Agricultural Information Research Articles

Factors Influencing Adoption of Faro 58 Rice Package (NERICA 7) by Small Holder Farmers of Katsina State, Nigeria

This study investigates the multifaceted factors that enhance the adoption of the FARO 58 rice package, specifically focusing on the NERICA 7 variety, among smallholder farmers in Katsina State, Nigeria. The FARO 58 rice package, known for its adaptability to diverse agro-ecological zones and improved yield potential, serves as a crucial element in enhancing food security and livelihoods within the region. Multi-stage sampling technique was used to arrive at a sample size of 220 respondents based on a sample frame of 2,630 farmers. Data obtained for the study were analyzed using descriptive and inferential statistics. The result of the study indicated that the average proportion of the respondents fall within the medium adoption category (0.34-0.66), 42.3% fall within the high adoption category (0.67-1.0), while only a small fraction of the respondents (6.4%) fall within the low adoption category. This could enable smallholder rice farmers to take advantage of access to agricultural information and technology adoption. Based on the findings of the study, it was concluded that farmers’ socio-economic factors had a significant influence on their adoption of the FARO 58 rice production package in the study area.

Comparative Study of Agricultural Extension Methods Used by the Public and Private Sectors Before and During COVID-19 Pandemic in Myanmar: A Case Study

Agricultural extension plays a crucial role in the development of the agricultural sector and the dissemination of agricultural information. There are three extension methods, namely individual, group, and mass methods, that facilitate communication between extension workers and farmers. The study was conducted to examine the agricultural extension methods used by the public and private sectors before and during COVID-19 pandemic, and to investigate farmers’ preference of agricultural extension methods used by the public and private sectors before and during COVID-19 pandemic in the Zeyarthiri township, Nay Pyi Taw Union Territory. A total of 60 respondents from three villages were interviewed using structured interview questionnaires for quantitative and qualitative data in July 2022. The demographic characteristics, agricultural extension methods received by farmers, and farmers’ preference of agricultural extension methods by the public and private sectors were all collected. The descriptive analysis and paired sample t-test were used to compare agricultural extension methods used by both sectors. The Chi-square Friedman test was also conducted to analyze farmers’ preference on extension methods with a 5-point Likert scale (1932) before and during the pandemic in SPSS. In terms of farmers’ preference, they mostly liked farm and home visits under the individual method used by both sectors among other extension methods in this study area. It indicates that individuals can speak with extension staff members face-to-face during farm and home visits about anything they want to know. During COVID-19 pandemic, the farmers mostly preferred “TV” under the mass method. It means that TV is the best way, not only for COVID-19 restrictions but also for quick access to agricultural information during COVID-19 pandemic.

Socio-Economic Factors Influencing the Use of Information and Communication Technology for Accessing Agricultural Information among Cowpea Farmers in Alkaleri Local Government Area of Bauchi State, Nigeria

Socio-Economic Factors Influencing the Use of Information and Communication Technology for Accessing Agricultural Information among Cowpea Farmers in Alkaleri Local Government Area of Bauchi State, Nigeria

Exploring the Socioeconomic Dynamics and Technological Adaptation among Farmers: Implications for Sustainable Agricultural Development and Rural Livelihoods in Jaipur, India

The research was conducted in Jaipur district of Rajasthan. There are 23 AAO departments under the jurisdiction of Deputy Commissioner of Agriculture, Jothwara (Jaipur). Among these, 4 AAO departments viz. Hingonia, Jobner, Boraj and Bichun were deliberately chosen for this study because the AAO circle is next to SKNAU, Jobner is within a radius of 20 km, researchers from the school respectively many people are making technological improvements in nearby villages and farmers are also active. A total of 120 participants were selected from these four AAO circles. Judging from the entire health history of farmers benefiting from Nongtang, the majority of farmers benefiting from Nongtang are middle-aged (35 to 51 years old) (58.33%). Primary school graduates (20.00%), farmers are union members (37.50%), their share of average annual income (77.50%) is Rs. 1,26,781 to Rs. 4,72,303 and farmers share small land. category (38.33%). Moreover, most of the beneficiary farmers (44.17%) have moderate farming experience ranging from 15 to 31 years, (23.19%) farmers use PM Kisan application, (70.00%) farmers use information technology, (68%) 34) consider agriculture as the main business. job. The relationship between income and technological change shows that there is a positive relationship between education level, social participation, annual income, insured land, agriculture, agricultural practice and knowledge. The beneficiary's social profile indicates education, community involvement, annual income, land ownership, farm practice use, and data-effective and relevant job creation and annual income. The correlation between the profile of the beneficiaries and their social variables shows a positive relationship between the level of education, social participation, and annual income. There is a significant relationship between the use of agricultural practices and the change in personal property and the education level of family members. Agricultural knowledge and information are important and positively related to changes in household members' education levels and ownership of agricultural equipment.

Enhancing agriculture production through smart assessment of soil nutrients

ABSTRACT The growth of the world population is leading to an increased demand for food production. Consequently, there is a need to update agricultural processes to enhance production. Smart farming has evolved as a farm management concept that leverages real-time, dependable, and site-specific agricultural information to ensure consistent and sustainable yields. This study focuses on soil nutrient analysis, specifically nitrogen (N), phosphorus (P), and potassium (K) for enhancing crop production. Maintaining an appropriate balance of NPK is crucial for the well-rounded nutrition of crops. Various environmental factors such as temperature, rainfall, humidity, and soil pH affect the NPK composition of agricultural land. The optimal usage of NPK levels can help to improve plant growth, increase crop yields, and enhance overall farm productivity. Hence, we have proposed a stack regressor learning algorithm comprising of two layers for accurate, reliable, and context-sensitive predictions of NPK levels. The proposed approach considers the combined impact of these environmental factors and predicts the optimal NPK requirements tailored to specific crops and agricultural land. The analysis of graphs demonstrates that the predictive accuracy of the proposed stacked regressor model far surpasses that of preexisting built-in machine learning models. This study helps farmers make informed decisions, leading to productivity and sustainability.

Behaviour recognition of housed sheep based on spatio-temporal information

ABSTRACT Livestock behavior is related to the healthy breeding and welfare level. Therefore, monitoring the behavior of sheep is helpful to predict the health status of sheep and thus safeguard the production performance of sheep. Taking semi-housed sheep as the research object, a behavior identification method for housed sheep based on spatio-temporal information is proposed. Firstly, video acquisition of housed sheep is carried out, and sheep detection and tracking is implemented based on the YOLOv5 coupled with a Deep-SORT algorithm, which detects sheep from the flock and labels their identity information; then, sheep posture estimation is done based on the Alphapose algorithm, which estimates the keypoints in the skeleton; finally, the detected keypoints are inputted into the trained spatio-temporal graph convolutional network model, and the spatio-temporal graph constructed from the keypoints and edge information is used for sheep behavior recognition. In the study, two keypoints selection proposals were made to implement sheep behavior recognition for non-contacted detection of ruminating, lying down and other behaviors. The results show the feasibility of sheep behavior recognition based on spatio-temporal information in semi-housed farming. The method provides a new solution idea for intelligent monitoring of sheep behavior and health assessment.

Effects of agricultural informatization on agricultural carbon emissions: a quasi natural experiment study in China

ABSTRACT Agricultural informatization is regarded as a useful instrument for reducing carbon emissions, but few studies are devoted to illustrating the real effects and mechanisms of it in detail. In this paper, agricultural informatization policy (AIP) is regarded as an exogenous shock, TVDID (time-varying Difference-in-difference) method and county-level panel data from 2000 to 2018 in China are used to investigate the effects of agricultural informatization on agricultural carbon emissions. It shows that AIP reduces agricultural carbon emissions by 1.4% significantly. Technologies adoption and farmland enlarging are potential mechanisms for these effects. Education level and broadband accession can improve the effects of carbon reduction. The effects of AIP on carbon reduction are more salient for the eastern and main-grain-producing areas. This paper implies that agricultural informatization could be essential for local agricultural carbon reduction.

Kurdistan Rural Information System Platform, as a New Rural Innovation Paradigm: Local Decision-Makers Perspective

Background: This study aimed to achieve objectives through SWOT analysis and focus group discussion, identifying internal and external factors through the local decision-makers in Kurdistan Region, to explore the way to describe and analyze Kurdistan Rural information System Platform (KRISP). Problems with information in rural areas still exist in the Kurdistan region administration. The aim of this study is an attempt to develop a digital platform that will help rural communities realize their full potential and contribute to a resilient and successful digital future. The primary objectives of this project are how to design and implement an agricultural information system to collect rural data from various areas by various farmers and make it available online so that future users may eventually search for and obtain the essential data. The first category is concerned with knowledge sharing, information exchange, self-improvement, and self-improvement for grassroots extension practitioners. The study made use of qualitative data, with fixed questions. for the analysis. The achievement of primary data was also collected using a FGD’s implemented in Sulaimani governorates. The period of data collection from different study areas starting from June 2023 to September 2023 and were used in this study to collect qualitative data from a variety of government sectors (decision-makers) from various organizations were included in group discussions and gatherings to address the issues highlighted in this study.

Perception and Adoption of Government Agricultural Technologies among Smallholder Farmers in Western Uganda

Agriculture production and productivity remain key to feeding the growing population with agriculture extension being at the centre of the performance of the agricultural sector in Uganda. Research shows that improved technologies promoted through extension service provision could have an even greater impact on food production and on farmers’ livelihoods in developing countries like Uganda. This study was conducted to investigate the perception and adoption of improved agriculture technologies under the government extension system among smallholder farmers in Kagadi District, mid-western Uganda. Data was collected using a questionnaire from 149 randomly selected households in three sub-counties. Results generated using Excel and SPSS revealed a high positive perception index of +0.63 for government extension services. The level of adoption of improved technology based on generalised partial adoption was 54.3% with farm size and training attendance being the significant factors affecting adoption of improved agricultural technologies in the study area. It is clear from the results that notable differences exist in terms of the perceptions of government extension services and the adoption of improved agricultural technologies. The general observation of farmers’ perception is that government extension service is helpful to farmers and is the major source of agricultural information in the area. Efforts should be made to support access to arable land and intensification of agricultural training sessions coupled with appropriate mobilisation of farmers to attend such training. Further studies should be done to understand these aspects on a wider scope in the country since this study was only conducted in one district. There is also needed to study the factors individually as well as the relationships with other factors to determine the adoption processes of technological advancement

Peculiarities of investment and innovation potential in the assessment of the development of agribusiness enterprises

Three main criteria of investment-innovation potential of agricultural sector enterprises are identified: investment-innovation potential is a set of resources necessary for investment-innovation activities; investment and innovation potential is primarily related to the possibility and conditions (both internal and external) of using resources; investment and innovation potential should be aimed at the optimal use of investment and innovation resources to ensure the effective operation of this development subject. This allows for the identification of resource, organizational, economic and performance components that are key components of investment and innovation opportunities. A step-by-subject characterization of the investment-innovation potential of agro-industrial complex enterprises and a methodology for assessing the investment-innovation potential have been developed, which allows to qualitatively assess the investment-innovation potential of agricultural and processing enterprises (including special groups of indicators that take into account the specifics of their activities) and evaluate and compare them among themselves. It is proved that the inactivity of agricultural commodity producers in mastering the achievements of science and technology is due to the lack of a developed intermediate connection between science and production, which provides the most complete information about the modern achievements of science and technology to producers of raw materials. According to the results of the conducted research, it was established that at the current stage of development in domestic agriculture, the main subjects of innovative infrastructure can become agricultural technology parks and information and consulting centers, which are part of a single information and consulting service. Considering the peculiarities of the domestic agro-industrial complex, it is considered most expedient to create an agro-technological park in the form of a non-commercial partnership, which will contribute to the integration of multifaceted resources. organizations, mainly highly efficient agricultural commodity producers and educational establishments of higher education institutions, capable of carrying out innovative activities to achieve a common goal - innovative development of the agrarian sector of the economy. Agrotechnoparks should be created based on the product base, that is, their activities should be aimed at innovative development of agricultural production and the development of certain types of products. Agrotechnopark can be considered as a set of administrative, production, educational, research and marketing divisions.

Agricultural Information Needs and Resources of Smallholder Sugarcane Farmers in Swaziland

Abstract The sugar industry is the dominant agricultural sector in Swaziland’s economy, contributing significantly to the gross domestic product. Provision of relevant and timely information to smallholder sugarcane farmers is crucial for them to have a competitive footing with large-scale counterparts and reduce poverty. However, there is limited literature on the information needs and the kind of information communication resources that could make the dissemination of information to farmers efficient and effective. This study thus aims to investigate the information needs and resources of smallholder sugarcane farmers in Swaziland to inform the provision of information services in the sugar industry. It was underpinned by a positivist paradigm and used the survey research method complemented by methodological triangulation to collect quantitative and qualitative data. Data was collected using survey questionnaires and face-to-face interviews, with 168 responses and six interviews conducted. The findings revealed that 71 % of information needs of farmers were primarily in legislative compliance, sugarcane crop husbandry, markets and transport, and financial advice information, however, there were no statistically significant differences between the three mill groups in information needs. The smallholder sugarcane farmers also mostly obtained agricultural information through extension officers, farmer groups, and mobile phones, indicating that required information was mainly accessed through face-to-face interactions. The empirical findings of the study have implications for practice, policy, and theory with respect to guiding the implementation of agricultural information services by information providers in the context of rural farmers in developing countries.

Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images

Abstract With the modernization of agricultural production and the acceleration of urbanization, agricultural landscape planning and ecological balance control have become important issues in promoting sustainable development. Traditional agricultural production methods have problems such as resource waste, environmental pollution, and ecological damage. This article aimed to achieve scientific planning and management of agricultural landscapes, and promote the efficiency of agricultural production, rational utilization of resources, and protection of the ecological environment, thereby promoting sustainable agricultural development. This study first focused on denoising and feature extraction of agricultural remote sensing data images, using remote sensing technology to obtain agricultural landscape information. After that, artificial intelligence was adopted to achieve intelligent agricultural landscape planning, with the goal of maintaining ecological balance and promoting efficient, eco-friendly, and sustainable agricultural production. This study took the landscape of a certain city as an example to test the processing effect of remote sensing images, and it was proved that the effect was good. We tested the performance of an intelligent agricultural landscape planning and ecological balance control system based on remote sensing images. According to the experimental results, it can be concluded that the resource utilization efficiency of farmland A monitored by the intelligent agricultural landscape planning system using remote sensing image technology was 82%, while the traditional one was only 60%. This indicated that the collection effect of remote sensing image technology was much better than that of traditional technology. This article comprehensively and timely monitored and evaluated farmland through remote sensing image technology, including crop growth status, soil moisture, nutritional status, etc. The system can provide precise planting and management suggestions for farmers based on this information, and help them optimize farmland layout, crop selection, and irrigation management, thereby improving the production efficiency of farmland and crop yield.

Factors Influencing Participation of Rural Women Farmers in Agricultural Activities in Ranau, Sabah, Malaysia: An Exploratory Factor Analysis

Globally, rural women farmers benefited from only 5% of agricultural extension information, and also only 10% of the agricultural extension facilities, this affects their engagement in agricultural development resulting in an increased rate of poverty and lack of the necessary knowledge of agricultural practice. This study aimed to determine the internal and external factors influencing rural women farmers’ participation in agricultural activities in rural areas of Malaysia. The study was conducted in Ranau, Sabah, Malaysia. A sample size of 248 rural women farmers was selected using simple random sampling. A five-point Likert scale questionnaire was used for data collection. Collected data were subjected to descriptive and factor analysis using Statistical Packages for Social Science (SPSS) version 26. The findings indicated that the factors affecting rural women’s participation in agricultural activities in Ranau, Sabah, encompassed access to financial and agricultural inputs, social culture, land rights, access to land, technology adoption, participation in farm management decisions, limited scope of agricultural policy and access to resource and support for women in agriculture. The present study has provided insights into the factors contributing to women’s participation in agriculture activities. The study suggests that a theoretical model should be proposed to test the relationship between these factors and women’s participation in agriculture, along with research to identify solutions for reducing identified barriers.

Information and communication technology in smart agriculture: A scientometric review

SummaryAgriculture has been affected by several global trends raising the concern for food security. Agri‐food demands are amplifying due to the ever‐escalating population numbers. Thus, the notion of extending the use of smart innovative technology in managing agricultural practices has emerged rapidly over the last decade. Technological innovations have contributed significantly to shape modern agriculture as smart agriculture. Smart agriculture unfolds various benefits such as increased production, real time data and production insights and remote monitoring. The rising advancements in Information and Communication Technologies (ICT) have paved the way for researchers to use these technologies in managing agricultural practices, leading to greater benefits for farmers and society. These innovations are the key to establishing agriculture as a research discipline. The purpose of this article is to conduct a scientometric analysis to study the structure and evolution of research activities in the field of smart agriculture. The scientometric analysis aims to empirically map the scientific knowledge and identify any possible challenges in the field. This study performs elementary analysis to study publication growth over the years, impact analysis to assess the leading journals, authors, and countries, and articles analysis for findings patterns among the citations over the years and among the keyword‐based clusters. There has been a considerable increase of more than 200% in the number of publications from 2011 to 2022. However, around 60% of authors have contributed with a single publication. The findings of the study reveal the research trends and hot topics for future research fronts. Deep learning, digital agriculture, object detection, blockchain, and semantic segmentation have been identified as trending topics in smart agriculture. Comprehensively, an intellectual view of the agriculture domain is presented as a scientific field in this article.

283 Identification of new or existing risk factors associated with the development of sow pelvic organ prolapse

Abstract A survey was conducted between March and December of 2022 to examine the variation between farms that had high and low pelvic organ prolapse (POP) rate. The objective was to identify new or existing risk factors associated with the development of POP, which could open new avenues for further investigation. Sow farms (n = 53) across 26 production systems located in the US, Canada, and Mexico were used. Sampling of farms was not random. High and low POP systems were selected within each region as well as high and low POP farms within each system. Over 800 variables related to general farm information and management, performance traits, reproductive management, replacement gilt management, gestation and farrowing practices, labor and health management, and nutrition were collected during farm visits. To be included in the analysis, at least 70% of observations were needed for continuous variables with at least 10% of observation for each category for categorical variables. Univariable models were fitted to identify variables associated with annualized POP rate for 2021. Variables with P ≤ 0.10 were selected for further analysis, with 94 predictor variables selected for principal components analysis (PCA). A factor analysis of mixed data was conducted, and results were then fitted into a hierarchical clustering on PCA, which segregated the data into three clusters: 2 with low POP (2.5%) and 1 with high POP (6.1%) prevalence (low vs high P < 0.05). The resulting clusters explained 33.7% of the variability in annualized 2021 POP rate. Differences between clusters were evaluated by Kruskall-Wallis test for numerical variables and chi-square test for categorical variables. High POP cluster farms had greater total piglets born over the years, greater number of sows per worker, greater annual gestation feed usage, and a lower mean body condition score at 16 wk of gestation compared with low POP cluster farms. High POP cluster farms had a decreased proportion of farms using conventional artificial insemination, a greater proportion of farms utilizing cup waterers in gestation for sows in group housing and in farrowing, and greater proportion of farms with a routine sleeving practice. High POP cluster farms compared with low POP cluster farms had greater gestation distillers dried grains with solubles (DDGS) inclusion level (14.6% vs 4.0%, SE 3.02), greater levels of standardized total tract digestibility (STTD) P% (0.49% vs 0.39%, SE 0.014), narrower analyzed Ca to STTD P ratio (1.7 vs 2.2, SE 0.06), and lower phytase inclusion and release (0.16% vs 0.09%, SE 0.014). These variables were also the predictors with the greatest R2 values in the univariable models. These observations suggest further research is needed to evaluate the connection between dietary Ca and P and pelvic organ prolapse.

An intelligent decision support system for agriculture economy based on fuzzy c-means

Abstract Agricultural informatization construction has developed rapidly in recent years, but its data has not been well utilized to support decision-making. Cluster analysis is an important branch of data mining, which is applied to the agricultural industry and enhances the competitiveness of the industry. In response to the problem of insufficient information space services for rural agricultural economy, the application of clustering analysis algorithm in the field of agricultural feed industry was studied. Based on fuzzy C-means technology, clustering analysis was conducted, aiming to provide a universal decision support platform for agricultural production management departments and achieve value co-creation among farmers, enterprises, and investors. In this paper, a method based on Xie-Ben validity is adopted, and the method is modified. In addition, the steps of removing empty clusters are added after the cycle of FCM algorithm to improve the efficiency of the algorithm. In the experimental stage, different subdivision results are obtained by selecting different parameters, and the results are analyzed to verify the effectiveness of the FCM algorithm. Finally, the improved FCM algorithm is applied to the agricultural marketing decision support system to provide important decision-making for domestic and foreign feed raw material producers and traders, animal husbandry feed production enterprises, agricultural investment institutions and so on.

Rancang Bangun Sistem Informasi Penyewaan dan Rekomendasi Lahan Pertanian Menggunakan Metode KNN

Agriculture plays a crucial role in the economy of Indonesia, particularly in Kampar Regency, Riau Province. The agricultural, forestry, and fisheries sectors serve as the backbone in forming the Gross Regional Domestic Product (GRDP), making a significant contribution to the national economy. However, farmers in Karya Indah Village face challenges in finding and renting agricultural land that meets their needs. To address this challenge, the development of a web-based agricultural land rental information system is essential. This research aims to design a web-based information system using the K-Nearest Neighbor (KNN) algorithm to provide recommendations for agricultural land suitable for farmers' needs. This system facilitates farmers in finding and renting suitable agricultural land, while landowners can efficiently offer their land for rent. The research not only aims to improve efficiency in the process of renting agricultural land but also to enhance agricultural productivity and farmers' income. The research findings indicate that the KNN method can provide accurate recommendations for agricultural land, thus helping to improve farmers' welfare and the overall sustainability of the agricultural sector. The research findings show that the KNN method can recommend agricultural land with an accuracy rate of 80%.

An iterative and subsequent proximation method to map historical crop information with satellite images

Mapping agricultural information such as cropping area and type is of great significance for land use and food security and a common method to retrieve such information is satellite imagery classification. The current image classification techniques require a statistically large number of training samples to obtain representative spectral signatures, ideally collected during the satellite overpass time/date. Although this prerequisite sounds simple and easy in principle, it is extremely challenging and sometimes impossible when classifying historical satellite images, as one simply cannot go back in time to collect training datasets or ground truthing. In this paper, we introduce an iterative and subsequent proximation (ISP) method to circumvent this problem for historical image classifications for historical crop mapping. This method assumes that the same crops grown two years apart have similar spectral properties within the same growing season, with limited variation. This allows the use of the crop information classified in any given year (n) to be used as training samples for the next year (n + 1) or the previous year (n-1). Iteratively repeating n-1, n-2… process leads to the mapping of historical cropping information without a priori ground truthing data. To demonstrate the ISP feasibility, we first used the historical Landsat time-series data to map four major stable crops (rice, maize, soybean, and wheat) in Hailun County, Heilongjiang Province, China, and then further expanded the ISP application to the entire Heilongjiang Province to map cropping areas from 1982 to 2020, using the classification and regression trees (CART) algorithm. The results were validated for those years when actual cropping measurement data were available and further verified with statistical data for other years. The results indicated that the proposed ISP method was appropriate for the historical mapping of four major crops, with a mapping accuracy of approximately 80 % when validated with field data, and correlation coefficients of 0.86, 0.85, 0.91, and 0.94, respectively when compared with historical statistical cropping data. The crop mapping results showed distinct trends of northward expansion in each of the four crops in Heilongjiang Province, which agreed well with previous studies. In conclusion, the ISP method is quick, easy, and convenient for historical crop mapping, which is important in understanding the agricultural production history.

Gender Perspectives in Agriculture and Livestock Production: Insights from Garo Tribal Farm Households in West Garo Hills: Meghalaya

This study was conducted in two villages situated in the West Garo Hills district of Meghalaya in 2023, focusing on a sample of 60 tribal farm families. Respondents were randomly selected from the selected villages. Statistical analyses were performed using frequencies and percentage. The findings revealed that 80.0% of households had a nuclear family structure, with 61.67% being led by males. Agriculture was the primary occupation of 51.67% of households, and 33.33% reported an annual household income ranging from Rs. 85,001 to Rs. 150,000. Additionally, 78.33% of households possessed areca nut orchards and 60.0% utilized mobile phones for communication. Credit facilities were available to 31.67% of respondents. Regarding information sources, 98.33% of males and 96.67% of females relied on friends and neighbours for agricultural information. Decision-making was reported to be joint in 65.0% of households. Crop harvesting, which was primarily performed by females (55.0%), and the selling of harvests during financial needs, which were handled by males (35.0%) and females (38.33%), were identified as patterns. Revenue management from sales was undertaken by males (36.67%) and jointly (33.33%). In livestock-related decisions, 63.0% reported joint decision-making, and the grazing of animals was managed by children within households (68.33%). For healthcare, 63.33% of independent males consulted the veterinary department during instances of animal disease. Joint decisions were made for the purchase and sale of animals (81.76%). The present findings contribute valuable insights into gender in agricultural discourse, guiding informed and inclusive development in the North East Region. Practitioner Summary: The study was on 60 small Garo tribal farm families actively engaged in both agricultural and livestock activities. Study revealed that women has integral role in agriculture and livestocks then men. Joint decision making in agriculture collaborative farm management, males often takes lead in financial management and certain post-harvest processes.

The Benefits of Social Media Platforms Used in Agriculture for Information Dissemination

Traditionally, agricultural information is disseminated through industrial media such as newspapers, television, and radio. People, including farmers, are using social media platforms like Facebook, Twitter, YouTube, and blogs to spread personal or agricultural information. This paper highlights the benefits of social media to farmers as follows: coverage of large geographical boundaries in a short time, reducing farmers’ social isolation, increasing networking platforms, mobilising farmers, keeping farmers updated and marketing agricultural goods with ease. Literature acquired from Google Scholar, Scopus, Science Direct and the University of Limpopo e-library search engines provided sources of information for the paper. This paper discusses the benefits of social media, defines the concept of social media, and lists different social media platforms available to farmers. It concludes that social media can enhance farmers’ capabilities and interaction with extension officers. The paper recommends that agricultural news and communication be spread using social media platforms popular in the farming communities, that there be development of information centres where farmers can access social media and get assistance while accessing such information and that they receive proper training on the use of social media platforms. Extension officers must be equipped with skills to package relevant information to disseminate to the farmers.