Livestock Technologies Research Articles

Repeatability and predictability of lying and feeding behaviours in dairy cattle

Subtle changes in behaviour, which may be useful as early indicators of disease or stress in farm animals, can be detected using precision livestock technologies. However, as animals often display differences in their baseline behaviours from one another, individual variation needs to be measured and accounted for if we want to successfully detect abnormalities. In addition to consistent individual differences in their mean behaviour, which are called behavioural types and measured by repeatability, animals may differ in the amount of day-to-day variation around their own mean. This is known as predictability and it is very rarely measured in animals as it requires data with high granularity for extended periods of time, which is hard to obtain without precision technologies. Here we aim to quantify the repeatability and predictability of lying and feeding, two behaviours which have been investigated as potential indicators of disease with inconsistent results, in dairy cows. We used data on daily lying behaviours from leg-mounted sensors for 2183 cows and data on daily feeding behaviours from neck-mounted sensors for 2584 cows belonging to multiple herds to quantify the variation between individuals, the individual differences in predictability and any correlations between individual behaviour type and predictability of the same behaviour. Using multivariate double hierarchical generalised linear models, we were able to quantify individual variation in feeding and lying behaviours of adult cows for the first time. Consistent variation between individuals was present for all measures of lying and feeding with repeatability values of 0.38 for daily feeding time and 0.31 for daily lying time. Individuals also varied in their levels of predictability with coefficients of 0.46 and 0.29 for the daily lying and feeding time respectively. Lastly, there were significant positive correlations between several behaviours and the amount of residual intra-individual variation for the same behaviour (mean lying bout length: 0.93, mean feeding bout length: 0.88), indicating that cows with the longest bouts of the two behaviours were also more variable and unpredictable, perhaps due to an opportunistic strategy. These results highlight the importance of measuring individual variation in behaviour, supporting the evidence of personality traits in cattle, as well as differences in predictability, which must be taken into account in any use of behavioural indicators for early disease diagnosis.

PSIII-30 Development of an application programming interface (API) to automate downloading and processing of precision livestock data

Abstract Advancements in technology have ushered in a new era of sensor-based measurement and management of livestock production systems. These sensor-based technologies have the ability to automatically monitor feeding, growth, and enteric emissions for individual animals across confined and extensive production systems. One challenge with sensor-based technologies is the large amount of data generated, which can be difficult to access, process, visualize, and monitor information in real time to ensure equipment is working properly and animals are utilizing it correctly. A solution to this problem is the development of application programming interfaces (APIs) to automate downloading, visualizing, and summarizing datasets generated from precision livestock technology. For this methods paper, we develop three APIs and accompanying processes for rapid data acquisition, visualization, systems tracking, and summary statistics for three technologies (SmartScale, SmartFeed, and GreenFeed) manufactured by C-Lock Inc (Rapid City, SD). Program R markdown documents and example datasets are provided to facilitate greater adoption of these techniques and to further advance precision livestock technology. The methodology presented successfully downloaded data from the cloud and generated a series of visualizations to conduct systems checks, animal usage rates, and calculate summary statistics. These tools will be essential for further adoption of precision technology. There is huge potential to further leverage APIs to incorporate a wide range of datasets such as weather data, animal locations, and sensor data to facilitate decision-making on times scales relevant to researchers and livestock managers.

511 Assessing the carry-over effects of precision livestock technology on steer performance and carcass characteristics

Abstract Our objective was to evaluate how virtual fencing grazing management during the stocker phase influences steer growth performance, carcass traits, and enteric emissions during the finishing phase. Angus steers [n = 96; initial body weight (BW) = 375 ± 7.2 kg) grazed native rangeland from 07 June 2023 to 31 August 2023 in Cottonwood, SD at South Dakota State University’s Cottonwood Field Station. Following summer grazing, steers were transported to Brookings, SD and fed for 130-d at the South Dakota State University Cow-Calf Education and Research Facility. During the summer grazing season, steers were assigned to different stocking rates (Light, Moderate, and Heavy, at 0.32, 0.42, and 0.72 animal unit months, respectively), and grazing strategies [continuous (CG) or virtual fencing rotational (RG)] in a 2 × 3 factorial design. Steers were transitioned from a 30% roughage to a 10% roughage diet over 21-d. The finishing diet (13.7% CP, 17.2% NDF, 1.36 Mcal/kg NEg, and 30 g/907-kg monensin sodium) was manufactured twice daily and provided ad libitum. Feed consumption was tracked using precision monitoring equipment (Insentec, The Hague, Netherlands). Steers were individually weighed on d 1 (entry BW), 21, 63, 90, and 130 and administered a steroidal implant (200 mg trenbolone acetate and 20 mg estradiol; Revalor-200, Merck Animal Health, DeSoto, KS) on d 21. Enteric emissions, including methane and carbon dioxide, were monitored using the GreenFeed trailer system (C-Lock Inc., Rapid City, SD), growth performance, carcass traits, and categorical carcass traits were analyzed in a factorial design using a randomized complete block design with individual steer considered the experimental unit. Final BW was determined from hot carcass weight divided by 0.625. Steers from heavy-CG had greater feedlot entry BW (P ≤ 0.05) compared with all treatments except light-CG and light-RG. Light-CG and light-RG had greater entry BW compared with heavy-RG (P ≤ 0.05). Gain efficiency was greater for light-CG compared with light-RG, moderate-CG, and heavy-CG (P ≤ 0.05), while moderate-RG and heavy-RG were intermediate (P ≤ 0.05). Steers from moderate-RG had greater marbling scores compared with heavy-RG (P = 0.05), and all other treatments were intermediate. Neither stocking density (P ≥ 0.15) nor grazing management strategy (P ≥ 0.13) had any influence on other measures of growth performance, emissions (CH4 and CO2) production rate, or carcass traits. These findings suggest that stocking density and grazing-management strategy (CG vs. virtual fencing-RG) influence gains on pasture and alter feedlot entry BW, highlighting the need for further investigation into their implications for greenhouse gas emissions, as well as for determining optimal stocking densities and management strategies for ranchers

456 Allocating distribution of pasture utilization across the grazing landscape in grazing steers equipped with virtual fencing collars

Abstract Spatial utilization of pasture landscapes by grazing animals is often heterogeneous and driven by complex environmental and physiological interactions between plants and animals. Synergistic energy pathways can be modeled using mechanistic relationships describing resource distribution, animal behavior, metabolic energy rate, and pasture utilization using biometric sensors. The objective of this study was to demonstrate the ability to measure the energy landscape by mapping fine-scale contributions to animal energy expenditure, nutrient acquisition, growth, and overall economic profitability. We utilized animal trajectories and location fixes recorded by virtual fencing collars (Vence) daily body weight (BW) using precision livestock scales (Smartscale, C-Lock Inc.) and oxygen consumption (GreenFeeds, C-Lock Inc.) on steers (n = 127), managed as part of a broader project to evaluate environmental synergies in extensive grazing systems. Steers were allocated to one of six native grass pastures assigned to either rotational or continuous grazing strategies, and one of three stocking rates (low, moderate, high) in a 2 x 3 factorial arrangement. Space utilization was quantified as the frequency of fixes located within each cell of a 5 x 5-meter Grid and the distance between grid cells and water was calculated using the Pythagorean theorem. Movement behavior was quantified using Program R to calculate step length, the distance between two temporally continuous fix points utilizing the Pythagorean Theorem, and turn angles calculated as the cosine of the pre- and pro-ceeding step lengths where larger values indicated greater deviation from a straight trajectory. A mixed linear regression model was fitted using the lmer function in the lme4 package. Space utilization decreased with increased distance from water (P < 0.05), with rotational grazing strategies increasing concentration around water sources (P < 0.05). This indicates an opportunity to utilize precision livestock technology to facilitate pasture management and increase space utilization in grazing cattle.

Adoption of Innovative Livestock Technologies: Potentials and Constraints among the Smallholder Farmers

Adoption of Innovative Livestock Technologies: Potentials and Constraints among the Smallholder Farmers

Impact of Integrated Agricultural Productivity Project on the Smallholder Beneficiaries in Mithapukur Upazila, Rangpur District of Bangladesh

In Bangladesh, plenty of development projects are assumed, though success of very few is evaluated. This study was aimed to evaluate the impact of Integrated Agricultural Productivity Project (IAPP) on the smallholder beneficiaries. The proportionate random sampling technique was used to select 90 smallholder beneficiaries from seven project villages implemented. Data were collected during 2018 to 2019 using a predesigned interview schedule. The perceived advantages of the project and the beneficiaries' annual income change were utilized to assess the impact of the project on the smallholder beneficiaries. Majority (58.8%) of the smallholder project farmers were under young to middle age category, with literacy belonged to moderate family size, small farm category, average annual income of BDT 134989 and 227633 during before and after the project intervention, respectively. They showed moderate contact with the extension source (95.6%) and moderate organizational participation (64.5%). Benefits derived from different components of the project were caused change in the usages of different agricultural improved technologies by the beneficiaries. The technologies implemented were improved fish, crop, livestock and water technology. All technologies had statistically significant contributions to the beneficiaries. The changes were significant for all the cases, viz. improved fish technology (t=13.65), improved crop technology (t=24.36), improved livestock technology (t = 20.43) and improved water technology (t= 22.29). There was also significant change in annual income comparing before and after the project intervention. Major problems faced during the intervention of the project were poor coordination of activities followed by training, poor quality deliverables and inadequate supply of project incentives. It is recommended that the authority needs to consider necessary measures to sustain the tempo and resolve the problems experienced by the beneficiaries in the future interventions.

Responsible development of digital livestock technologies for agricultural challenges: Purpose, practicality and effects are key considerations

AbstractDigital livestock technologies (DLTs) are presented as solutions to grand challenges in post‐Brexit British agricultural policy, such as climate change and food security. Evidence suggests technological solutions to agricultural challenges will be more effective with stakeholder and public engagement, yet there is little known about stakeholder views on these emerging technologies. We drew on responsible research and innovation, to analyse stakeholder perspectives on three case studies of DLT development through anticipatory focus groups with expert stakeholders in British animal agriculture. We found that stakeholders from broadly agroecological approaches to farming are at risk of exclusion from DLT development and policy, with negative implications for the ability of DLTs to resolve grand challenges in animal agriculture. We propose a heuristic framework of purpose, practicality and effects as key considerations for inclusive and responsible DLT development that contributes to ensuring effective solutions to grand challenges while avoiding wasted investments.

Understanding the heterogeneous effect of microcredit access on agricultural technology adoption by rural farmers in Ethiopia: A meta-analysis

Though the Ethiopian economy is predominantly agriculture-based, the adoption of agricultural technologies has been very low. The results of a previous study had shown that microcredit access was one of the factors affecting the adoption of agricultural technology in Ethiopia. However, its effect has not yet been analyzed at the meta-level. Therefore, this study employed meta-analysis to understand the heterogeneous effect of microcredit access among farmers adopting agricultural technologies. We used subgroup analysis and meta-regression analysis to identify the heterogeneity level of credit access on technology adoption using the random-effects (RE) model. The study observed that there was a positive effect of microcredit access on agricultural technology adoption with a log odds ratio of 1.59. The subgroup analysis revealed a 93.2 % overall variation (I2) with a p-value of 0.000, signifying a significant level of microcredit access within the between-groups heterogeneity of agricultural technology adoption studies conducted in Ethiopia. Notably, this was reflected by the adoption of improved livestock technologies, fertilizers, seed varieties, multiple agriculture, and irrigation technologies, with rates of heterogeneity of 94.9 %, 94.4 %, 94.3 %, 85 %, and 73.8 %, respectively, all with a p-value of 0.000. In addition, the meta-regression analysis results indicate that household experience, distance to the market, and income are significant moderators that affect the technology adoption decisions of farmers in rural Ethiopia. These findings suggest that policymakers should focus on improving the financial facilities and extension systems for rural farmers to enhance the adoption of agricultural technologies to increase production efficiency.

Are you ready for a challenge? Personality traits influence dairy calves' responses to disease, pain, and nutritional challenges

Dairy calves routinely experience disease, pain, and nutritional stressors such as diarrhea, dehorning, and weaning early in life. These stressors lead to changes in behavioral expression that varies in magnitude between individuals, where a greater magnitude change would suggest lower resilience in individuals to a stressor. Thus, this study first aimed to quantify the individual variation in magnitude change in feeding behaviors and activity in response to a bout of diarrhea, dehorning, and weaning. The next objective was to then investigate if personality traits were related to this magnitude of behavioral response in dairy calves, and thus their resilience toward these stressors. Calves were followed with 2 precision livestock technologies (e.g.: an automatic feeding system (AFS), and leg accelerometer) to track behavioral changes in response during the time when the stressors were present. The AFS provided daily measures of milk intake, drinking speed, rewarded and unrewarded visits to the milk feeding station, and calf starter intake. The leg accelerometer provided daily measures of steps, activity index, lying time, and lying bouts. At 23 ± 3 d of age, Holstein dairy calves (n = 49) were subjected to a series of standardized personality tests that exposed calf to novelty and fear stimuli. Factors extracted from a principal component analysis on the behaviors from the personality test were utilized to represent personality traits: Factor 1 ('Fearful'), Factor 2 ('Active') and Factor 3 ('Explorative'). The magnitude change in behaviors from the precision livestock technologies were calculated relative to the behavior performed on the day the stressor occurred (i.e., day of diagnosis; day of dehorning; day weaned). Linear regression models were utilized to determine if calf scores on each factor were associated with magnitude change in behavior for each of the stressor periods with day relative to the stressor included as a repeated measure. Models were run independently for the period leading up to and following each stressor. We found that calves varied in their behavioral responses to diarrhea, dehorning, and weaning stressors, despite being reared in the same environment and experiencing consistent management procedures. Additionally, personality traits measured from standardized tests were associated to both the direction and magnitude of change in behaviors around each stressor. For instance, with diarrhea, calves that were highly 'Fearful' had a greater magnitude change in milk intake and drinking speed following diagnosis than the least 'Fearful' calves. With dehorning, calves that were highly 'Explorative' had a greater magnitude change in lying time when dehorned, but a smaller magnitude change in lying bouts and drinking speed following dehorning, than the least 'explorative' calves. With weaning, calves that were highly 'Active' had a smaller magnitude change in unrewarded visits leading up to and following weaning than calves that were the least 'Active'. Each of the personality traits had a significant association with change in behavior surrounding each of the stressors evaluated, although these associations depended on the type of stressor. These results have implications for how individual calves experience each stressor and therefore individual animal welfare.

Impacts of ethnoveterinary medicine integrated with livestock farm technologies on the performance and antimicrobial resistance of indigenous goats in South Africa –A review

Ethnoveterinary medicine and livestock farm technologies represent a junction of innovation and tradition with the aim to accomplish livestock systems that are resilient, productive, and sustainable to meet 21st century challenges, especially the antimicrobial resistance issue. This article aims to emphasise the impacts of integrating ethnoveterinary medicine with livestock farm technologies on the performance of indigenous goats in South Africa. With the growing concern over antimicrobial resistance in livestock, there is a pressing need for complementary approaches to the health of animals and their productivity. In this review, the aim evaluated whether an integrative approach could offer a sustainable alternative that benefits animal health and productivity while addressing the concerns of antimicrobial resistance. Comparative study designs across multiple indigenous goat farms were used to integrate specific medicinal plants in ethnoveterinary medicine with present-day livestock technologies that are used to monitor the effects on livestock performance indicators and antimicrobial resistance patterns. In the treated populations, the outcomes were indicative of substantial improvements in reproduction and growth rates, and alongside, there has been a notable decrease in the markers of antimicrobial resistance. Therefore, it is proposed that through these discoveries, the integration of these traditional and modern approaches not only improve the performance of indigenous goats but also contribute immensely to the mitigation of risks associated with antimicrobial resistance.

Advancing Livestock Technology: Intelligent Systemization for Enhanced Productivity, Welfare, and Sustainability

The livestock industry is undergoing significant transformation with the integration of intelligent technologies aimed at enhancing productivity, welfare, and sustainability. This review explores the latest advancements in intelligent systemization (IS), including real-time monitoring, machine learning (ML), and the Internet of Things (IoT), and their impacts on livestock farming. The aim of this study is to provide a comprehensive overview of how these technologies can address industry challenges by improving animal health, optimizing resource use, and promoting sustainable practices. The methods involve an extensive review of the current literature and case studies on intelligent monitoring, data analytics, automation in feeding and climate control, and renewable energy integration. The results indicate that IS enhances livestock well-being through real-time health monitoring and early disease detection, optimizes feeding efficiency, and reduces operational costs through automation. Furthermore, these technologies contribute to environmental sustainability by minimizing waste and reducing the ecological footprint of livestock farming. This study highlights the transformative potential of intelligent technologies in creating a more efficient, humane, and sustainable livestock industry.

The influence of gender specific decisions on household technology choice within the farming households in central Uganda

How households make decisions, who influences decision making and how members bargain over resources and opportunities greatly affects the livelihood and wellbeing of members within a given household. This study sought to understand gender specific decisions and their influence on household technology choice, packaging and adoption of agricultural technologies. Growing Bananas with Trees and Livestock (GBTL) technology system was implemented by National Agricultural Research Organisation and Bioversity International in three districts of Central Uganda: Kiboga, Nakaseke and Ssembabule. Using Principal Component Analysis (PCA) and Cluster Analysis (CA), typologies were created in which two distinct clusters of farming households were revealed. Using a bargaining model of technology adoption, three types of households were identified; male and female only, female only and male only headed households. For technology uptake, either a single component, two components or all components of a technology was adopted. Results indicated that Household size, age, land owned, labour and gender composition of the household positively influenced the adoption of the technology. Farm households were able to take up and adopt components of the technology that were equivalent to the available household resources. Technology choice and adoption was influenced by available land, labor and household objectives (food, income and nutrition security). Households' ability to avert the loss of production and/or assets was very varied and depended on household size. For non-business home expenses, decisions followed a gendered perspective where households with both male and female, had more participants involved in household decision making, households make decision jointly when it comes to purchases and sales. Banana plantations establishment and management was for the spouse. Livestock production was initiated and managed by the household heads. Individual decisions were influenced by age of the household head, livestock owner. Joint household’s decision making was significant on purchases, sales of inputs and outputs, land ownership, and were influenced by household size and farm size. This study brings out important policy implications that in order to ensure widespread adoption of improved technologies, there should be equitable access to complementary inputs, especially land and labour for females. And technology packaging should take into consideration the gender specific decisions for sustainable agricultural development. Key words: Decision making, Technology choice, adoption, Coffee banana farming system, Gender

Social network analysis to predict social behavior in dairy cattle

Dairy cattle are frequently housed in free stalls with limited space, impacting social interactions between individuals. Social behavior in dairy cattle is gaining recognition as a valuable tool for identifying sick animals, but its application is hampered by the complexities of analyzing social interactions in intensive housing systems. In this context, precision livestock technologies present the opportunity to continuously monitor dyadic spatial associations on dairy farms. The aim of this study is to evaluate the accuracy of predicting social behavior of dairy cows using social network analysis. Daily social networks were built using the position data from 149 cows over 14 consecutive days of the study period. We applied the separable temporal exponential random graph models to estimate the likelihood of formation and persistence of social contacts between dairy cows individually and to predict the social network on the subsequent day. The correlation between the individual degree centrality values, the number of established social contacts per individual, between the predicted and observed networks ranged from 0.22 to 0.49 when the structural information from network triangles was included in the model. This study presents a novel approach for predicting animal social behavior in intensive housing systems using spatial association information obtained from a real-time location system. The results indicate the potential of this approach as a crucial step toward the larger goal of identifying disruptions in dairy cows expected social behavior.

The Workshop on Cattle Breeding and Fattening in an Effort to Increase the Human Development Index in Sijunjung Regency

The Human Development Index (HDI) is an important indicator to measure a country's progress in improving the welfare of its people. Compared to other Southeast Asian countries, Indonesia's HDI is still low. To improve Indonesia's HDI, the livestock sector, especially cattle breeding and fattening, can contribute significantly. ICMI (Indonesian Muslim Scholars Association) in collaboration with the Department of Agroindustry developed a high-quality and sustainable cattle breeding and fattening program. The goal of this collaboration is to improve cattle breeding and raising skills and support sustainable agricultural development. The solution of this collaboration is the improvement of participants' knowledge and skills on better livestock technology so as to increase the productivity and quality of beef cattle especially in Sijunjung Regency.

Livestock Farming in Bashkiria in 1946-1950: Dynamics of Production of Main Types of Products

The article examines the dynamics of livestock production in the individual and collective sectors in the Bashkir ASSR during the first postwar five-year period (1946-1950). Archival data is introduced into scientific circulation. Emphasis is placed on the fact that throughout the studied period, the recovery of livestock farming in the republic faced significant challenges. Information is provided on the production of main types of livestock products during the fourth five-year plan by specific categories in natural and monetary terms. It is noted that the pre-war level of production volume was never reached in various indicators: the number of cattle, sheep, goats, and horses, gross production of eggs, wool, honey, etc. Among the socio-economic reasons hindering the development of livestock farming in the republic are cited: consequences of World War II; low state investment in agriculture; low level of livestock technologies; deliberate policy by authorities viewing agriculture as an appendage to industry; low living standards of rural residents. The contribution of Bashkiria to the country’s food balance is determined. The conclusion is drawn that the individual sector of livestock farming, despite extremely unfavorable conditions and resistance from government authorities in the first post-war five-year period, overall maintained its positions and produced over 2/3 of the livestock products in the republic.

КОЗЬЕ МОЛОКО КАК ПЕРСПЕКТИВНОЕ СЫРЬЕ В ПРОИЗВОДСТВЕ СГУЩЕННЫХ ПРОДУКТОВ НА ПРИМЕРЕ ЗААНЕНСКОЙ ПОРОДЫ МИНИ-ФЕРМЫ «ДАНИРИНЫ КОЗЫ» ЯРОСЛАВСКОЙ ОБЛАСТИ

The aim of research is to study the main chemical and biological indicators of goat milk as a new raw material for the production of condensed products with increased biological value, produced at the Daniriny Kozy mini-farm in the Yaroslavl Region. Objectives: to conduct a comparative chemical analysis of cow and goat milk as a raw material base for the production of condensed products; to determine the main physical properties of goat milk: heat stability and acidity; to identify the best indicators of fat and moisture content in the milk of goats at different lactation periods. The object of research is goat milk obtained from a herd of Saanen goats (aged 2–5 years) at the Daniriny Kozy enterprise in the Yaroslavl Region. The method of daily milk (milk yield) recording was used. Control milkings were carried out from 01.06.2023 to 31.08.2023. The unit of measurement is liters, due to the small volumes of milk and livestock. The daily milk yield, total for 3 milkings (morning, afternoon and evening), was taken into account. The amount of milk was recorded in a measuring container for each goat separately. Samples were collected and prepared according to GOST 26809-86. Determination of heat resistance, acidity, microbiological contamination of raw materials was carried out on the basis of the chemical-analytical laboratory of the livestock technology department of the Yaroslavl Research Institute of Animal Husbandry and Forage Production. Milk was tested for fat, protein and dry nonfat milk residue content using the Laktan 1-4 device. During the experiment, the chemical composition of cow's and goat's milk was determined, a comparative analysis of the organoleptic properties, fat and moisture content in the milk of goats of different lactation periods was carried out. Goat's milk obtained from goats of the 1st and 2nd year of lactation is character¬rized by higher fat content and lower moisture content. Such indicators not only improve the quality of the finished product, but also reduce its cost due to the energy efficiency of the industrial production process of the condensed product. The product obtained from goat milk was called Condensed goat milk.

Development of an application programming interface to automate downloading and processing of precision livestock data

Abstract Advancements in technology have ushered in a new era of sensor-based measurement and management of livestock production systems. These sensor-based technologies have the ability to automatically monitor feeding, growth, and enteric emissions for individual animals across confined and extensive production systems. One challenge with sensor-based technologies is the large amount of data generated, which can be difficult to access, process, visualize, and monitor information in real time to ensure equipment is working properly and animals are utilizing it correctly. A solution to this problem is the development of application programming interfaces (APIs) to automate downloading, visualizing, and summarizing datasets generated from precision livestock technology (PLT). For this methods paper, we develop three APIs and accompanying processes for rapid data acquisition, visualization, systems tracking, and summary statistics for three technologies (SmartScale, SmartFeed, and GreenFeed) manufactured by C-Lock Inc (Rapid City, SD). Program R markdown documents and example datasets are provided to facilitate greater adoption of these techniques and to further advance PLT. The methodology presented successfully downloaded data from the cloud and generated a series of visualizations to conduct systems checks, animal usage rates, and calculate summary statistics. These tools will be essential for further adoption of precision technology. There is huge potential to further leverage APIs to incorporate a wide range of datasets such as weather data, animal locations, and sensor data to facilitate decision-making on time scales relevant to researchers and livestock managers.

Analysis of the Impact of Modern Livestock Technology Implementation, Resource Availability, and Marketing Strategy on the Sustainability of Chicken Farming Business in Central Java

This research investigates the key determinants of sustainability in the chicken farming industry, focusing on the interplay between marketing strategy, modern livestock technology implementation, resource availability, and the overall sustainability of chicken farming businesses. Utilizing Structural Equation Modeling (SEM), data from a sample of chicken farmers in the study region were analyzed to assess the relationships among these variables. The results highlight the significant positive impacts of a well-executed marketing strategy, adoption of modern livestock technology, and resource availability on the sustainability of chicken farming operations. The findings provide actionable insights for industry stakeholders to enhance their strategies and practices, contributing to a more sustainable and resilient chicken farming sector.

A SCALE TO MEASURE THE SCIENTIFIC TEMPER OF FARM WOMEN

The scientific temper unifies our mental processes, social interactions, and manner of life. The primary goal of this study work is to examine scientific positioning on advanced technologies. A person who is scientifically literate uses their extensive knowledge, which includes comprehension of scientific concepts and principles, theories, and procedures, to make well-informed decisions in the context of science and technology. In the time of scientific and technical advancement. Women’s material and nonmaterial development has been drastically altered by science. It is now a necessary component of life, without which no one could lead a comfortable life. Therefore, a new intellectual temper known as the scientific temper has been fostered by science and technology. Out of total 50 statements, 28 statements were selected to measure the scientific temper of women regarding the agriculture, household and livestock technologies. Coefficient of correlation was 0.769.

Perbandingan Analisis Finansial Sistem Kandang Closed House Semi Otomatis dan Otomatis di Peternakan Ayam Dekem Tengah Sawah

The cage system is one of the supporting factors in broiler chicken farming. In general, closed house cages are the type of cages that are often used by breeders for maintenance because they are considered more efficient for production. Livestock technology in Indonesia continues to develop along with the times. In addition, financial calculations are needed in a business to find out the profit of the business being run. Ayam Dekem Tengah Sawah Farm is a company in the field of raising broiler chickens which was founded in 2016 with a population of 29,000 chickens. The company has 2 (two) closed house cages with different systems, namely semi-automatic and automatic. Using the two cage systems, the owner of the cage does not clearly know the financial benefits that have been implemented. The research was conducted at Ayam Dekem Tengah Sawah Farm, Sumberagung Village, Peterongan District, Jombang Regency. This study aims to determine the differences in closed house cage systems (semi-automatic and automatic) owned by Ayam Dekem Tengah Sawah Farm through financial analysis. The method used is descriptive quantitative. The study was conducted for one period of rearing broiler chickens without special treatment for livestock. The results of this study indicate that the financial analysis of the results of raising broiler chickens using an automatic closed house cage system is superior to the results of raising broiler chickens using a semi-automatic closed house cage system.