Farm Implements Research Articles

Analisis Pola Kemitraan Petani Tebu (Saccharum officinarum Linn) di PT. PG Rajawali II Unit PG Subang

PG Rajawali II unit of PG Subang made a partnership program as a solution to the company's crisis as well as a form of integrated agriculture implementation. After approximately 5 years of running the partnership program, there are still things that are felt to be lacking from this partnership program, such as capital, facilities and infrastructure, guarantee of selling prices for partner farmers, and lack of attention from the factory that is evenly distributed to all partner farmers. This study aims to see the results related to the PG Subang partnership program in the context of partnership patterns and farmer satisfaction. This study uses a descriptive quantitative approach and is supported by descriptive qualitative data. The researcher assigned 80 partner farmers as respondents using simple random sampling, a measurement tool using a Likert scale. Overall, PG Subang's partnership program is in the good category. The partnership pattern used by PG Subang is the Plasma Core partnership pattern, in this case PG Subang moves as the core and partner farmers as plasma. With an importance value of 4.89, there are aspects of reliability and responsiveness that show that farmers are very concerned about the stability and availability of support from the program. However, there is still concern about the PG's response. Subang in responding to complaints and solving problems in the field.

PENGARUH MODAL SOSIAL TERHADAP KAPASITAS MANAJERIAL PETANI JAGUNG DI DESA UMBA KECAMATAN NAPANO KUSAMBI KABUPATEN MUNA BARAT

This study aims to ascertain the social capital and managerial capacity of farmers, as well as to determine the influence of the social model on the managerial capacity of corn farmers in Umba Village, Napano Kusambi Subdistrict, West Muna Regency. The research population comprises all individuals engaged in the cultivation of corn in Umba Village, amounting to a total of 32 individuals. The sample was selected using the census method, resulting in a sample size of 32 respondents for this study. Data were collected through observation, surveys, and structured interviews, with the use of a questionnaire. This study employed a quantitative approach. The variables under investigation are divided into two categories: social capital and managerial capacity among farmers. The data were subjected to two distinct forms of analysis. Initially, a quantitative descriptive analysis was conducted utilising the class interval formula to delineate the prevailing conditions pertaining to social capital and managerial capacity among maize farmers. Subsequently, a multiple linear regression analysis was employed to ascertain the influence of social capital on the managerial capacity of maize farmers. The multiple linear regression analysis is comprised of three tests: the T-test, F-test, and determination test. The findings indicate that the utilization of social capital among corn farmers in Umba Village is classified as favorable. This is evidenced by the presence of a robust level of trust, a commendable application of norms, and a relatively strong network of social connections. The managerial capacity of maize farmers is categorized as good, as evidenced by their effective maize farm planning and organization. However, there are areas for improvement, particularly in the dimensions of maize farming implementation and supervision, which remain in the poor category. Social capital has a significant positive effect on the managerial capacity of maize farmers, amounting to 29.1%, with 70.9% influenced by other factors.

Exploring the Socio-economic Conditions of Potato Farmers in Farrukhabad District of Uttar Pradesh, India

This study investigates the socio-economic profile of potato growers in Farrukhabad district, Uttar Pradesh, aiming to understand their demographic composition, educational background, caste distribution, marital status, family structure, landholding size, occupation, income levels, social participation, and possession of farming resources. A sample of 100 respondents cultivating potatoes as the main crop was selected from Kamalganj block, Farrukhabad district. Data were collected through personal interviews using a pre-structured schedule and analyzed using percentages. The results reveal that the majority of respondents are middle-aged, literate, and belong to scheduled castes. Most respondents are married and come from joint families with medium-sized households. Marginal and small landholdings dominate, and agriculture is the primary occupation, supplemented by subsidiary activities such as dairying and business. Income levels vary, with a significant proportion falling within the medium-income bracket. Social participation is moderate, with most respondents engaging in multiple organizations. Farm resources such as farm power and implements are moderately possessed. Extension services and information sources play a crucial role, with most respondents exhibiting moderate contact. This study provides valuable insights into the socio-economic landscape influencing agricultural practices among potato growers, which can inform policy formulation and extension activities aimed at fostering agricultural development and rural prosperity.

The Effect Of Good Dairy Farming Implementation On The Income Level And Efficiency Of Dairy Cows Farmers Businesses In West Malang Regency

The research aims to identify the implementation of Good Dairy Farming Practice, measure the income and efficiency of livestock business. The research was conducted in West Malang Regency from November 2021 to February 2022 in three sub-districts namely Pujon, Ngantang and Kasembon. Samples were taken as many as 100 using purposive sampling method. Data analysis was descriptive quantitative to identify the Good Dairy Farming Practice score, analysis of business efficiency with Cobb Douglass Production Function Regression, analysis of business income and influential factors with Multiple Linear Regression. The results showed that the application of GDFP with sufficient score categories is health aspects (2.84), milking hygiene aspects (2.76), feed nutrition and drinking water aspects (2.43), animal welfare aspects (2.87), environmental aspects (2.64), and unfavorable score category is socio-economic aspects (1.37). The average income of dairy farmers is IDR 70,959,024 per year. The results of income regression analysis showed that the variables of health and nutrition aspects had a very significant effect, the milking hygiene aspect had a significant effect, and the environmental aspect had a less significant effect. The results of the efficiency of the use of factors of milk production with a value of 1.215 showed increasing returns to scale. All aspects of GDFP are in the sufficient category and the socio-economic aspects are in the unfavorable category. This makes the farmer's income less than optimal.

Conservation tillage (CT) for climate-smart sustainable intensification: Benchmarking CT to improve soil properties, water footprint and bulb yield productivity in onion cultivation

Environmental sustainability indicators for conservation tillage (CT) in agricultural systems primarily focus on assessing the impacts on soil organic carbon (SOC) and water footprint (WF). One way to improve these indicators is by boosting crop production while minimizing environmental impact through the implementation of sustainable intensification (SI) and climate-smart agriculture (CSA) to ensure food security. Conservation agriculture (CA) based CT practice with crop residue retention has potential for benchmarking the conserving of water in agriculture, improving soil health, crop productivity and ensuring agricultural sustainability. The CT-based water-saving potential in onion cultivation nonetheless remains understudied in Bangladesh. For this, a field experiment was undertaken to assess soil properties and water footprint in onion cultivation in the Charland agroecosystem in Jamalpur, Bangladesh. Three different tillage practices, such as minimum tillage (MT), tractor tillage (TT) and conventional power tillage (PT), and flatbed flood irrigation were introduced with four replications. Tillage practices showed significant positive effects on yield characteristics and bulb yields. The findings indicate that the MT practice in onion (BARI Piaz-4) cultivation resulted in the highest fresh bulb yield of 22.79 t ha−1, followed by TT (20.48 t ha−1) and PT (16.25 t ha−1) practices. The MT practice achieved the highest water footprint (WF) savings of 40% water, where crop biomass, including above and below-ground parts, bulb size, yield characteristics, and yield productivity were significantly increased. The findings also indicate a direct correlation between the water productivity index (WPI), WF and the bulb yield under MT practice. The study's findings favor CT practice and, therefore, suggest a methodology of employing MT practice as a benchmark to increase agricultural water-saving potential. It can also be used as a reference for promoting water conservation practices achieving sustainable development and improving resource efficiency in agriculture.

A Coffee Plant Counting Method Based on Dual-Channel NMS and YOLOv9 Leveraging UAV Multispectral Imaging

Accurate coffee plant counting is a crucial metric for yield estimation and a key component of precision agriculture. While multispectral UAV technology provides more accurate crop growth data, the varying spectral characteristics of coffee plants across different phenological stages complicate automatic plant counting. This study compared the performance of mainstream YOLO models for coffee detection and segmentation, identifying YOLOv9 as the best-performing model, with it achieving high precision in both detection (P = 89.3%, mAP50 = 94.6%) and segmentation performance (P = 88.9%, mAP50 = 94.8%). Furthermore, we studied various spectral combinations from UAV data and found that RGB was most effective during the flowering stage, while RGN (Red, Green, Near-infrared) was more suitable for non-flowering periods. Based on these findings, we proposed an innovative dual-channel non-maximum suppression method (dual-channel NMS), which merges YOLOv9 detection results from both RGB and RGN data, leveraging the strengths of each spectral combination to enhance detection accuracy and achieving a final counting accuracy of 98.4%. This study highlights the importance of integrating UAV multispectral technology with deep learning for coffee detection and offers new insights for the implementation of precision agriculture.

KOMPARASI PREFERENSI PETANI JAGUNG DAN CABAI RAWIT DALAM MATERI PENYULUHAN UNTUK PERTANIAN BERKELANJUTAN

Suwawa Selatan is one of the areas vulnerable to climate change, this condition is caused by unsustainable agricultural practices such as land clearing on slopes and burning agricultural waste. This study aims to identify the level of knowledge and implementation of sustainable agriculture that is relevant to the needs of farmers and prioritize extension materials needed by farmers. The method used in this study is a quantitative method that uses BNA analysis techniques and independent T-test statistical tests. The results showed that maize farmers had a lower knowledge level than chili farmers regarding sustainable agriculture components. Meanwhile, chili farmers in Suwawa Selatan needed more materials to increase the use of organic fertilizers and reducing excessive soil plowing (priority), while the priority extension materials for corn farmers in Suwawa Selatan sub-district were reducing the use of chemical fertilizers and reducing the use of chemical herbicides (priority).

Strong Community-Academic Partnerships Led to Successful Implementation of Farm to School Programs in Rural Kentucky Schools

Strong Community-Academic Partnerships Led to Successful Implementation of Farm to School Programs in Rural Kentucky Schools

Impact of regulated deficit irrigation on the dynamics of quality changes in processing tomato fruits during ripening

Quality is a key factor restricting the development and economic benefits of the tomato processing industry, and improving the quality of tomatoes has become a hotspot in the development of the tomato processing industry in Xinjiang. Regulated deficit irrigation (RDI) is an abiotic means of crop yield and quality control widely used for crop yield and quality improvement. This study aimed to investigate the impact of RDI on the dynamics of quality changes in processing tomato fruits during ripening via a 2-year (2022–2023) filed experiment with five water irrigation treatments in Xinjiang, China. The results showed that compared with conventional irrigation, regulated deficit irrigation significantly saved 315–1260 m3 ha−1 irrigation water. Mild RDI increased the single fruit weight and fruit hardness by 0.15 % and 3.29 kg cm2, respectively, thus improved the yield and storage and transportation quality of processed tomatoes. Moderate RDI increased the contents of soluble solid, soluble sugar and lycopene in fruit to 0.6 %, 0.56 % and 3.53 μg/g, respectively, therefore significantly improved the nutritional quality and flavor quality of processed tomato. Ultimately, a comprehensive evaluation using a coupled Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model, taking into account the appearance, nutrition, flavor, and storage and transportation indexes of processed fruits, concluded tha W1 treatment is a sustainable water management approach that balances yield and quality. Therefore, the optimal deficit irrigation model for processing tomato fruits in Xinjiang was recommended to be the W1 treatment, whereas the W2 treatment was considered as an alternate model. The study supported the large-scale development of the tomato processing industry in Xinjiang and the implementation of effective water-saving farming.

Status of farm mechanization and factor affecting its adoption among the rice (Oryzae sativa) farmers in Sarlahi district, Nepal

This study aimed to investigate the degree of agricultural mechanization adoption and the factors influencing its acceptance in the Haripurwa municipality and Parsa rural municipality of Sarlahi district, specifically concerning rice agriculture using a multistage random sampling method. A total of 98 respondents were selected for the study, 52 were from Haripurwa municipality and 46 were from Parsa rural municipality. Primary data were collected using semi-structured questionnaires, focal group discussion, and key informant interviews whereas secondary data were obtained through review of relevant literature. The data was analyzed using descriptive statistics, scaling and indexing, chi-square tests, T-tests, and the logit model. By analyzing the adoption index, 62.245% and 37.755% of respondents were under the adopter and non-adopter categories respectively. In contrast to 100% physical labor for transplanting, fertilizer application, and other intercultural tasks like weeding and harvesting, the study found that land preparation was done mechanically (100%). The two biggest obstacles to the use of agricultural machinery were small farms scattered terrain and poor infrastructure with index values of 0.845 and 0.843, respectively. Major factors influencing agricultural mechanization were respondents' educational status, gender, farmers' experience, participation in organizations, loan availability, and primary source of family income. Thus, it can be said that socio-economic determinants which had a significant association with adoption status and most needed farm implements for farmers can be considered by the concerned authority to increase the farm mechanization and enhance profitability from rice farming.

Optimizing Agricultural Mechanization to Enhance The Efficiency and Productivity of Farming In Indonesia: A Review

Agricultural mechanization has emerged as a cornerstone of modernizing the agricultural sector in Indonesia, playing a pivotal role in enhancing productivity and efficiency. The growing population and the necessity for increased agricultural output have driven the adoption of mechanization to overcome challenges such as labor shortages and the adverse effects of climate anomalies. The introduction of agricultural equipment follows a selective principle by considering the local area's socioeconomic conditions. Future agricultural mechanization utilizes technologies based on weather analysis, soil sensor information, and satellite and drone imaging that can increase agricultural productivity. Precision agriculture innovation to improve the accuracy of farm business management is carried out by utilizing sensor systems, drones, remote sensing, digital technology, and the Internet of Things (IoT) to collect, process, and present data that smart farming systems will use. Integrated information system innovations for the supply chain are designed to bridge farmers, distributors, markets, and end buyers by utilizing mobile applications. The traditional to modern transition process and the implementation of smart digital farming require mentoring and field learning in the agricultural process from upstream to downstream. This review provides a comprehensive overview of the development, challenges, opportunities, and prospects of agricultural mechanization in Indonesia, offering insights into how these efforts can support the country's economic growth and food security. Materials were prepared from various sources, including development planning documentation program reports, evaluation, and critical analysis of different research results.

Social Economic Challenges of Adaptation to Climate Change in Masinga Sub-County, Kenya

Climate in Masinga sub-county has been changing at a momentum which is unprecedented in the recent human history. This area consists mainly small-scale farmers who depend on rain to carry out their farming activities. Coping strategies to the changing climate in the area has faced various challenges ranging from high poverty, low levels of education, age, gender among others. This study investigated how social-economic challenges affecting adaptation strategies on climate change among the households living in Masinga sub-county, in Kenya. The main objectives of the study included; 1) To examine the adaptation strategies employed by households in Masinga sub-county 2) To determine the main factors that affect household in adaptation to climate change in Masinga sub-county 3) To investigate the environmental implications of adaptation to climate change in Masinga sub-county. Essentially, variables such as education levels, age, gender, were assessed. In order to gain an understanding on adaptation strategies used by households in Masinga sub-county, the study was conducted in all six divisions. Various methods of sampling were used in the survey which included stratified random sampling based on the number of households proportionately in the six divisions. In essence, 384 household heads were sampled through stratified random sampling. The study employed specific data collection tools in order acquire data from the six divisions; structured questionnaires, interviews schedules, Focused Group Discussions (FGDs) and direct observation were used. Qualitative data was collected through; interviews, Desk research, Focus Group Discussions comprising six to eight sampled through stratified random sampling and purposive sampling. The households coping strategies, influence of adaptation strategy to climate change and environmental implications of household adaptation was analyzed through both qualitative and quantitative interpretation. Data from survey was organized and analyzed using descriptive and inferential statistics. The results were subjected to statistical package for social sciences (SPSS) to determine their reliability. When applying descriptive statistics, the results were presented in tables, bar graphs, and charts. In this study Chi-squire was used because it was easier to compare the results from a two dimensional perspective. These results after analysis by chi-square test, the p-value was found to be .001, thus, smaller than the significance level (α = .05). Using Chi-square tests, this study established that there is strong evidence of an association between the education level and the implementation of green-house farming (Χ2 (3) = 1.064, p = 0.001). Further analysis by chi-square test indicated that the p-value was found to be .008, thus, less than the significance level (α = .05). This study established that early warning as a strategy to adaptation to climate change was not common amongst households in the area. Further research is suggested on impact of charcoal burning on climate change adaptation and cost implications in semi- arid areas. The study findings will enable the government and other relevant stakeholders to ensure that early warning system information is able to reach the local residents at all times

DEVELOPMENT OF MEDICINAL VEGETABLE CULTIVATION FOR FAMILY USE (TOSGA) IN REALIZING SUSTAINABLE AGRICULTURAL INNOVATION FOR WOMEN IN PENGABUAN VILLAGE, ABAB DISTRICT, PALI REGENCY, SOUTH SUMATRA

In Pengabuan Village, women dominate poverty. The vulnerability of this group is explained by the fact that they do not have enough training, experience, and a source of investment to put food on their table (to meet even basic family needs, including healthcare). This journal in this case study is the implementation of the Independent Agriculture for Empowerment Village Women ("PERMATA") program, which is initiated by PT Pertamina EP Adera Field at Pengabuan Village, Abab Districts, Penukal Abab Lematang Ilir (PALI), South Sumatera. Its purpose is to increase economic welfare as well as the health of society by growing Medicinal Family Vegetables (TOSGA). Under the theme of building an inclusive and sustainable economy, PERMATA, in its fourth year, will focus on product diversification from TOSGA-derived herbs and group capacity building, followed by institutional mentoring. The program has had far-reaching effects on economic, social, and environmental welfare. One initiative has seen a dramatic increase in the income of women's groups and made a real dent in greenhouse gas emission targets through straw waste alternative energy. The PERMATA program has increased community awareness and capabilities in managing the environment and the production of herbs as flora medicinal plants. Through sustainable agricultural innovation, the program also improved quality life criteria or indicators of life.

Tillage and land use management effects on soil organic matter and soil microbial biomass in a field network of practical farms in France, Romania, and Sweden

A reduction in tillage intensity, organic farming, and introduction of ley-grass periods into the crop rotation are means to improve the sustainable use of arable soils. The current study uses an on-farm approach to investigate soils from different practical farms in Northern France, Central Sweden, and Romania in comparison with previously published results from randomized field-experiments nearby. No-tillage generally increased the mean SOC and total N contents of arable fields in comparison with ploughing. However, this increase was only significant for the 70 % increase at 0–10 cm depth in France. No-tillage had no general effects on MBC or MBN and increased the ergosterol content at 0–10 cm depth in France and Sweden but not in Romania. Averaging depths and tillage systems, median MBC significantly increased in the order France (220 μg g−1 soil), Romania (324 μg g−1 soil), and Sweden (384 μg g−1 soil), whereas the median MB-C/N ratios followed the order France (5.6), Sweden (8.3), and Romania (10.4). The study region-specific changes in soil pH significantly affected covariate MBC and MBN in the regression equations for equal slopes ANCOVA models. In Northern France, organic farming and ley-grass implementation into the crop rotation increased SOC and total N contents to the level of the no-tillage fields. On-farm research gives similar results to long-term field experiments in France, Romania, and Sweden. For this reason, on-farm research on practical fields is an important, less expensive alternative to randomized field experiments, with a high potential for investigating actual and relevant research objectives. This will intensify exchange in knowledge between scientists and farmers.

Evaluation of Standard Times for Some Local Blacksmith’s Products

The practice of menial farming in the southwestern part of Nigeria have necessitated the need for the blacksmith industry to produce farm implements for the need of their immediate environment (farmers). With increased cost and time of production, coupled with demand size, reduced productivity and in order to meet the customer’s schedule, the study was conceived to evaluate the standard time to start and finish a product to manage production time and to estimate the optimum production capacity of the blacksmith workstation. After a careful survey of the local blacksmiths and with the aid of a stopwatch and study time chart, standard time was evaluated for harvester, digger and axe. These implements are the most commonly used items by the locals. The standard time for the local blacksmith’s axe, digger and harvester production was estimated to be 1458.35, 1931.44 and 936.66 Seconds respectively. It can therefore be concluded that the blacksmiths working for 8 hours a day will produce either (i) about 20 units of axe per day, (ii) 15 units of digger per day, or (iii) 31 units of harvester per day, or (iv) 7 units each, of the products per day

Macro-Nutrient Prediction of Paddy Field Soil Using Artificial Neural Network and NIR Spectroscopy

Understanding soil fertility, influenced by macronutrients like nitrogen, phosphorus, and potassium, is essential for adaptive agriculture implementation based on various soil conditions. Near-infrared spectroscopy technology provides non-destructive, rapid soil property measurements without chemicals, applicable both in-field and in-laboratory. However, the wide NIR spectrum range and neural network complexities can hinder Artificial Neural Network (ANN) training and inference, leading to time and resource inefficiency, especially without sophisticated computing devices. This study examines data reduction methods to enhance ANN performance in predicting soil macronutrients using NIR spectra. Multiple Linear Regression (MLR) and Principal Component Analysis (PCA) were applied to select wavelengths from the 1000–2500 nm for ANN input, comparing their performance. About 237 NIR reflectance data from paddy soil were transformed into absorbance data. MLR used forward selection to identify wavelengths with correlations higher than 0.9, while PCA selected wavelengths corresponding to the loading factor peaks for each principal component. These selected wavelengths served as inputs for the ANN model. The ANN’s performance was assessed using correlation and determination coefficients, RMSE, RPD, and model consistency. For nitrogen, the PCA+ANN model with reflectance spectra performed better (RPD 2.4-4.8) than the MLR+ANN model (RPD 2.2-2.6) using fewer wavelengths (5-9 for PCA+ANN vs. 9-12 for MLR+ANN). For phosphorus estimation, the PCA+ANN model also excelled (RPD 2.3-7.0 vs. 2.3-2.4) with fewer wavelengths (4-7 vs. 7). For potassium estimation, the PCA+ANN model showed superior performance (RPD 4.3-9.5 vs. 4.2-4.4), using the same number of wavelengths (4-8 vs. 4-6).

Processos de vulnerabilização de empreendimentos eólicos em comunidade camponesa no Agreste Meridional de Pernambuco

ABSTRACT Amid sustainable agendas, renewable energy sources play a strong role, especially wind energy. However, the implementation of wind farms produces transformations in communities, causing impacts in different areas and vulnerability processes. The study aims to problematize the reports of the peasant population regarding the processes of vulnerability in the area of influence of the implementation of wind farms in a municipality in Pernambuco. This is an observational, descriptive research with a qualitative approach, carried out in a peasant community, located in the municipality of Caetés, Pernambuco, Brazil. Data collection was carried out through semi-structured interviews. Data analysis was based on the content analysis technique in the thematic modality. It was observed that the arrival and operation of the wind turbines coincided with the emergence of signs and symptoms, such as hearing and skin problems, anxiety, dizziness and headache. This situation allows us to consider a probable connection between the impacts caused by wind towers, already described in the literature, and those present in the participants’ reports. Prudence is necessary when planning and building wind farms, since such health problems can be temporary or permanent, leading the local community to constant suffering.

Life cycle assessment of oil palm plantation in Riau province: evaluating environmental impacts

Abstract Indonesia possesses palm oil as one of its strategic commodities, and it plays a crucial role in its economic growth. Over the years, the expansion of land and the production of Fresh Fruit Bunches (FFB) of palm oil has consistently increased, accompanied by a rise in land area and crude palm oil (CPO) production. The pivotal role of Indonesia as the world’s largest palm oil producer must be highlighted through sustainability studies, especially in environmental aspects. Life cycle assessment is a technique utilized to evaluate the environmental implications of products, processes, and services, spanning their complete life cycle from the extraction of raw materials to waste management. Life Cycle Assessment (LCA) encompasses various environmental impact categories, providing a comprehensive understanding of the ecological contribution of a product or service. This research assesses the environmental impact of oil palm plantation activities in Riau province, Indonesia. The research’s boundary is set to a cradle-to-gate analysis within the oil palm plantation subsystem. The Life Cycle Assessment was conducted utilizing the SimaPro 9.5.0.0 software employing the ReCiPe 2016 method. The total emissions generated during the production process of 5 tons of Fresh Fruit Bunches (FFB) amount to 1634.22 kg CO2 eq/5 tons of FFB. The major contributors to emissions are the production and use of inorganic fertilizers. Specifically, the types of fertilizers responsible for the high greenhouse gas emissions are KCl, followed by phosphorus and nitrogen fertilizers. Besides the potential for global warming, human carcinogenic toxicity is another potential impact, primarily from fertilization. The findings in this study can serve as scientific evidence in formulating solutions for sustainable oil palm plantations, particularly in reducing greenhouse gas emissions. An environmentally conscious approach to lowering emissions requires meticulous scrutiny and implementation of precision farming. It chiefly involves keeping a close watch on the quantity of fertilizer used in plantation settings and promoting using fertilizers with lower carbon footprints.

Analisis Pengaruh Peran Kelompok Tani Bangkit Merbabu terhadap Penerapan SOP Pertanian Sayur Organik di Besa Batur Kecamatan Getasan

The role of farmer groups as a learning class, a cooperation vehicle, and a production unit in the implementation of organic vegetable farming is important to produce quality and safe-to-consume products. This research aims to describe the role of the Bangkit Merbabu Farmer Group, describe the implementation of organic farming SOP by the Bangkit Merbabu Farmer Group, and analyze the influence of farmer group roles on the implementation of organic vegetable farming SOPs. The study was conducted from November 6 to December 28, 2023. The research location was the Bangkit Merbabu Farmer Group located in Kaliduren Hamlet, Batur Village, Getasan Sub-district, Semarang Regency, Central Java. The research method used was a census method with saturated sampling involving all 53 members of the Bangkit Merbabu Farmer Group. The analysis methods used were quantitative descriptive and multiple linear regression analysis. The research shows that the Bangkit Merbabu Farmer Group has characteristics such as: the average age of members is 19-59 years old, the majority have only completed elementary education, and farming is their primary occupation. The results of this research indicate that the role of farmer groups as a learning class, a cooperation vehicle, and a production unit falls into the good category with percentages of 58%, 53%, and 60% for the production unit falling into the rare category. The implementation of organic vegetable farming SOPs has a percentage of 49% and falls into the rare category. Based on the SPSS output results in multiple linear regression analysis, the learning class, cooperation vehicle, and production unit have simultaneous effects on the implementation of organic vegetable farming SOP. The factors from the independent variables contribute 39.6%, while the rest is influenced by other factors. Based on the t-test, there is a significant influence for the role of the learning class and cooperation vehicle, while there is no influence for the production unit.

ASSESS THE KNOWLEDGE LEVEL AND RELATIONSHIP BETWEEN PROFILE OF FARMER ABOUT POLYHOUSE VEGETABLE CULTIVATION PRACTICES

Polyhouse technology offers an excellent opportunity to grow high value crops during off-season with maximum input use efficiency. However, the successful implementation of polyhouse farming requires adequate knowledge about the specific cultivation practices involved. Therefore, the purpose of this study is to evaluate the farmer knowledge about polyhouse vegetable cultivation practices in Southern Rajasthan and also ascertain the relationship between knowledge of farmers with their personal characteristic. The study was carried out in two districts of Rajasthan namely Bhilwara and Chittorgarh. Data was collected through surveys and interviews conducted with farmers in the region. The analysis of the data was done with the help of different statistical tools like frequency distribution, percentage, mean, standard deviation, mean percent score and correlation coefficient. The study clearly shows that majority of respondents (63.00%) were having medium level of knowledge about polyhouse vegetable cultivation practices in study area. They had highest knowledge about the aspect of components of polyhouse and least about nematode infestation in polyhouse and its control methods. There was a significant correlation found between annual income, education level and land holding with knowledge of respondents about polyhouse vegetable cultivation practices.