Paddy Production Research Articles

Effect of alternate wetting and drying technique (AWD) on water productivity of paddy in major irrigation schemes – A case study in Mahaweli System B

This report investigates the effectiveness of the Alternate Wetting and Drying (AWD) technique on water productivity and yield in paddy cultivation within Mahaweli System B, located in Sri Lanka's dry zone. With increasing water scarcity, particularly during the Yala season, farmers struggle to meet irrigation demands using traditional methods. The study compares AWD with conventional irrigation practices, focusing on its ability to reduce water consumption while maintaining or increasing rice yields. Two paddy fields were selected for trials, and the results show that fields using AWD consumed significantly less water, averaging 3.7 feet per acre, compared to 5.3 feet in conventionally irrigated fields. Moreover, AWD fields produced an average yield of 6.04 tons per hectare, an increase of over 100 kg compared to the control fields, which yielded 5.04 tons per hectare. The technique also reduced the frequency of irrigation events, offering a practical solution to water management challenges in the region. These findings indicate that AWD can enhance water productivity without sacrificing crop yield, making it a promising strategy for areas facing water scarcity. However, further studies across multiple seasons and varied locations are recommended to validate its long-term benefits and adaptability.

Nexus of climate change, irrigation requirement and water balance for paddy production in Chandra Canal Irrigation System, Nepal

Nexus of climate change, irrigation requirement and water balance for paddy production in Chandra Canal Irrigation System, Nepal

Determinants of paddy production during COVID-19 regime in Andhra Pradesh

Determinants of paddy production during COVID-19 regime in Andhra Pradesh

Unveiling the Welfare Puzzle: Exploring Fertilizer Subsidy Effects on Farmer's Earnings in Indonesia

This study investigates the unresolved issue of how fertilizer subsidies affect paddy production and farmer income, a critical aspect of Indonesia's agricultural policy that has not been fully understood. By analyzing panel data from 33 provinces between 2019 and 2022 using the Generalized Least Squares (GLS) method, the research explores both income dynamics and productivity. Results reveal that NPK and SP36 fertilizers boost paddy yields by 0.198% and 0.155%, respectively, while UREA and ZA have no significant impact on production. Additionally, rising wages reduce production by 1.343% but increase farmer income by 0.332%. These findings highlight the complexity of balancing productivity with farmer welfare, suggesting that while fertilizer subsidies can enhance yields, they are not a universal solution. Policymakers must consider multifaceted approaches that address both productivity and sustainable income growth to ensure long-term welfare improvements for Indonesian farmers.

Spatial Heterogeneity of Soil Nutrient in Principal Paddy and Cereal Production Landscapes of Fengtai County within the Huai River Basin, Eastern China

The problem of cultivated land soil quality in the Huaihe River Basin has become increasingly prominent. How to accurately and quantitatively evaluate the soil quality of regional cultivated land and realize its efficient use has become an urgent problem. In order to explore the spatial autocorrelation and variation in soil nutrients in cultivated land in the plain of Fengtai County in the Huaihe River Basin, a total of 306 soil samples and mature wheat samples were collected in the study area to analyze soil pH, total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), available potassium (AK) and slow-release potassium (SK) content and wheat biomass, and combined with geostatistical methods and GIS technology. The Kriging interpolation method and Moram‘s I index method were systematically analyzed. Principal component analysis (PCA) and Pearson correlation analysis were used to establish the minimum data set (MDS) of soil quality, which was used to calculate the soil quality index (SQI) and determine the key factors affecting soil quality. The results showed that the soil pH was in weak variation, and the other nutrient indexes were in medium variation. The spatial variability of soil-available potassium nutrients was affected by random factors such as human activities and structural factors such as soil parent materials. The spatial autocorrelation of organic matter, total nitrogen, alkali-hydrolyzable nitrogen, available phosphorus, available potassium and mitigation potassium was weak, which was mainly affected by random factors such as human activities. An unequivocal positive spatial nexus was discerned across all nutrients. Cumulatively, the nutrient dispersion across the investigated territory was somewhat diffuse, manifesting in a mosaic pattern with pronounced zonal nutrient allocation disparities in the meridional, median, and septentrional segments. An explicit latitudinal dichotomy delineating zones of nutrient opulence and paucity was also observed. These insights can pave the way for tailored fertilization strategies and judicious pedological stewardship in Fengtai County.

Deep Learning with Crested Porcupine Optimizer for Detection and Classification of Paddy Leaf Diseases for Sustainable Agriculture

India has a vast number of inhabitants and the main food source distribution is from agriculture. Agricultural lands are being demolished generally owing to plant and crop illnesses. The detection of plant diseases by using image processing models can aid agriculturalists in defending the farming area from damaging or affecting it. Paddy is the main harvest worldwide. Early recognition of the paddy diseases at dissimilar phases of development is very vital in paddy production. However, the present manual technique in identifying and classifying paddy diseases needs a very educated farmer and is time-consuming. Deep learning (DL) is an effectual research area in the classification of agriculture patterns where it can efficiently solve the problems of diseases identification. Therefore, the articles focus on the design and expansion of Deep Learning based Crested Porcupine Optimizer for the Detection and Classification of Paddy Leaf Diseases (DLCPO-DCPLD) method for Sustainable Agriculture. The main aim of the DLCPO-DCPLD method use DL method for the recognition and identification of rice plant leaf diseases. To accomplish this, the DLCPO-DCPLD technique performs the image pre-processing using Median Filtering (MF) to recover the excellence of the input frames. Next, the ConvNeXt-L method is applied for extraction of feature vectors from the pre-processed images. Also, the Conditional Variational Autoencoder (CVAE) model is utilized for the automated classification of Paddy Leaf diseases. Eventually, the hyperparameter tuning of the CVAE technique is accomplished by implementing the Crested Porcupine Optimizer (CPO) technique. To safeguard the enhanced predictive results of the DLCPO-DCPLD method, a sequence of experimentations is implemented on the benchmark dataset. The experimental validation of the DLCPO-DCPLD method portrayed a superior accuracy value of 99.12% over existing approaches.

Comparative Analysis of Paddy Cultivation Sustainability through Integrating Eco-efficiency and Best-Worst Method Approaches

To investigate the sustainability of agricultural systems, it is necessary to prioritize production systems from various viewpoints. The current research, as a new approach, aimed at prioritizing different paddy cultivation areas in Iran based on sustainability criteria using the best-worst method (BWM), which is regarded as one of the modern multi-criteria decision-making techniques. Mazandaran, Fars, and Khuzestan areas in Iran with different climatic classes, i.e., Mazandaran, Fars, and Khuzestan, were considered in this study. Sustainability criteria included energy, exergy, economic, and environmental indices, and the prioritization process was done based on the eco-efficiency index and BWM method. In the evaluation of the eco-efficiency index, the amount of net income and the total environmental index were considered as economic and environmental indices, respectively. In the prioritization of the BWM method, ranking was done based on energy and exergy efficiency, benefit-cost ratio, and the total environmental index. The results of the eco-efficiency index investigation demonstrated that paddy production in Mazandaran province had the most sustainability and compatibility with the environment, followed by Fars and Khuzestan provinces, respectively. The results of the BWM method prioritization also indicated that Mazandaran province was the best and most sustainable area with a final index of 0.98, followed by Fars and Khuzestan provinces, which were placed in the next ranks of sustainable paddy cultivation areas with final indices of 0.93 and 0.85, respectively. In conclusion, the paddy production systems located in the humid subtropical region were found as the most sustainable systems in this area.

Enhancing the productivity of paddy through frontline demonstrations for SC farmers of Chamarajanagara District, Karnataka

Enhancing the productivity of paddy through frontline demonstrations for SC farmers of Chamarajanagara District, Karnataka

Assessing Efficiency Of Paddy Farming In Deli Serdang Regency, North Sumatra, Indonesia

The use of agricultural input is significant for farm management. It would relate to productivity and efficiency. The problem is that the paddy farmers still needed to determine the appropriate agricultural input use level to achieve efficiency. This study aims to assess the efficiency of paddy farming in Deli Serdang Regency, North Sumatra, Indonesia. This study evaluated the efficiency of paddy farming with three types: technical efficiency, allocative efficiency, and economic efficiency. A survey was conducted with 40 paddy farmers to obtain data on paddy production and agricultural input use such as seed, fertilizer, chemicals, and labor. Data envelopment analysis with an input approach was employed to analyze the data. The scores of technical efficiency, allocative efficiency, and economic efficiency were 0.935, 0.711, and 0.668, respectively. This study indicated that paddy farming in Deli Serdang Regency, North Sumatra, Indonesia, was technically efficient. However, it was allocative and economically inefficient. The unachieved cost minimization was the driving factor of the allocative inefficiency. Furthermore, this study also found that the condition of paddy farming increased the return to scale (IRS). This condition implied that the paddy farmers could escalate the paddy production and achieve efficiency by improving agricultural input use. Moreover, eco-friendly agricultural input is encouraged to minimize costs to improve allocative efficiency and support sustainable agriculture. Also, the government should take some actions and policies to improve the efficiency of paddy farming in Deli Serdang.

Comparative analysis of production and marketing aspects of deficit and surplus paddy production areas in Bangladesh

The study aimed to compare production and marketing aspects in deficit and surplus paddy production areas in Bangladesh. For this study, a face-to-face interview was conducted with a semi-structured questionnaire. The survey was carried out in two districts from February to March 2022. Data were collected from a total of 113 paddy farmers from Brahmanbaria, a deficit district, and 128 farmers from Habiganj, a surplus district. According to this study, farmers in surplus districts have excellent geographic characteristics such as medium-high land and a triple crop area, while farmers in deficit districts suffer unfavorable conditions such as low land and flooding. The study also discovered that there are differences between the districts in terms of land availability, paddy cultivation area, and cropping intensity. In production aspects, the size of the farmland and the productivity differ significantly at the 1% level between the districts. Deficit farmers produce less paddy per acre compared to farmers with surplus districts. In the paddy marketing channel, local paddy assemblers (LPA) are the dominant actors in the deficit and LPB/local paddy brokers in the surplus area. Farmers in surplus areas have more marketing facilities and get higher paddy revenue and profits compared to deficit districts. However, farmers in both districts are mostly dependent on traders to sell their produce. In that case, paddy marketing facilities can accumulate through farmers’ community investment and the organization of cooperative societies. It will help improve farmers’ negotiation power at the village level in both districts. Res. Agric. Livest. Fish. Vol. 11, No. 2, August 2024: 173-183

Envirotyping helps in better understanding the root cause of success and limitations of rainfed production systems

The current diagnostic agronomy study of the Bankura region of West Bengal, India, examined the variations in crop yields through a socio-ecological analysis of multiple production system components. Envirotyping for root cause analysis was employed to delve into the variables that affect the performance of rainfed production systems. Mother Earth, man, machine, management, and materials (5Ms concept) were the five indicators under which the variables were grouped. Findings demonstrated the fragility of the region’s soils due to its undulating terrain, unpredictable rainfall patterns, and frequent drought scenarios. The LULC’s NDVI showed that the agricultural area is about 60% and 43% of the total geographical area in the Hirbandh and Ranibandh blocks, respectively. Soils are acidic and diagnosed with deficiency of both macro and micronutrients (phosphorous, sulfur, and boron) having poor water holding capacity (35 to 55 mm for a 50 cm soil depth). The sand and soil organic carbon contents ranged between 43.04%–82.32% and 0.17%–1.01%, respectively with a low bacterial population. These factors are the root cause for low cropping intensity (106%) and low paddy productivity (3,021 kg/ha). Overall, the study contributes to designing and scaling-up of sustainable landscape management practices that could ensure higher cropping intensity and system productivity in similar agro-ecologies with limited evidence.

Knowledge, attitude and practices of smart farming technology for small scale farmers in paddy production: A case study in Melaka

Knowledge, attitude and practices of smart farming technology for small scale farmers in paddy production: A case study in Melaka

Responses of Methane Emission and Bacterial Community to Fertilizer Reduction Plus Organic Materials over the Course of an 85-Day Leaching Experiment

Methane produced from paddy fields has a negative impact on global climate change. However, the role of soil bacterial community composition in mediating methane (CH4) emission from waterlogged paddy soil using the column experiment is poorly known. In the present study, various fertilization treatments were adopted to investigate the effects of fertilizer reduction combined with organic materials (CK: control; CF: conventional fertilization; RF: 20% fertilizer reduction; RFWS: RF plus wheat straw amendment; RFRS: RF plus rapeseed shell amendment; RFAS: RF plus astragalus smicus amendment) on CH4 emission and soil bacterial community during an 85-day leaching experiment. We hypothesized that the fertilizer reduction plus the organic materials could enrich the bacterial communities and increase CH4 emission. The average CH4 flux varied from 0.03 μg m−2 h−1 to 76.19 μg m−2 h−1 among all treatments in the nine sampling times, which may account for the experimental conditions such as air temperature, moisture, and anthropogenic factors. In addition, high-throughput sequencing was utilized to investigate the alteration of the soil bacterial community structure. It was revealed that the diversity and composition of the bacterial community in the topsoil amended with organic materials underwent significant shifts after the 85-day leaching experiment. Proteobacteria was identified as the dominant phylum of the soil bacteria, with an average proportion of 35.2%. For Firmicutes, the proportion of RFRS (11%) was higher than that in the CK (8%), RF (8%), RFWS (7%), RFAS (6%), and CF (5%) treatments. Additionally, Gammaproteobacteria and Alphaproteobateria were supposed to be the major class bacterial communities, with average proportions of 12.8% and 12.2%, respectively. For the RFWS treatment, the contribution of Alphaproteobateria was the highest among all the bacterial relative abundance. According to the correlation heatmap analysis, the top ten bacterial communities were positively related to soil microbial biomass carbon (MBC) and ammonia nitrogen (NH4+-N) (p < 0.01). The findings also indicated that the RFRS treatment was the favorable management to alleviate CH4 emission during an 85-day leaching experiment or possibly in paddy production. Collectively, these results predict that the impacts of different treatments on CH4 production are strongly driven by soil microbial communities and soil properties, with soil bacteria being more prone to the crop residue degradation stage and more sensitive to soil properties. The discoveries presented in this study will be useful for assessing the efficacy and mechanisms of organic material amendments on CH4 emissions in paddy soil.

Influence of natural farming vs conventional farming practices on growth and dry matter production of paddy

Influence of natural farming vs conventional farming practices on growth and dry matter production of paddy

Assessing the formation and stability of paddy soil aggregate driven by organic carbon and Fe/Al oxides in rice straw cyclic utilization strategies: Insight from a six-year field trial

Soil organic carbon (SOC) and iron/aluminum (Fe/Al) oxides are key cementing agents in driving soil aggregate formation, yet their direct effects and interactions on aggregate under long-term rice straw cyclic utilization (LSCU) in cold regions are still unclear. We compared chemical fertilizer (CF) with LSCU strategy: rice-straw (RS), biochar (RB), and biochar-based fertilizer (BF). We showed that the increase of macroaggregate (2–0.25 mm) is associated with SOC, dissolved organic carbon (DOC), humin carbon (HUC), amorphous and organic complexed Fe/Al oxides (Feo, Fep, Alo, Alp), and in each size of the aggregate, there exists an interaction between SOC (fractions) and Fe/Al oxides. Furthermore, aggregate stability was determined by Feo, Fep, and Alo. LSCU enhances macroaggregate and aggregate stability by increasing SOC and Fe/Al oxides in the bulk soil and aggregates, but there are differences among LSCU. In all treatments, RS had more DOC, fulvic acid carbon (FAC), humic acid carbon (HAC) and Fep; while RB had more SOC, HUC, free Fe/Al oxides (Fed, Ald), Feo, Alp; and BF had more Alo in bulk soil. Over the years, RS increased the DOC, FAC and HAC, whereas RB enhanced the stable SOC fractions (HUC) and promoted high reactive Fe/Al oxides formation (Feo, Fep, Alo), and BF increased DOC, Feo, Fep and Alo. Moreover, RB increases the direct pathway of SOC and Fe/Al oxides to aggregate, promoting aggregate formation. Our study provides new perspective on the mechanisms and promising practice for improving rice straw utilization efficiently, paddy soil fertility and productivity sustainably in cold regions.

Impact Assessment of Integrated Pest Management Technology on Kharif Paddy Cultivation in Vidarbha Region of Maharashtra, India

The Eastern Vidarbha region consist of Bhandara, Gondia, Gadchiroli and Chandrapur and some part of the Nagpur district is famous for specialized farming and paddy as major crop. The total area in Maharashtra state was 15.53 lakh hectares with annual production 34.81 lakh tons of rice (Anonymous 2023-24). About 80.00 per cent gross cropped area in this region is under paddy. IPM has been proved to be a cost minimization technique. Losses in Paddy yield the tune 10 to 25 per cent occurs due to attack of insect pest and disease. Being the topic of such high importance from cultivators point of view, the research topic has been selected i.e. Impact Assessment of Integrated Pest Management technology on Kharif Paddy cultivation in Vidarbha region of Maharashtra State its economic investigation in different level of adoption of IPM technologies. The study was carried out with the main goals of determining the extent to which recommended technology has been adopted in Kharif paddy production by using principle component analysis approach and for develop the composite index, examining the input utilization of Kharif paddy at varying levels of IPM adoption, and workout cost effectiveness and profitability of kharif paddy at different level of adoption of IPM technology. The study was conducted in the districts of Gadchiroli in the Vidarbha region of Maharashtra State, India. Three tahasil, Gadchiroli, Chamorshi and Dhanora were chosen from these districts, and a total of 120 farmers were selected from seven villages, namely Gadchiroli, Indala, Hirapur, Chamorshi, Krishna Nagar, Heti, Kanartola. The primary data, which cover the years 2023–2024. Total 120 farmers, 25 farmers were classified as high adopters, 76 farmers were classified as medium adopters, and 19 farmers were classified as low adopters. As a result of input usage, the group with a high adoption level utilized the most human labour. Farmyard manure is used most in the high adopter group (49.87 quintal per hectare), followed by low adopters (31.73 qtl/ha) and medium adopters (34.45 qtl/ha) because the farmers can apply only owned farm FYM. The reasons of lower used of FYM, due to shortage of cattle’s population. The reasons of low adopter, high expenditure of Integrated pest management components was the 89.00 per cent farmers can use chemically control that means 2 to 3 spraying was use in kharif paddy in low adopter group. The B:C ratio at Cost ‘A1’ was 1.79, 1.85 and 1.92 in low, medium and high adopters, respectively, while B:C ration at Cost ‘C2’ for low, medium, high adopter were 1.12,1.19,1.25 respectively. The results concluded that the low adopters group are not making more profit. It indicates that, as adoption of technology increases the yield level of crop and so that the net returns also increases. The reduction in per quintal production cost at Cost ‘C2’ over low adopter group were Rs. 188.06/-. Paddy productivity has been reported increased by 19.84 per cent with the reduction in the cost of Rs. 7375.89 in high level of adoption of Integrated Pest Management Technology. The findings of the present study with regards to overall adoption of integrated pest management practices of paddy by paddy growers were observe for wide adoption of IPM technology in Kharif Paddy, Government should take initiative for production of bio-agents and available the pheromane trap and yellow sticky trap through establishing unit in Government Agricultural Offices and Krishi Vigyan Kendra and encourage the rural youth for establishing Units at taluka level.

Four-parameter beta mixed models with survey and sentinel 2A satellite data for predicting paddy productivity

Ensuring food security, fostering agricultural sustainability, and driving economic development. However, existing prediction models often overlook the unique characteristics of paddy productivity distribution, which varies between areas, skewed, and bounded within a certain minimum and maximum range, following a four-parameter beta distribution. Consequently, these models yield less accurate and potentially misleading predictions. Additionally, most approaches fail to capture the complex interrelationships among variables that often occur when we incorporate satellite data alongside survey data that has been recognized as a key approach for improving prediction accuracy and optimizing farming practices. To address these shortcomings, this study introduces a four-parameter beta Generalized Linear Mixed Model (GLMM) augmented within a four-parameter beta Generalized Mixed Effect Tree (GMET). The four-parameter beta GMET, an extension of the four-parameter beta GLMM model integrated with a regression tree, offers enhanced flexibility in modeling complex relationships. Application of this methodology to an empirical study in Central Kalimantan and Karawang reveals notable improvements over previous methods, as evidenced by substantially lower AIC and RRMSE values. Notably, the analysis identifies lagged values of band 4, band 8, and NDVI from Sentinel-2A satellite data as significant predictors of paddy productivity, overriding the importance of farmer survey variables. This underscores the potential of satellite data to be utilized in paddy productivity predictions, offering a more efficient and cost-effective alternative to farmer survey-based methods. By enhancing satellite technology, future efforts in paddy productivity prediction can achieve higher efficiency and accuracy, contributing to informed decision-making in agricultural management.

Assessing Groundwater Use Efficiency and Productivity across Punjab Agriculture: District and Farm Size Perspectives

While previous studies have focused on the technical aspects of groundwater extraction and optimal cropping patterns, there is a notable lack of research on the socio-economic factors affecting groundwater access and agricultural productivity, especially at a micro-level in Punjab, India. This study, therefore, investigates the water use efficiency (WUE) and economic water productivity (EWP) of paddy and wheat crops across diverse farm sizes and districts in Punjab, offering critical insights into agricultural water management. The study is based on primary data from Punjab, India, with Sangrur, Jalandhar, Pathankot, and Bathinda districts selected for groundwater profile analysis via multistage random sampling of 246 farmers. Notably, Punjab exhibits high EWP for wheat, surpassing the national average. However, disparities exist across districts, emphasizing the importance of localized interventions. Larger farms consistently demonstrate higher WUE and EWP, underlining the significance of scale in optimizing water inputs. Factors such as farm size, crop variety, and regional variations significantly influence WUE and EWP. Tailored approaches for marginal farmers and districts with lower efficiency are crucial for promoting sustainable agricultural practices. The findings underscore the need for targeted policy interventions to enhance water use efficiency and productivity in Punjab’s agriculture sector.

FACTORS EFFECTING PADDY PRODUCTIVITY IN THE MADA REGIONS, MALAYSIA

Rice commodity is becoming increasingly important for most countries worldwide, particularly those where rice is the main staple meal. This study examines the socioeconomic attributes of farmers, their perspectives on management practises, and the implementation of paddy machinery technology in the four MADA (Muda Agricultural Development Authority) regions in Malaysia. The study aims to determine the main factors effecting paddy productivity in the MADA regions. Primary data was collected from paddy farmers in the four MADA zones using a standardised questionnaire. The data was collected from 673 respondents from four regions of MADA. The analysis employed both descriptive statistics and regression analysis. The results indicate that variables such as land area, selection of paddy planting as the primary occupation, increased time spent on paddy farms, gender, and the educational background of farmers have a significant impact on paddy productivity in the MADA regions. The findings also show that, only a small percentage of respondents (6.2%) followed the crop schedule, and 93.8 percent of them were late. The utilisation of machinery in paddy cultivation achieved the following results: nine farmers achieved a success rate of 85.71 percent, while a majority of farmers (662 farmers) achieved a 71.43 percent utilisation rate, with one farmer earning the lowest usage rate of 57.14 percent. In conclusions the study has found that it is imperative to promote the use of management practises and advanced machinery technologies among paddy farmers to effectively increase productivity.

A Decade Analysis (2013-2023) of Paddy's Yield Productivity by Using Landsat 8 Imagery in Sukoharjo District, Indonesia

Sukoharjo District has the highest rice productivity in Central Java. Sukoharjo has a strategic location. It makes this area prone to land use changes. It makes a severe impact on Paddy's productivity. This condition needs to be monitored continually. Remote sensing can provide an efficient and accurate method to solve this condition. Using the NDVI from Landsat 8 imagery and ubinan data, the model can be built to calculate and analyze paddy’s productivity. The steps were 1) interpretation of paddy fields area; 2) calculation of NDVI’s mean values a month before harvesting; 3) interpretation accuracy test; 4) correlation value between NDVI and ubinan data in 2022; 5) calculation of paddy productivity; and 6) analysis. Within a decade (2013-2023), there was a reduction in paddy's yield area for 981.90 Ha. During that period, there was an increase in paddy's productivity, around 38.2 x 103 tons. Almost all sub-districts in Sukoharjo’s yield had been reduced except for Tawangsari and Weru. Kartasura and Grogol have experienced an intensive change in paddy yields to non-paddy yields. Intensive land use changes affected paddy’s productivity. Multi-temporal imagery combined with ubinan data can be used to monitor paddy’s productivity. Forty-one points were calculated for the y (productivity) and x (NDVI value) equation. The equation resulting from this method (y=6.2212x+6.7444) can be used as a reference for calculating productivity in Sukoharjo District in different periods. From different calculations, the accuracy obtained from this method was 86%.Keywords: Landsat 8; NDVI; Paddy’s Productivity; Sukoharjo; Ubinan data