Minimum Support Research Articles

Integrating agricultural land suitability and farmers' perception on crop selection in a water-stressed region of eastern India

CONTEXTThe choice of crops for cultivation should be ideally based on the appropriateness of a specific parcel of land for a particular crop. This is a multi-criteria problem associated with a host of natural conditioning variables including topography, climate and pedology. However, in a country like India, where agriculture is often traditional and subsistence-based, the farmers' choice of crop selection is usually influenced by numerous factors and therefore, may not be explained solely by the spatial variation in the agricultural land suitability. OBJECTIVEThis study is an attempt to understand the intricacies involved in the farmers' selection of crops by integrating the dual aspects of agricultural land suitability and the farmers' understanding of the land. The Kumari River Basin in eastern India has been selected for this study. This area is characterized by acute scarcity of water. METHODSThe basic methodology involved extracting systematic information on conditional factors such as topography, climate and soil. After normalizing different parameters by the Fuzzy Membership Function, a reiterative Principal Component Analysis modified Analytical Hierarchy Process was applied to these conditional rasters to derive an index of agricultural land suitability of the studied basin. Furthermore, the crop-specific suitability of paddy and maize was also considered by employing the Boolean Logic. RESULTS AND CONCLUSIONSIt is observed that the lower domain of the Kumari Basin is characterized by greater land suitability as compared to the upper and middle domains and the most important factors behind this distribution include slope, potential evapotranspiration and soil fertility. Crop-specific land suitability suggests that, by and large, the suitability of maize is greater than that of paddy in the basin, except for the lower domain where paddy is more suitable to cultivate. However, a study of the perception of the local farmers reveals that although they are aware of this fact, they prefer paddy over maize and are more inclined towards cultivating paddy. The chief reasons cited by them include the high demand for paddy in the area and the absence of a Minimum Support Price for maize. SIGNIFICANCEThis study is possibly an instance where the agricultural land suitability analysis has been substantiated by a field-based perception survey of the farmers which is expected to help in understanding the complexities of crop selection in this part of India.

Right ventricular free wall longitudinal strain as a predictor of myocardial recovery in patients with advanced cardiogenic shock supported with the Impella device

Abstract Background Right ventricular (RV) dysfunction is a known independent factor influencing the outcome of patients in cardiogenic shock (CS). The aim of this monocentric retrospective study was to investigate the impact of left ventricular (LV) unloading on the right heart function and its predictive role regarding weaning following Impella device implantation in patients with profound CS due to LV failure. Methods We performed a retrospective analysis of 41 patients admitted to intensive care unit over a period of 3 years with CS due to LV dysfunction requiring support with Impella. Clinical and echocardiographic data were collected and correlated with weaning success. Finally, a multivariate analysis to identify independent predictors of weaning success was performed. Results After Impella implantation, the following was observed: right ventricular fractional area change (RVFAC) increased from a mean value of 28% to 38% (p=0.01), the tricuspid annular systolic velocity (TASV) increased from 9 cm/s to 10 cm/s (p=0.01), the velocity time integral right ventricular outflow tract (VTI RVOT) increased from 10 to 13 cm3/stroke (p=0.01), the right ventricular free wall longitudinal strain (RVFWLS) increased from -12% to -21% (p< 0.001). However, following LV unloading, a decrease in both RVFAC from 38% to 30% (p 0.01) and in VTI RVOT from 13 to 11 cm3/stroke (p<0.01) was observed. Moreover, there was a significant decrease in RVFWLS from -21% to -14% (p < 0.001). Notably, the percentage of change in RVFWLS between maximum and minimum (Δ%RVFWLSPmax-Pmin) support with Impella during the weaning process was significantly lower in weanable patients (34.5% in weaned vs 86% in non-weaned; p=0.038). Investigating the predicting ability of these parameters, Δ%RVFWLSPmax-Pmin emerged showing an AUC of 0.826 (0.690-0.962) in identifying non-weaned patients with a cut-off value of 38%. According to the multivariate analysis, Δ%RVFWLSPmax-Pmin in non-weaned patients remained the only significant parameter even considering possible confounders. Conclusions LV unloading with Impella in advanced CS patients improved RV function echocardiographic parameters. RVFWLS increased significantly after Impella implantation and its percentage of change between maximum and minimum support was significantly lower in weanable compared to non-weanable patients. Our findings suggest that RVFWLS could be used as a predictor of myocardial recovery allowing to identify weanable patients with adequate accuracy.

Echocardiographic evaluation of ventricular performance in VA-ECMO weaning: results from a observational monocentric prospective study

Abstract Background Although temporary mechanical circulatory support (MCS) devices are increasingly used in the management of cardiogenic shock (CS), several open question regarding the kind of support and timing of institution/weaning remains open. Echocardiography is widely applied to drive the weaning process and decision although there are no standardized protocols for the trial nor accordance on the parameters to apply. Purpose We sought to evaluate the overall accuracy of echocardiographic indices in predicting successful weaning from VA ECMO in patients with CS. Specifically, we tested total isovolumic time (tIVT), an index of ventricular performance, and longitudinal function (MAPSE) on top of the commonly used parameters (left ventricular ejection fraction, LVEF; left ventricular velocity time integral, LV VTI; TAPSE; right ventricular S’ at tissue Doppler imaging, RV S’). Methods Monocentric prospective study on adults receiving VA-ECMO due to refractory CS and/or cardiac arrest (CA) from 2012 to 2020. Echocardiography was performed at VA-ECMO placement and during the weaning trials. Weaning trials were performed daily, starting 48 hours after VA-ECMO institution, when patients were hemodynamically stable: mean arterial pressure >65 mmHg, no or minimum adrenergic support (vasoactive inotropic score <10), heart rate <110 bpm, lactate <2 mmol/L, and no signs of respiratory distress. Weaning trials were performed with a stepwise decrease of VA-ECMO blood flow until reaching 1 or 1.5 L/min under adequate anticoagulation. Successful weaning was defined as removal of VA-ECMO with no requirement for further MCS in the following 30 days. Results 76 patients were enrolled (23.8% female, 54.2±10.6 years-old), 52.6% due to CA. Median duration of VA-ECMO was 58 hours; 47 (61.8%) had intra-aortic balloon pump (IABP) inserted upfront. In-hospital mortality was 62.4% overall, 40% for CS without CA. 6 of the 32 weaned patients died for multiorgan failure due to septic shock. The baseline echocardiographic parameters associated with successful weaning were (table): stroke volume >13.9 mL (p 0.002), tIVT >23.6 min/sec (p 0.053), LV VTI >6.6 cm (p<0.001), MAPSE >6.15 mm (p 0.001), TAPSE >11 mm (p 0.023), RV S’ >10 cm/s (p 0.012). LVEF did not reach the statistical significance. Figure shows Kaplan-Meier analysis on echocardiographic indices collected at time of cannulation (panel A) and during the last weaning trial (panel B). Conclusions Echocardiography is pivotal in defining cardiac recovery and monitoring the weaning trial. Indices reflecting ventricular performance and delivered flow from LV were associated with weaning success both at VA-ECMO institution and throughout the weaning trials. Considering the known limitations of LVEF (heart rate, loading and left ventricular dyssynchrony dependence), tIVT and MAPSE should be introduced in the standard evaluation of patients in the acute setting.TableFigure

From Field to Market: The Challenges Faced by Onion Growers in Chitradurga, Karnataka, India

Horticultural crops are integral to the Indian economy, serving as a major source of employment, and supplying vital raw materials to the food processing sector. Their cultivation leads to enhanced farm profitability, driven by increased yields and improved market opportunities. Moreover, the export of horticultural produce significantly contributes to foreign exchange earnings, further strengthening India's economic framework. Onion grows extensively across the nation in a variety of climates. India is the world's second-largest producer of onions. It ranks first in terms of acreage, third in terms of exports, and contributes roughly 22.83% to global production. The present study was conducted in 2023 in the Chitradurga district of Karnataka, aimed to identify the challenges faced by onion growers and gather their recommendations for addressing these issues. A total of 120 farmers were selected for the study, comprising sixty small and sixty big farmers. Utilizing an ex post facto research design, data were collected through a pre-tested, structured interview method. The findings highlighted several key constraints in onion cultivation, including limited awareness of nutrient management, price fluctuations in the market, and inadequate access to credit. The majority of farmers recommended the implementation of a minimum support price for onions and timely provision of credit at low-interest rate to mitigate these challenges.

Seasonal Behaviour of Arrivals and Prices of Major Crops in Krishi Upaj Mandis of Chhattisgarh, India

Chhattisgarh state is famous for its forest wealth and mineral resources and there is abundant production of crops. According to total area of crops, Paddy (77.47 percent) and Chickpea (5.43 percent) are major crops of Chhattisgarh state. Arrivals and price data (Year 2014-15 to 2023-24) of major crops were collected from website of Chhattisgarh state Mandi Board. The study was observed that the peak arrivals & price of paddy were started in the same months November to January in both market (KUM, Bemetra & KUM, Bhatapara) except peak price season starts in August to October with narrow difference in KUM, Bhatapara. In case of Chickpea, the peak arrivals and price started in the month of March to May & September to November, respectively. The Price stability of both crops (paddy & Chickpea) was higher in KUM, Bhatapara as compared to KUM, Bemetra. The less price fluctuation of paddy as compared to chickpea in Chhattisgarh state due to purchasing directly to farmers by the Government with Minimum Support Price (MSP) and also provided the Bonus. The study was suggested that the economic development of farmers in state, the government should purchase agricultural products other than paddy and cooperate in setting up dal mills & processing units. Necessary steps should be taken to increase of marketable surplus and development of community level threshing area. The study was importance in knowing the market behaviour and price fluctuation during the peak season and the major reason behind. The studies also throw light on the aspect how to enrich the economic condition of the farmers.

Minimum Support Price, Agrarian Issues and Farmers’ Movement in India

Minimum Support Price (MSP) is one of the many important aspects related to agricultural development. Farmers have been demanding MSP for decades, but the demand for legalisation of MSP has been raised prominently by the contemporary farmers movement. On the one hand, farmers had been engaging in protests in Tikri, Singhu (Delhi–Haryana border) and Ghazipur (Delhi–UP border) throughout the year (2020–2021) for legalisation of the MSP. On the other hand, the government is in favour of neoliberal policy and saw the MSP as an agro-ecological and financial risk. This article uses quantitative and qualitative methods to establish a relationship between MSP, agrarian issues and the farmers movement in India. The result shows that the MSP policy has had a very negative impact on agro-ecology and groundwater conditions in Punjab, Haryana and Western UP.

Assessing Economic Sustainability in Gujarat’s Cereal Sector: Trends in Costs, Prices, and MSP (2001 – 2022)

The data highlights the changes in MSP over the years for each cereal. It's evident that MSPs have generally increased over time, although the rates of increase vary among different crops and years. The correlation analysis provides valuable insights into the relationships between MSP, wholesale prices, farm harvest prices, and the cost of production. Strong positive correlations between these variables indicate significant interdependence within the agricultural market. Notable changes in increasing order in MSP (Minimum support price) was seen over years in all cereals. Years with negative values in excess of actual MSP over COP (Cost of Production) suggested farmers were not able to cover even COP and years with positive values suggested farmers were in profitable margin after covering COP. Cost and prices of all the selected cereals were having high correlation between MSP, WP (Wholesale Price), FHP (Farm Harvest Price), COP (C2) and COP (A2 + FL (Family Labour). Highest growth rate amongst the particulars was seen for MSP in pearl millet and lowest for COP (A2 + FL) in pearl millet. More variability was seen in MSP for pearl millet and low variability was seen in MSP for Wheat. Overall, analysis provides a comprehensive understanding of the agricultural landscape in Gujarat state.

Role Of Government Policies In Shaping Vegetable Marketing Practices: Evidence FromRajasthan

This study examines the impact of government policies on vegetable marketing practices in the Indian state of Rajasthan. Using primary data collected from surveys of 500 farmers, 100 wholesalers, and 50 retailers across five districts of Rajasthan, as well as secondary data fromgovernment reports and academic literature, the paper analyzes how various national and state-level agricultural policies have influenced the structure and functioning of vegetable value chains in the region. Key policies considered include the Agricultural Produce Market Committee (APMC) Act, contract farming laws, minimum support prices (MSP), and agricultural subsidies. The results show that the APMC Act has led to the development of a network of regulated wholesale markets which serve as the main marketing channel for vegetables, but its provisions restricting sales outside these markets have hindered direct linkages between producers and buyers. Recent reforms aimed at allowing private markets and removing barriers to interstate trade have had limited impact so far. Contract farming remains underdeveloped due to regulatory uncertainty and lack of trust between stakeholders. MSP haslittle relevance for most vegetable crops given their perishability and lack of public procurement. Input subsidies, while increasing yields, have exacerbated problems of overuse of chemicals and declining water tables. The paper argues for a more holistic, nutrition-sensitive approach to agricultural policy that goes beyond a narrow focus on boosting production and marketable surplus. Specific recommendations include investments in storage and cold-chain infrastructure, expansion of crop insurance coverage, promotion of Farmer Producer Organizations and shorter supply chains, and greater emphasis on sustainable production practices and nutrition education. Enhancing smallholder access to credit, information, and input-output markets remains critical

Analisis Perbandingan Algoritma Apriori dan FP-Growth untuk Menentukan Strategi Penjualan Pada Maestro Jakarta Cafe & Space

There has been a decline in sales at Maestro Jakarta Cafe & Space due to a lot of competition and not optimal management of transaction data so that innovation is needed to increase sales. This study aims to compare the performance and results of the Apriori and FP-Growth algorithms in analyzing sales transaction data to determine the optimal sales strategy. This research uses the Apriori and FP-Growth methods to analyze sales transaction data by applying the Cross-Industry Standard Process for Data Mining (CRISP-DM). The data used is product sales transaction data from November 2023 to April 2024. The results of performance comparisons in processing time speed and memory usage that have been carried out show that in processing time speed the FP-Growth algorithm is slightly faster than the Apriori algorithm while in the use of memory capacity the Apriori algorithm requires a larger memory capacity than the memory capacity used by the FP-Growth algorithm. This shows that the performance of the FP-Growth algorithm is better than the Apriori algorithm. The analysis results of the Apriori and FP-Growth algorithms on sales transaction data using a minimum support value of 1% and a minimum confidence value of 100% resulted in 22 association rules. Both algorithms produce identical rules, with the only difference being the occurrence index. The results of this analysis can be used by Maestro Jakarta Cafe & Space in determining sales strategies.

Pemodelan Data Mining Transaksi Penjualan Menggunakan Algoritma Apriori (Studi Kasus: Kedai Ngodeng & Smoothies)

The role of UMKM is very large in the growth of the Indonesian economy, Kedai Ngodeng & Smoothies, as one of the UMKM that is active in the food and beverage industry. This shop has not made maximum use of sales transaction data. The transaction data is only used as an archive and is not used to organize sales strategies. In this research, the method used is the a priori algorithm to determine the relationship between one product item and other product items so that it can be used as a promotional package or bundling to increase sales profits. The data used is sales transaction data for the Ngodeng & Smoothies shop from January to May 2024. The research began with initial data collection, followed by data description and evaluation of data selection. After that, attribute selection is carried out. The CRISP-DM method is applied in this research which includes six stages, namely business understanding, data understanding, data preparation, modeling, evaluation and dissemination. Based on the results of the research, there are 95 Association Rules based on previously determined parameters, namely the minimum support value is 50% and the minimum confidence is 90%. One of the rules that was formed is that Smoothies Mangga Large, Twister, Kembang Cumi --> Odeng Spicy has a confidence value of 100%. The information obtained can provide important insights into customer preferences and can be used to design more effective product bundling promotions.

Intelligent Identification of Hidden Dangers in Hydrogen Pipeline Transmission Station Using GWO-Optimized Apriori Algorithm

This work proposes an intelligent grey-wolf-optimizer-improved Apriori algorithm (GWO-Apriori) to mine the association rules of hidden dangers in hydrogen pipeline transmission stations. The optimal minimum support and minimum confidence are determined by GWO instead of the time-consuming trial approach. Experiments show that the average support and average confidence of association rules using GWO-Apriori increase by 29.8% and 21.3%, respectively, when compared with traditional Apriori. Overall, 59 ineffective association rules out of the total 105 rules are filtered by GWO, which dramatically improves data mining effectiveness. Moreover, 23 illogical association rules are excluded, and 12 new strong association rules ignored by the traditional Apriori are successfully mined. Compared with the inefficient and labor-intensive manual investigation, the intelligent GWO-Apriori algorithm dramatically improves pertinency and efficiency of hidden danger identification in hydrogen pipeline transmission stations.

ANALISIS ATURAN ASOSIASI KESALAHAN STATISTIKA SISWA KELAS X-11 SMA NEGERI 10 SAMARINDA BERDASARKAN KRITERIA WATSON

Mathematics plays an important role in forming systematic thinking patterns, logic, and financial management skills. However, many students have difficulty in understanding mathematical concepts due to various factors, which affect the success of learning. This study aims to identify and classify common errors of class X-11 students of SMA Negeri 10 Samarinda in solving statistics problems using mixed quantitative and qualitative methods. solving statistics problems using mixed methods, namely quantitative and qualitative. Using the apriori algorithm with a minimum support of 20% and 80% confidence, four types of errors were found that were often made by students, namely incorrect data errors, procedural errors, missing conclusions, and skill hierarchy problems. Data analysis and interviews showed a strong correlation between these errors, where errors in data collection often lead to data manipulation and incorrect conclusions. To overcome this problem, the school has implemented more effective learning strategies, such as additional guidance, material adjustments, and contextual approaches. These strategies are expected to improve students' conceptual understanding, reduce errors, and improve academic achievement in statistics.

Korelasi Antara Karakteristik TKI dengan Jenis Pekerjaan Menggunakan Metode Apriori

This study addresses the issue of Indonesian migrant workers (TKI) whose characteristics do not match the jobs assigned abroad, often leading to complaints from agencies and companies. This mismatch is caused by incorrect job placements and insufficient training, which prompts TKI to leave their assigned jobs. The research aims to better understand the characteristics of TKI that influence successful job placement. The **apriori** method was used to identify patterns and relationships between TKI characteristics, destination countries, and suitable job types. Based on a 30% minimum support, 3 and 4 itemset combinations were produced, showing correlations between TKI characteristics and job positions. Using lowerboundminsupport 0.001 and minmetric 0.1, this study generated 6 itemsets from 13 data points, providing significant correlations between TKI characteristics and more accurate job placements.

Turmeric Cultivation in Erode District: An Analysis of Farmer Constraints

Turmeric farming is a key agricultural activity in the Erode District of Tamil Nadu, contributing significantly to the region's economy. However, farmers in this area face a myriad of constraints that hinder their productivity and economic stability. This study investigates the specific challenges encountered by turmeric growers, focusing on technical, economic, marketing, storage, and general constraints. In terms of production, consumption, and exports, India leads the world in turmeric usage. India is estimated to produce 11.7 lakh metric tonnes of turmeric in 2022–2023. Telangana, Maharashtra, Karnataka, Tamil Nadu, Andhra Pradesh, Madhya Pradesh, and West Bengal are the main states in India that produce turmeric. In Tamil Nadu, 96,000 metric tons of turmeric are grown around 20,000 hectares. An ex-post facto research design was employed, with Kodumudi Block selected due to its prominence in turmeric cultivation in Erode district. A proportionate random sampling technique was used to select 120 respondents from five villages: Vengampur, Punjai Kollanali, Unjalur, Kollathupalayam, and Kodumudi. The inclusion of an interview schedule as the data collection tool adds depth to the study, as it allows for a structured approach to gathering information directly from the respondents, ensuring the reliability and validity of the findings. The data that were gathered was compiled and subjected to suitable statistical analysis like cumulative frequency method, percentage analysis and ranking method. The findings reveal that the most critical issues include high fluctuations in market prices, pest and disease outbreaks, inadequate storage facilities, and a lack of technical guidance. Economic challenges such as high input costs, difficulty in securing loans, and insufficient subsidies further exacerbate the situation. Marketing constraints, including poor transportation infrastructure and the absence of regulated markets, force farmers into distress sales. General issues like labor shortages and inadequate irrigation facilities add to the farmer burdens. To address these challenges, the study suggests implementing efficient irrigation systems, promoting integrated pest management (IPM) programs, establishing community-based storage facilities, and strengthening farmer cooperatives to enhance their bargaining power. Additionally, introducing government-backed procurement systems with minimum support prices (MSP) and improving access to financial services are recommended as the solutions. By tackling these constraints, the study aims to enhance the sustainability and profitability of turmeric farming in Erode District, ensuring a stable livelihood for the farmers.

Agrarian Distress in Indian Agriculture: Causes, Socio-economic Consequences and Coping Strategies

Agrarian distress is the economic, political and social challenges faced by the farmers and rural communities due to factors such as low crop yields, fluctuating prices of agricultural produce, high input costs, indebtedness, and lack of access to credit, markets, and infrastructure. Over 8,00,000 individuals are dies by suicide each year because of various reasons. More over the suicides are happening in the families whose own land is less than 1-2 hectares, who are in debt, have been identified the most at risk for suicide. The present article aims at better understanding of the causes, consequences and possible coping strategies for the agrarian distress in India. Causes such as fluctuations in crop sales, weather and climate conditions, dependent on natural resources, etc. are discussed in detail. Consequences of agrarian stress are suicides of farmers, rural migration, food insecurity, environmental impacts and so on. Solutions such as strengthening the forward markets, comprehensive crop insurance schemes for the framers where the non-MSP (Minimum Support Price) crops also may be covered, assured price to the farmers are discussed. Many researchers argued that farmers suicides are increasing but the research is limited in the specialised area of interest. In addition to that, researchers are focussing only on the socio-economic variables rather than the psychological variables. In order to mitigate the risks out of agrarian distress, farmers should be encouraged by the government and extension service providers to take up the subsidiary occupations and secondary agricultural occupations which helps them in getting profits in the situations where the crop damages due to the extreme weather patterns. As rightly pointed out by National Bank for Agriculture and Rural Development (NABARD), distress of the framers should have a long-term potential solution such as major reforms in the existing agricultural laws rather than farm loan waivers which acts as the short-term relief to the farmers.

Analyzing the Determinants of Yarn Economics in the Cotton Industry: A Comprehensive Case Analysis

The cotton industry is a cornerstone of the global economy, influencing agricultural practices, trade, and industrial development. This study explores the key determinants shaping the cotton sector, focusing on procurement, price stabilization, export promotion, research and development, and skill enhancement initiatives. The Cotton Corporation of India (CCI) plays a crucial role in this ecosystem by ensuring fair compensation for farmers through minimum support prices, facilitating consistent cotton supply for the textile industry, and promoting exports to enhance market reach. Furthermore, the CCI's investments in research and development aim to improve cotton quality and resilience, addressing the industry's evolving challenges. Amidst these advancements, the cotton industry faces pressures such as price volatility, shifting consumer preferences, and an increasing emphasis on sustainable practices. This paper underscores the need for adaptive strategies and collaborative efforts among stakeholders, including farmers, manufacturers, and policymakers, to enhance the industry's competitiveness and sustainability. Future research should delve into the impacts of global market dynamics and technological innovations to better understand the cotton sector's opportunities and challenges.

Penerapan Algoritma Apriori untuk Rekomendasi Asuransi pada Nasabah

Jasindo Insurance Company is one of the insurance companies that receives insurance coverage both directly and indirectly, with ownership of 1 share of dwiwarna series A owned by the Republic of Indonesia and 424,999 shares of Series B owned by PT Bahana Pembinaan Usaha Indonesia (Persero). PT Asuransi Jasa Indonesia has several products and choices in choosing which insurance is needed by customers in agriculture, health, education and many more. Due to the large amount of competition in the business world, it requires management to find the right strategy in increasing the use of Jasindo insurance by knowing the relationship between age, gender, marital status, occupation and the type of Jasindo insurance that is widely chosen by customers. In order to find out the use of insurance that is widely used by the community, it is necessary to analyze the data on the use of insurance using the apriori algorithm method to determine the combination between item-sets of transaction data on Jasindo insurance data. Based on the research conducted after experimenting with the above case with a minimum support = 25%, confidence = 100% so that the results of the rule that meets the support and confidence values are obtained, namely if the gender is male, the marital status is Unmarried, then the type of insurance is jasimdo health and jasindo rainbow then giving value is successful with 25% support, 100% confidence.

Penerapan Algoritma Apriori Mengetahui Pola Tindakan Kriminal Berdasarkan Wilayah ( Studi Kasus : Polsek Sunggal)

Police Sector (Polsek) is one of the agencies that provide protection, order and ensure public safety in the sunggal area. The number of cases of criminal acts that occur makes residents feel unsafe and always feel threatened in certain areas in the Sunggal sub-district, the pattern of criminal acts that often occur due to several factors, one of which is due to the lack of security in the area so that many criminal acts occur as well as behaviour that has been planned by the perpetrator to achieve their goals by planning, preparing, implementing, disposing of evidence, even hiding or escaping depending on the type of crime committed based on the characteristics of the perpetrator, and the situation or context in which the crime occurred. Therefore, it is necessary to analyse techniques from existing criminal data using the a priori algorithm method to find patterns of relationships between variables that can assist agencies in taking action for public safety. Based on the research conducted, the above case is tested with a minimum support = 10%, confidence = 100% so that the results of the rule that meets the support and confidence values are obtained: ‘If the criminal act is theft then the job is self-employed’, then giving value is successful with 15% support, 100% confidence. And ‘If the age of 17-25 years, the criminal act is Theft then the job is unemployed’, then giving value is successful with 10% support, 100% confidence.

Advancing Redgram Productivity: Impact of Cluster Front Line Demonstrations in Wanaparthy District, Telangana, India

This study aimed to assess the productivity improvement of redgram under Cluster Front Line Demonstrations (CFLD) in Wanaparthy district in the operational area of YFA-KVK, Mahabubnagar-I. A total of 261 demonstrations were conducted over a seven-year period (2016-17 to 2022-23), covering 104.4 hectares during the kharif season under rainfed situation with protected irrigation. Results showed that with the introduction of improved high yielding short duration varieties -PRG176 and WRGE 97 when combined with seed treatment, recommended fertilizer doses, weed management, and plant protection, achieved an increase in average yield of 10.20 quintals per hectare, compared to 6.23 quintals per hectare with traditional farmers’ practices. Net returns averaged ₹35000 from CFLD demonstrations, significantly higher than the ₹14,230 from conventional methods, though variations were influenced by the Minimum Support Price (MSP) set by the Government of India. The study identified an average extension gap of 3.98 quintals per hectare between the demonstrated technology and traditional practices, with an average technology gap of 14.80 quintals per hectare across the years. This gap varied annually due to the performance of recommended varieties and interventions. The technology index correlated with the technology gaps. The findings suggest that redgram production can be significantly improved through the adoption of improved technologies via CFLD. Therefore, it is crucial to spread these improved technologies among farmers using effective extension methods such as awareness camps, farmers-scientist interactions, group discussions, trainings, demonstrations, field days, and exposure visits through CFLD.

Understanding and Explaining Recent Changes in Income, Consumption and Poverty Among Agricultural Households Across Major States of India

The study, using unit level data from two nationally representative surveys, examines changes in levels and sources of household income, consumption expenditure, incidence of poverty and determinants of household income and poverty among agricultural households. The study shows that across most of the states, there has been a significant decrease in the per cent share of income from cultivation coupled with an equally significant increase in the share of income from wages and salary; average annual household income of such households is higher than their average annual consumption expenditure and there has been a significant decrease in the incidence of poverty among them. The results of regression analysis show that household size, head of the household being male, literacy, farm size, income from cultivation, awareness of minimum support price (MSP), access to technical training, engagement in non-farm business and engagement in wages and salary have significant positive effect on households income and lower the probability of a household being poor across major states. JEL Codes: Q1, C1, C2, D1, R2