India. Based on review of literature and discussion with experts, three dimensions along with indicators and sub-indicators by adopting the indicator approach method under the vulnerability indices of paddy growers due to climate change were identified. The relevancy rating score was obtained from 50 experts in the concerned area. Based on the relevancy score, 17 indicators and 65 sub-indicators of 0.80 and above were considered for inclusion in the vulnerability index. To compute the index values for each of the identified dimensions, their relative importance in the vulnerability was worked out by assignment of weights to indicators and sub-indicators under each dimension through Principal component analysis (PCA) and the findings revealed that sensitivity was observed to be in the top position (8.36), followed by exposure (8.28) and adaptive capacity (5.61) in assessing the climate vulnerability of paddy growers.

Development and Standardization of an Adaptation Index to Assess the Climate Resilient Practices by Paddy Growers

India is prominently recognized as the foremost producer of paddy, cultivating this crop over 47.83 million hectares and generating 135.75 million tonnes of paddy, thus playing a substantial role in the worldwide paddy output. However, there is an anticipated decline in paddy production yields due to the projected effects of climate change, estimated to range from 10% to 30% by 2030. In recent times, adaptation to climate change has become a major concern to farmers, policy makers and researchers. Climate resilient rice production practices need to be enhanced at the farm level in order to aid rural residents in improving their household food security. Against this backdrop, the proposed research seeks to fill this crucial knowledge gap by developing and constructing adaptation index tailored specifically for paddy growers in India. Through a literature review and discussions with experts, we have identified indicators and sub-indicators using the indicator approach method. These indicators will help us understand how paddy growers are adapting to climate change and implementing climate resilient practices. The relevancy rating score was obtained from 30 experts in the concerned area. Based on the relevancy score, 8 indicators and 23 sub-indicators of 0.80 and above were considered for inclusion in the adaptation index. To compute the index values for each of the identified indicators, their relative importance in the adaptation practices was worked out by assignment of index values to indicators through Principal component analysis (PCA) based on the high factor loadings exceeded 0.5 of sub-indicators were considered and the findings revealed that disease and management had highest index value of 3.461, followed by methods of paddy establishment (2.195), crop rejuvenation techniques (2.10), altered planting dates (2.049), water saving and management techniques (1.987), nursery management (1.562), paddy varieties (1.342) and spacing (1.214).

Are rice systems sustainable in Sri Lanka? - A case of Deduru Oya reservoir irrigation scheme

Sustainable rice systems play a crucial role in achieving sustainable development goals, particularly in countries like Sri Lanka that heavily rely on paddy production. The study aims to examine the economic, social, and environmental sustainability gaps of a rice production system at various spatial scales using the Sustainable Rice Platform (SRP) framework v2.1 and identify interventions that can address these gaps. Data for the study was collected through a structured questionnaire, which incorporated the 12 performance indicators of the SRP framework, including profitability, labor productivity, grain yield, water productivity, nutrient use efficiency, biodiversity, greenhouse gas emission, food safety, health and safety, child labor and youth engagement, and women empowerment. The survey was conducted over two consecutive cropping seasons, in 2019 dry and 2019/2020 wet seasons, in selected paddy fields representing three topo-sequences within the Deduru Oya irrigation project in Sri Lanka. The study's findings revealed that the rice systems' profitability ranges from 475 ± 45 to 642 ± 59 USD/ha across seasons and topo-sequences, and a yield gap of approximately 33% was observed. Substantial exploitable gaps were observed in labor productivity (67%–77%) and water productivity (58%–68%). Additionally, there was significant variability in nutrient use efficiency and greenhouse gas emissions due to variations in water management practices. The social sustainability of rice systems has received lower scores, particularly for health safety and women empowerment. The study attributed most of the economic and environmental sustainability gaps in the agricultural practices of cultivators, while various socio-political and cultural factors influenced the social sustainability gaps. This study offers valuable insights to policymakers and practitioners in countries with extensive rice systems, aiding their efforts toward achieving sustainable development goals.