Tool For Farmers Research Articles

Особенности оценки углеродного следа в сельском хозяйстве: сравнительный анализ методических подходов

The study of the components of the carbon balance and the possibilities of its regulation for different types of land use is an urgent scientific task within the framework of the global problem of increasing concentrations of greenhouse gases in the atmosphere and the development of the concept of carbon neutrality. In this article, an assessment of the carbon footprint of the farm was carried out based on an analysis of the capabilities of carbon calculators Cool Farm Tool, AgRe-Calc, Farm Carbon and Ex-Act V9.4, as well as the Methodology for quantitative determination of greenhouse gas absorption volumes, approved by Order of the Ministry of Natural Resources of the Russian Federation No. 371 dated 05/27/2022. Calculations were carried out using the example of the farm located in the Burlinsky region of the Altai region. The results of the study showed that the largest carbon footprint of the considered farm is formed by the cultivation of flax, somewhat smaller by sun-flower and wheat crops, and the lowest by fodder crops. Differences in estimates based on different methods are recorded not only in the resulting total carbon footprints, but also in the structure of the carbon footprint for each crop. In general, in Russia and abroad there are different approaches to determining the carbon footprint. The approach used in carbon calculators assumes that all carbon generated in one way or another during economic activity forms a carbon footprint, while the 2022 methodology of the Ministry of Natural Resources also takes agriculture into account as an important sink and carbon reservoir.

Lactic Acid Bacteria of Marine Origin as a Tool for Successful Shellfish Farming and Adaptation to Climate Change Conditions.

Climate change, especially in the form of temperature increase and sea acidification, poses a serious challenge to the sustainability of aquaculture and shellfish farming. In this context, lactic acid bacteria (LAB) of marine origin have attracted attention due to their ability to improve water quality, stimulate the growth and immunity of organisms, and reduce the impact of stress caused by environmental changes. Through a review of relevant research, this paper summarizes previous knowledge on this group of bacteria, their application as protective probiotic cultures in mollusks, and also highlights their potential in reducing the negative impacts of climate change during shellfish farming. Furthermore, opportunities for further research and implementation of LAB as a sustainable and effective solution for adapting mariculture to changing climate conditions were identified.

Explore the Functional Beauty of Chinese Traditional Farm Tools

As a traditional agricultural society in ancient China, farm tools and instruments have been an indispensable part of China's agricultural production since ancient times, and their production development is an important symbol of the development of social productive forces. Chinese traditional farm tools have typical characteristics of The Times and regional characteristics. Excavating and sorting out these historical elements and cultural characteristics and integrating them into modern industrial design can not only promote traditional culture, but also make these traditional elements relate to modern life and reflect The Times value of traditional culture. The simple functional aesthetics embodied in traditional farm tools is the technology and experience accumulated by working people in long-term production practice, and has the characteristics of "practical, simple, flexible and environmental protection". Starting from the development history of farm tools, this paper combs the significance of pragmatism in traditional farm tools, explores the functional beauty of Chinese traditional farm tools and the theoretical and practical value of functional beauty in traditional farm tools. Hope to provide some references for the protection and inheritance of Chinese traditional farm tools.

Precision Aquaculture: A Way Forward for Sustainable Agriculture

The escalating demands for food, fiber, energy, and water due to swift population growth have underscored the necessity for the sustainable utilization of natural resources. The advent of precision farming tools and machinery since the 1990s has markedly enhanced productivity and optimized the employment of inputs in aquaculture. The burgeoning connectivity in rural regions and its improved integration with data from sensor systems, remote sensors, equipment, and smartphones have paved the way for innovative concepts in Digital Aquaculture. Automation is the most effective strategy to manage situations, augment productivity, and reduce manufacturing costs. Biosensors are deployed to control unidentified sensor-based remotely and guided aerial vehicles to apply chemicals or fertilizers while monitoring water quality. A sophisticated aeration system manages the concentration of dissolved oxygen. Another critical aspect is the administration of feeding and automatic biomass estimation. Robotics and automatic feeders are employed in ponds and cages to minimize feed wastage and the Feed Conversion Ratio (FCR), with these tools being dependent on the behaviour of the organisms and the water condition. Post-harvest, farmers acquire information on biomass estimation to attain optimal yield. The most vital element is the automatic monitoring of the health and welfare management of the organism to detect any challenging situations or early signs of anomalies. An underwater surveillance system, a camera-based visual system, collects data on water quality, organism activity, feeding, cage biofouling, and net cleaning. Automation is poised to shape the future of the aquaculture industry to make the nations agriculture sustainable.

Adoption of Indigenous Language (Igbo) In Teaching of Agricultural Science at the Primary School: A Panacea for Food Insecurity

This Study was carried out with the aim of ascertaining whether the adoption of indigenous language (Igbo) in teaching of Agricultural science at the primary school could help in solving food insecurity. The study adopted the descriptive survey research design. Three research questions guided the study. The population of the study comprised 350 agricultural science teachers. The sample for the study was 210, comprised 52 teachers and 158 pupils in the public primary schools in Abakaliki Education Zone of Ebonyi State. The research instrument used for the data collection was questionnaire developed by the researchers and validated by three experts. The reliability of the instrument was established using Pearson product moment correlation. The reliability coefficient of the instrument was found to be 0.79 which was considered highly reliable. The data analysis was done using mean (x̄) and standard deviation. The results of the study showed that adoption of indigenous language (Igbo) in teaching of food crop production, farm animal production and maintenance of farm tools and equipment will help in solving food insecurity in the state. Based on these findings relevant recommendations and suggestions were made.

금강유역권 축소모형농공구의 형태와 특징

These days, relics that used to have regional specificity tend to deviate from their specificity due to the active cultural property excavation research. It is necessary to recognize the newly identified area. Therefore, among the archaeological materials that strongly reflect regional specificity, we paid attention to the Miniature farming tools accumulated around the Geum River basin. The Miniature farming tools can be divided into ttabi type, cheolseo type, iron axe type, and sickle type. Data from the Geum River basin also show high excavation rates for Iron Axe type and sickle type, although the warm and cheolseo type are also identified. Cheoljun is one of the characteristic iron artifacts excavated from the Geum River basin. Compared to the Daegaya sphere, this was identified as a ttabi-type Miniature farming tool, and the plane shape and cross-sectional shape were considered to be more likely to have been produced under the influence of the Daegaya sphere rather than generated and produced within the Geum River basin. Iron axe-type Miniature farming tools are again divided into I-shaped and V-shaped in crosssectional form, and the I-shaped is the same as or similar to those confirmed in the Daegaya sphere, so it is thought to be highly relevant. On the other hand, the V-shaped is also excavated from the remains of the Proto-Three Kingdoms Period, which is confirmed around the Geum River basin, and is similar to the form of Iron axe, which has been produced and used for a long time, so it is thought that the traditional method was inherited. Although there is a limit to linking data excavated from the Geum River basin with Miniature farming tools excavated from the Daegaya sphere, data that are likely to have been produced in a manner similar to that of the Daegaya sphere in both plane and cross-sectional shapes were identified. From these data, it can be seen that there are also data that are more likely to have flowed into Baekje sphere from Daegaya sphere than from Baekje sphere.

Innovative use of sensor technology to study grazing behaviour and its associations with parasitic resistance in sheep

Gastrointestinal nematodes (GINs) are a concern for sheep production and are associated with significant economic losses globally, driving the need for effective management strategies. The aims of this research were first to determine the influence of GIN infections on sheep grazing behaviours, specifically grazing time (GT) and grazing event length (GL), and then to estimate the genetic and phenotypic correlation between faecal egg counts (FEC) and salivary specific IgA activity vs GT and GL. Data were collected from 146 Merino sheep on a commercial farm in Victoria, Australia. Faecal, saliva and body weight (BW) were collected at four time points (A: Oct 2019, B: early May 2020, C: late May 2020, and D: Jul 2020), while tri-axial accelerometer sensors recorded GT and GL for the length of 26 days between B and C. Univariate linear regression and Bayesian Generalised Linear Mixed Model, estimated using Markov Chain Monte Carlo, were used to assess the relationships between the behaviours and infection indicators. We found an increase in the logarithm of FEC was associated with a significant rise in grazing time (p < 0.05), suggesting compensatory behaviour in infected sheep. GT also accounted for 6% of the FEC variation. In contrast, the effect of IgA on GT was not significant (p > 0.05). There was a positive genetic and phenotypic correlation estimated between GT and FEC, however, the High Posterior Density interval for the genetic and phenotypic correlations between GT and FEC indicates some uncertainty in these estimates. These results imply that sheep may modify their grazing strategies as an adaptive response to parasitic infections to ease the impact on their nutritional intake. This study improves our understanding of how natural GIN infections affect sheep behaviour and highlights the potential to use animal behaviours as a precision livestock farming tool and in breeding for resilience against parasites.

BovineTalk: machine learning for vocalization analysis of dairy cattle under the negative affective state of isolation.

There is a critical need to develop and validate non-invasive animal-based indicators of affective states in livestock species, in order to integrate them into on-farm assessment protocols, potentially via the use of precision livestock farming (PLF) tools. One such promising approach is the use of vocal indicators. The acoustic structure of vocalizations and their functions were extensively studied in important livestock species, such as pigs, horses, poultry, and goats, yet cattle remain understudied in this context to date. Cows were shown to produce two types of vocalizations: low-frequency calls (LF), produced with the mouth closed, or partially closed, for close distance contacts, and open mouth emitted high-frequency calls (HF), produced for long-distance communication, with the latter considered to be largely associated with negative affective states. Moreover, cattle vocalizations were shown to contain information on individuality across a wide range of contexts, both negative and positive. Nowadays, dairy cows are facing a series of negative challenges and stressors in a typical production cycle, making vocalizations during negative affective states of special interest for research. One contribution of this study is providing the largest to date pre-processed (clean from noises) dataset of lactating adult multiparous dairy cows during negative affective states induced by visual isolation challenges. Here, we present two computational frameworks-deep learning based and explainable machine learning based, to classify high and low-frequency cattle calls and individual cow voice recognition. Our models in these two frameworks reached 87.2 and 89.4% accuracy for LF and HF classification, with 68.9 and 72.5% accuracy rates for the cow individual identification, respectively.

한국 전통 농기구 호미를 활용한 지역 콘텐츠 개발 가능성

This study examines the global attention on the 'Yeongju Daejanggan Homi' from Amazon, exploring content development in Yeongju, Gyeongbuk, with the traditional Korean farming tool, the hoe. Analyzing homi popularity, ‘Homis in BTS rap lyrics, the first lady's hoe diplomacy, and collaborations with Petite Hoe, the study assesses Yeongju's content potential. It designs a gardening festival and explores creating a gardening hoe set. Renowned as the birthplace of “Putgut” or hoe washing, Yeongju's cultural significance is reinterpreted, designed a global trends-aligned gardening festival. The study aims to enhance the 'Yeongju Daejanggan Homi' set and create a home gardening hoe set combining excellence, functionality, and aesthetics, contributing to regional development. This exploratory study is significant in that it reevaluates the value of traditional Korean farming tools and seeks ways to contribute to regional development in a modern context.

Building Trust in AI Farming Tools

AbstractPrecision agriculture tools like decision support systems increasingly use machine‐learning algorithms and other types of artificial intelligence (AI) to analyze large quantities of agricultural data and provide recommendations to producers and crop advisers. However, several barriers threaten adoption of these tools. Three papers in the recent Agronomy Journal special section, “Machine Learning in Agriculture,” explore this phenomenon and offer solutions and opportunities for building trust in these technologies.

Determinants of Profitability Among Agricultural Equipment Fabricators in Oyo State, Nigeria

The study examined enterprise profitability among agricultural equipment fabricators. It was conducted in Oyo State, Nigeria using a multistage sampling procedure to select the 48 respondents from whom data were collected using a structured questionnaire. Percentage was used to analyse the socioeconomic and enterprise characteristics of the respondents, while gross margin analysis was used to determine the profitability of the enterprise. A linear regression model was used to ascertain the drivers of enterprise profitability among respondents. Findings revealed that over half (54.4%) of the fabricators produced processing equipment, while fewer (28.2%) produced farm tools. Most of the fabricators operated with a mean workshop space of 1.3 m2. The gross margin analysis showed a total revenue of N95,302,900 exceeding the total cost of production (N20,374,205), indicating (N74,928,695) profitability of their enterprise with an N3.68 return on investment per Naira. Fabrication being a secondary occupation (β=0.340), and business registration with the Corporate Affairs Commission (β=0.473) significantly influenced profitability among the respondents. This study recommends regulating the fabrication sector through policies, ensuring that fabricators register their outfits with designated statutory bodies to significantly enhance the standardization of outputs and increase the units of production, hence, improving the profitability of the enterprise.

Challenges of Small-Scale Agriculture: Evidence from Depressed Communities in Fundong Sub-Division Northwest Region, Cameroon.

Small-scale agriculture has become the backbone of most developing countries in the world especially Cameroon in general and Fundong Sub-Division in particular. Following the economic crisis of the early 1990s that hit Cameroon economy, there has been a steady increase in the rate of unemployment, which has paved the way for agriculture to be the leading economic activity. This investigated the challenges faced by small-scale farmers in Fundong Sub-division. The data used in this study were obtained from the survey questionnaire and interview administered on the sample of 104 households. Using cluster-sampling approach, proximity villages were grouped into four clusters villages and Purposive sampling was then used to select households to participate in the study. Descriptive statistics were used to analyse the challenges of small-scale farmers. Results obtained revealed that low agricultural production was as a results of these challenges (Poor farm to market roads, Limited access to modern farming tools, Insecurity at the suburbs, Lack of improved and resistant seed varieties etc) faced by these small scale farmers. Based on the finding this study recommends that the government should subsidize the agricultural sector and addressed the issue of farm to market road.

A Platform for GHG Emissions Management in Mixed Farms

This research introduces an innovative platform designed to manage greenhouse gas (GHG) emissions in mixed farms. Emphasizing the urgent need to address GHG emissions, particularly methane (CH4) and nitrous oxide (N2O), the platform targets mixed farming systems where the interplay of livestock and crop production significantly contributes to environmental impacts. Our methodology is grounded in comprehensive data collection, encompassing soil data, energy consumption, and detailed livestock information. Utilizing the Agricultural Internet of Things (AIoT), it facilitates real-time data acquisition and analysis, providing insights into various farm activities’ GHG emissions. This approach allows for precise monitoring and management of emissions from different sources, including enteric fermentation in livestock and fertilizer use in crop production. Results from the application show its effectiveness in offering a clear and interactive visualization of GHG emissions, aiding farmers in making informed decisions for sustainable farm management. The platform’s user management system, coupled with advanced data processing and visualization capabilities, underscores its potential as a vital tool for sustainable farming. Conclusively, Solution4Farming represents a significant advancement in digital agriculture, combining IoT technology with sustainable practices. Though initially designed for Romanian cattle farming, Solution4Farming’s anticipated expansion to various farming environments suggests a broader impact and relevance in sustainable agriculture.

Assessment of Use Values and Propagation Methods of Native Fodder and Fruit Species in Merhabete District, Ethiopia

Native fodder and fruit species provide various products and services to local communities besides their fruit (food) and fodder supply in our country including in the study area. Although, there is rich traditional knowledge on propagation methods of native fodder and fruit species and their local use, but little recognition has been given by forestry research and extension efforts to enhance them. The general objective of the study was to investigate the use value and propagation methods of native fodder and fruit species in the Merhabete district, Ethiopia. A total of 127 households were randomly selected and interviewed about local use and propagation methods of native fodder and fruit species. The study indicated that the majority of native fodder and fruit species were used for firewood (23.9%) followed by charcoal (10.9%), timber, and construction wood (10.6%), fencing (9.3%), soil fertility improvement (9.1%), farm tool (7.1%), and medicine (3.3%). Native fodder and fruit species (42.7%) were propagated through wilding (natural regeneration) and the remainder were propagated through seedlings (7.2%), seed (6.06%), and stem cutting (4.8%). Overgrazing (46.5%) followed by overexploitation (22%), climate change/drought (20.5%), and disease and pest (11%) were the major regeneration constraints to native fodder and fruit trees/shrubs species in the study area. Therefore, proper involvement either through research or development works are essential to reduce the propagation constraint of studied species. Ziziphus spina-christi (L.) Desf. followed by Faidherbia albida (Delile) A. Chev., Cordia africana Lam., Ximenia americana L., and Acacia senegal (L.) Willd. were the most preferred species for planting by farmers in the study area. Domestication should focus on the preferred top five species to promote species conservation and sustainable use.

One-Participant 401(k) as a Tool for Farmers and Ranchers

According to USDA, only 40% of farm households participate in some type of retirement account. For self-employed farmers and ranchers without full-time employees, the opportunity to invest in a One-Participant 401(k) plan is a way to (1) save money for retirement, (2) reduce taxable income, and (3) provide the potential option to borrow from the plan. This series of articles will review these features. What is a One-Participant 401(k)? The One-Participant 401(k)is a qualified retirement plan designed specifically for business owners with no full-time employees other than the business owners and their spouses. Visit with your financial planner and tax advisor if you have part-time employees and are considering establishing a 401(k) for your business to make sure you comply with 401(k) funding rules.

Ethnomathematics explorations on the concept of two-dimensional shape in “Tadulako Bulili” folk story

To explore the folklore of Tadulako Bulili as a literacy medium in learning the two-dimensional shape, a qualitative descriptive study was carried out with an ethnographic approach. Methods of observation, interviews, documentation, and literature studies were used to collect research data, which were analyzed using the Miles &amp; Huberman interactive model. The subjects of this study were traditional leaders, 3rd-grade elementary school teachers, lecturers, and several students who lived in Sigi Regency. The findings show that Tadulako Bulili's folklore can be thematic contextual learning in two-dimensional material that supports Ausubel, Bruner, and Gagne's learning theory. The results found four fundamental mathematical activities: counting, locating, designing, and explaining. In addition, various two-dimensional shapes were found in the illustrations of objects in the story. The exploration results also provided knowledge and information on the mention of two-dimensional shapes in the Kaili language and replicas of objects that were thought to be found in the story. Folklore could also introduce students to the local wisdom of Central Sulawesi, such as traditional houses, traditional weapons, hunting and farming tools, and the stories themselves.

SMART GROW – Low-cost automated hydroponic system for urban farming

Urban farming has gained popularity in recent years, as more people have become interested in locally grown food and reducing their carbon footprint. Smart hydroponic systems can be an important tool for urban farming as they allow for precise control over plant growth and require less space and resources than traditional farming methods. Urban areas often lack access to land suitable for farming, making hydroponic systems a viable option for growing crops in limited space. Readily available hydroponic systems in the market are costly and not cost effective, thus hydroponic systems are usually only installed in larger scale farming. The challenge here is to connect multiple low-cost sensors to microcontrollers and to any store-bought hydroponic set. This paper describes the development of smart Internet of Things (IoT) hydroponic system integrated with an Android mobile application for small scale urban farming.The new set up of IoT hydroponic set, coined as SMART GROW, is used to monitor and control various aspects of the system based on the basic parameters important in growing a healthy plant. The challenges faced during this build were irregular reading of the analog sensor when connected to a single board microcontroller (ESP32). This issue was resolved. SMART GROW currently is capable of monitoring basic parameters such as pH, EC and water level and can cater to additional sensors for monitoring other parameters if required. SMART GROW can easily be replicated and built at home and customized to the needs of the plant’s requirement. SMART GROW is versatile as it can be used to grow a wide variety of plants, including herbs, vegetables, and fruits, and offers several benefits over traditional soil-based growing methods such as automated regulation of the water level.

Estimation of economic life and feasibility of combine harvesters in Bangladesh deploying a unique web-based app

Combine harvester is one of the most crucial pieces of harvesting equipment in modern agriculture. Farmers and entrepreneurs employing a combine harvester need to focus on two pivotal factors: its profitability and optimal replacement time. Proper performance in this scenario can lead to prompt, and high-quality farm operations, enhancing income and simultaneously reducing product expenses significantly. This paper proposes a web-based application that would allow estimating the economic life and feasibility of combine harvesters in Bangladesh. The minimum cost value determination process has been used to estimate economic life by applying the double declining depreciation method. A high-level Python web framework has been used for the design and development of the software. The combine harvester exhibits a consistent economic life of 10 years for 300 to 450 hrs of annual use, with an increase in average yearly use from 300 to 450 hrs. As average yearly usage increases, the combine harvester's economic life declines drastically after 500 hrs of operation. Comparison with manual estimation shows that economic feasibility estimated by the web-based app provides more relevant data. The web-based app provides a useful tool for farmers, and entrepreneurs in Bangladesh to estimate the economic life and feasibility of combine harvesters, enabling better decision-making and improved managerial policies.

Environmental Impact Decision Support Tools for Horticulture Farming: Evaluation of GHG Calculators

Horticulture is essential in the European agricultural sector and fundamental for many EU member states. Decision Support Systems and Tools can play an essential role in a shift to result-based agriculture and evidence-based decision making, improving productivity and environmental performance of farming practices. Investigations have been conducted on horticulture crop and farming impact on the environment and Green House Gas emissions. Despite the availability of a broad spectrum of tools, the use of Decision Support Tools in agriculture in Europe could be much higher. This research aims to analyze and recommend environmental impact Decision Support Tools for small and medium-sized companies to approach, measure, and evaluate horticulture farming. The research methodology includes a systematic review, bibliometric analysis, Multicriteria Decision analysis, and a case study analysis. During the research, multiple tools, including calculators used for an impact assessment of the agricultural sector, were selected. After applying eligibility criteria, an in-depth analysis of eight of the most suitable calculators was performed. The results of the Multicriteria Decision analysis show that the Solagro Carbon Calculator, The Farm Carbon Calculator, and the Cool Farm Tool are recommended in the first place as Green House Gas calculators for farmers.

Evaluation of Greenhouse Gas Emissions of Quinoa Seed Production in Greece

Population growth has led to an increase in food production, resulting in an increase in agricultural products in terms of quantity and quality. Quinoa (Chenopodium quinoa Willd.) cultivation is prevalent in most areas of the world due to its high-quality grain and its potential to produce high yields under tough growing conditions. This study aimed to investigate all greenhouse gas (GHG) emissions generated by quinoa seed production in Greece and their relationship with farm-related factors, from fertilizer production to energy consumption for all cultivation techniques. The amount of all GHG emissions was estimated using Cool Farm Tool software. In order to collect data, a questionnaire including questions regarding cultivation details, soil characteristics, inputs, fuel, and water use was distributed and completed by forty quinoa producers from Central Greece. Accordingly, the estimated carbon footprint values per hectare and per kilogram of quinoa seed were 1,159.65 and 0.48 kg CO2-eq, respectively. The present research also found that the highest CO2-eq emissions per kilogram of quinoa seed were found to be associated with the production of fertilizers, with a value of 0.20 kg CO2-eq corresponding to 40.88% of the total emissions per kilogram of produced seed. Consequently, attention must be given for the mitigation of the environmental impact of quinoa seed production. It is particularly important to manage chemical fertilizers and agricultural machinery properly in order to ensure the sustainable cultivation of quinoa.