Farm Profitability Research Articles

Effects of herd management decisions on dairy cow longevity, farm profitability, and emissions of enteric methane – a simulation study of milk and beef production

Sustainable dairy and beef production provides environmental, economic, and social values that can potentially be maximized by optimizing herd management strategies. The length of a dairy cow’s life is affected by, and affects, all three pillars of sustainability. Longevity in dairy cows is multifactorial and strongly dependent on herd management. Despite genetic improvements, the average time of culling for Swedish cows has barely changed and is currently at 2.6 lactations. This culling rate requires a high number of replacement heifers, generating high rearing costs for farmers. This study evaluated different herd management strategies to improve cow longevity and assessed the effects on enteric methane (CH4) emissions from the herd and the profitability of milk production and beef production from the dairy cows and their offspring. The base scenario, an average Swedish Holstein herd of 100 cows, was compared with seven scenarios simulated using a stochastic herd simulation model (SimHerd). Two of these scenarios involved improved health and survival of cows in the herd, three involved improved reproduction, one considered the consequences of keeping all surplus heifers in the herd, and one considered maximizing the use of X-sorted dairy semen and inseminating the rest of the herd with unsorted beef semen, to avoid surplus replacement heifers. Improved fertility had the greatest effect in increasing the productive life per cow, to 3.8 years compared with 2.8 in the base scenario, allowed for more use of beef semen, reduced the number of replacement heifers, and generated the highest herd profit (€98 per cow-year higher than base scenario). Keeping all surplus heifers instead of producing beef × dairy cross calves decreased the number of productive years by 0.8 and reduced profit by €22 per cow-year. The profit was highly associated with costs related to replacement heifers. The highest beef output (3 369 kg per year more than base scenario) was achieved by keeping all heifers and culling a high share of dairy cows, but this scenario also generated much higher enteric CH4 emissions (+1 257 kg per year). Improving health, survival, or fertility reduced enteric CH4 emissions by 90–255 kg per year, while total yearly beef production ranged from 59 kg less to 556 kg more than in the base scenario. Reducing the number of replacement heifers needed by improving cow reproductive performance is thus key to increasing cow longevity and profitability, while reducing enteric CH4 emissions from the herd without compromising milk and meat production.

Accurate monitoring of micronutrients in tilled potato soils of eastern Canada: Application of an eXplainable inspired-adaptive boosting framework coupled with SelectKbest

Plant growth is significantly dependent upon the combination and concentration of mineral nutrients in the soil, where the adequate supply of these nutrients is a severe issue in fulfilling the fundamental cellular process requirements. This study collected 22 physicochemical properties of tilled potato soils from eight stations in two Atlantic Canadian provinces (Prince Edward Island and New Brunswick). Along with the experimental investigation, an explainable dual pre-processing inspired-intelligent paradigm comprised of the SelectKbest feature selection (FS), modified bat algorithm (MBA), adaptive boosting (AdaBoost), and Shapley Additive Explanations (SHAP) explainer was designed to monitor the micronutrients, including copper (Cu) and zinc (Zn). The significant data predictors were filtered using the SelectKbest FS to monitor Cu and Zn. The MBA was coupled with AdaBoost for tuning the hyperparameters to ensure accurate predictions. To validate the outcomes of the MBA-AdaBoost, four advanced machine learning approaches, including categorical boosting (CatBoost) coupled with MBA (MBA-CatBoost), classical AadaBoost, ridge kernel regression (KRR), and multivariate adaptive regression splines (MARS), were examined to compare the accuracies. The robustness of the developed framework and the performance of comparative models were examined through several statistical metrics. Results revealed that the MBA-CatBoost performed the best in predicting the Cu (R = 0.9425, U1 = 0.1020, and U22 = 0.2036) and Zn in the soil (R = 0.9454, U1 = 0.0942, and U2 = 0.1858) when compared with other models. Furthermore, the SHAP explainer interpreted the block-box main model during the training phase by introducing the CEC and Fe as significant predictors to monitor the soil Cu and Zn, respectively. These findings demonstrate a clear and robust relationship between the presented modeling approach and the accurate prediction of soil micronutrient concentrations. Accurate predictions of micronutrients using these advanced techniques can be used to tailor site-specific micromovement management in agriculture fields to reduce production costs, increase farm profitability, and lower environmental contamination.

Pathogen Eradication in Garlic in the Phytobiome Context: Should We Aim for Complete Cleaning?

Global food production is challenged by plant pathogens that cause significant crop losses. Fungi, bacteria, and viruses have long threatened sustainable and profitable agriculture. The danger is even higher in vegetatively propagated horticultural crops, such as garlic. Currently, quarantine, rouging infected plants, and control of natural vectors are used as the main means of disease and pest control in garlic crops. Agricultural biotechnology, meristem-tip culture, and cryotherapy offer solutions for virus eradication and for the multiplication of 'clean stocks', but at the same time, impact the symbiotic and beneficial components of the garlic microbiome. Our research involves the first metatranscriptomic analysis of the microbiome of garlic bulb tissue, PCR analyses, and a biological assay of endophytes and pathogens. We have demonstrated that in vitro sanitation methods, such as shoot tip culture or cryotherapy can alter the garlic microbiome. Shoot tip culture proved ineffective in virus elimination, but reduced bacterial load and eliminated fungal infections. Conversely, cryotherapy was efficient in virus eradication but demolished other components of the garlic microbiome. Garlic plants sanitized by cryotherapy exhibited a lower survival rate, and a longer in vitro regeneration period. The question arises whether total eradication of viruses, at the expense of other microflora, is necessary, or if a partial reduction in the pathogenic load would suffice for sanitized garlic production. We explore this question from both scientific and commercial perspectives.

A deep learning approach combining DeepLabV3+ and improved YOLOv5 to detect dairy cow mastitis

Dairy cow mastitis has a great impact on the productivity of dairy cows and the profits of livestock farms. Early detection is of great significance to improve the efficiency of mastitis treatment. However, due to the low resolution of thermal infrared images and the complexity of the living environment of dairy cows, it is difficult to detect the eyes and udders of cows, which reduces the detection accuracy of mastitis. To solve this problem, this paper proposes a two-stage model (DCYOLO) integrating the DeepLabV3 + semantic segmentation network and an improved YOLOv5 target recognition network, which is used to detect the eyes and udders of dairy cows under complex background and applied to the severity classification of dairy cow mastitis. In the first stage, the DeepLabV3 + model was used to segment the eyes and udders of dairy cows from thermal infrared images. In the second stage, the segmented image was input into the target recognition YOLOv5 network for key parts recognition. Finally, to further improve the detection accuracy of the model, a convolutional block attention module (CBAM) was added at the end of the main part of the YOLOv5 model. After comparing different semantic segmentation and target recognition networks, the DeepLabV3 + network and YOLOv5 network performed best. The mIoU and mean pixel accuracy (mPA) of the DeepLabV3 + network reached 86.98 % and 92.92 %, respectively. The mean average precision (mAP) and F1 scores of the YOLOv5 network for unsegmented thermal infrared images reached 93.4 % and 90.9 %, respectively. The CBAM-added YOLOv5 (CAYOLOv5) model was combined with the DeepLabV3 + model. Compared with the single YOLOv5 model, the mAP and F1 scores of DCYOLO increased by 5.4 % and 5.3 %, respectively. Therefore, the proposed model can achieve more accurate positioning of key parts of dairy cows. Based on this model, the eye and udder temperature differences of 50 dairy cows were extracted for mastitis detection, and the detection results were compared with the results of the somatic cell count (SCC) approach. The results showed that the classification accuracy of mastitis was 86 %, and the average sensitivity and specificity were 79.41 % and 92.49 %, respectively. The dairy cow mastitis detection method based on the two-stage model can accurately locate the key parts of dairy cows and realize the automatic detection and classification of dairy cow mastitis, and the accuracy is high.

Profitability of insect production for T. molitor farms in The Netherlands

Abstract Insects are increasingly considered as a relevant alternative protein source in the transition to a more circular economy and more sustainable food production. Understanding the profitability of insect farms is crucial for starting entrepreneurs, established rearers, and third parties. In this study we analysed the revenues and expenses of seven T. molitor farms in the Netherlands, representing approximately a quarter of the total sector. We calculated their gross margin and net present value. Revenues came from the sales of fresh larvae and insect frass, and from extension services. Expenses included investments, and non-allocated and variable expenses. Results cover technical and economic results, and a qualitative description of farm operations. The gross margins and net present values ranged from −180 to 2,030 and from −12,359 to 15,535 EUR/tonne fresh larvae production, respectively. The main determinants of T. molitor farms’ profitability included the sales price of larvae, and its labour and substrate expenses. Our estimates can be used by decision making of farmers, credit providers, and policy makers to support the growth of this still very small, but emerging sector.

Produktivitas Dan Keuntungan Usahatani Padi Lokal Varietas Mayang (Oryza sativa L) Di Desa Bunipah Kecamatan Aluh Aluh Kabupaten Banjar

This research aims to determine the cost, production, revenues, profit and productivity of lokal paddy farming of the Mayang variety in Bunipah village Aluh-aluh district. The method used is a survey method with observation n techniques. The sampling technique used the census method, so that 33 farmer respondens were obtained. The results of this research show that the everage production of lokal rice of the Mayang variety in Bunipah village is 4.297,5 kg /farmers or 4,29 tons/hectare. The everage total cost is Rp.20.722.369,10/farmer. So the average revenue obtained is Rp.42.975.242,42/farmer or Rp.30.052.447,55/hectare. The average profit obtained during one production process is Rp.22.252.873,32/farmer or Rp.15.561.449,87/hectare. Thr everage productivity obtained was 2,93 tons/hectare

Effects of Lentilactobacillus buchneri and chemical additives on fermentation profile, chemical composition, and nutrient digestibility of high-moisture corn silage.

High-moisture corn silage presents a novel approach to reduce forage feeding expenses and enhance animal performance. Nevertheless, given corn's proclivity for starch, suboptimal fermentation quality in high-moisture corn silage can lead to spoilage, posing risks to livestock well-being. Therefore, the objective of this study is to evaluate the effects of different additives on the fermentation profile, chemical composition, nutrient digestibility of high-moisture corn (HMC) silage. All treatments improved the quality of high-moisture corn silage fermentation, as demonstrated by a decrease in pH and increase in lactic acid (LA) content. The high-moisture corn silage had a low content of trans fatty acids (TFA). Fermentation effectively decreased prolamin content while increasing 48-h in vitro dry matter digestibility (IVDMD), estimated total tract starch digestibility (eTTSD), total digestible nutrient (TDN), and relative grain quality (RGQ) of high-moisture corn silage. Nonetheless, no effect was observed on the 48-h IVDMD of high-moisture corn silage among the different treatments. Pearson's correlation analysis indicated that neutral detergent fiber (aNDF), neutral detergent insoluble protein (NDIP), crude protein (CP), zein, and prolamin closely correlated with the digestibility of high-moisture corn. The study's findings demonstrate that inoculating L. buchneri and potassium sorbate can improve the quality of high-moisture corn silage fermentation and digestibility in different hybrids. The results will provide insights for enhancing farm productivity and profitability in China.

Analysis of Irrigation Enhancement, Crop Diversification and Farm Profits: Evidence from Telangana State

In this study, the impact of access to irrigation on crop diversification and farm-level profits in the state of Telangana was examined. This study comprised two primary aspects. First, the determinants of crop diversification in Telangana were investigated using the logit model. Second, various farm production models were developed to evaluate the impact of irrigation enhancement sources on the farm profit function. The findings of this study indicate that the agricultural implements index and market access variables play a role in determining crop diversification in the studied villages, whereas surface irrigation has a negative effect on crop diversification. The Cobb–Douglas production function with different specifications was used in this study, which showed that the logarithms of the fertiliser variable and access to new irrigation facilities that improve groundwater table significantly enhance farm profits in the villages studied. The inclusion of a dummy variable representing agro-climatic conditions also revealed a significant effect on farm profits, indicating that farmers in north-zone districts achieve higher profits than those in central-zone districts, likely due to differences in soil fertility and crop diversification. Understanding the factors influencing farm profits is crucial for policymakers and extension agents in the state for informed decision-making and policy formulation.

Exploring the impact of soil water variability and varietal diversity on alfalfa yield, nutritional quality, and farm profitability

AbstractBackgroundDespite high nutritional and economic value, alfalfa yield has not been improved in the United States. Soil moisture critically influences alfalfa's yield and quality, affecting its physiological processes, nutrient uptake, and stand growth. Additionally, the maturity stage at harvest can significantly impact both hay yield and quality. Thus, this study aimed to assess the effect of different soil moisture levels and harvesting times on forage yield, nutritive value, and the overall profitability of commercially cultivated alfalfa.MethodsTwo conventional and three lower‐lignin alfalfa varieties were planted in a randomized complete block with split plot design under drought, rainfed, and irrigation conditions in 2020 in Manhattan, Kansas, USA. The dry matter yield (DMY) and forage nutritive value were evaluated at late bud, early flowering, and 7 days after early flowering stages, respectively.ResultsDMY varied with production year, soil water availability, and growth stages, with drought conditions causing a decline in DMY of 5% to 38% in the second production year. Water conditions and maturity stages influenced crude protein (CP) and in vitro dry matter digestibility (IVDMD). Higher soil moisture and advancing maturity stages negatively impacted CP, IVDMD, and relative forage quality. The study revealed net profit margins of 62%, 64%, and 52% for drought‐prone, rainfed, and irrigated production, respectively.ConclusionsHarvest timing and irrigation practices were found to have substantial implications for forage yield and nutritive value of alfalfa. The yield‐quality trade‐off differed under drought and irrigation, with early harvesting leading to lower yields but higher protein content and digestibility. The study findings provide potential guidance for improving alfalfa hay yield, quality, and profitability.

EFFECT OF NON-GENETIC FACTORS ON PRODUCTIVE AND REPRODUCTIVE PERFORMANCE IN CROSSBRED COWS MAINTAINED AT LIVESTOCK EXPERIMENT STATION, QADIRABAD DISTRICT SAHIWAL

The present study was undertaken to evaluate the effect of non-genetic factors such as the period of calving, season of calving, and parity on economically important productive and reproductive traits in crossbred cows (Holstein Friesian × Sahiwal) maintained at livestock experiment station Qadirabad Sahiwal, Pakistan. The study ranged from 1995 to 2014 (20 years). The duration of 20 years was divided into 4 periods (P1, P2, P3, and P4) with each period consisting of five years. Each year was further divided into three seasons winter (November-February), summer (March- June), and spring (July-October) based on geo-climatic conditions prevailing in the region. The parameters used as indicators of reproductive performance in this study were age at first calving (AFC), days open (DO), dry period (DP) and calving interval (CI). The overall least squares mean and standard errors for these reproductive parameters were 1235.23±45.81, 202.08±6.75, 178.4±6.85 and 482±5.97 days, respectively. While productive parameters were lactation milk yield 305 d(LMY), daily milk yield, and Lactation length (LL), and the least squares mean and standard errors of these were 2471.44±78.44 kg,8.07±0.27kg and306.22±4.84 days, respectively. Twenty years (20) data of 641 lactation records of crossbred cows representing the variance analyses indicated that significant (P≤0.05) effect of season of calving on age at first calving (AFC), days open (DO), lactation length (LL), and lactation milk yield (LMY). Least-squares means illustrated that the period of calving also significantly (P≤0.00) affects lactation milk yield (LMY) lactation length (LL) and dry period (DP). Similarly, a significant (P≤0.00) effect of parity on lactation milk yield (LMY), dry period (DP), days open (DO), and calving interval (CI) was noted. It is therefore concluded that the reproductive and productive performance of these crossbred cows is affected by some non-genetic factors and breeders must consider the season of calving, period of calving and parity in the management program because they greatly affect the farm productivity and profitability and they must select animals with higher breeding values to be the parent of the next generation.

Poultry disease early detection methods using deep learning technology

<span>Poultry production is a pivotal contributor to global economic growth, playing a central role in promoting human ecosystem sustainability. It offers affordable and readily accessible protein sources, encompassing meat, eggs, and other by-products. Beyond its direct nutritional benefits, poultry production enhances household income, bolsters food security, and aids in poverty reduction, making it integral to worldwide economic advancement. However, as the global population surges, so does the demand for poultry meat and eggs. Concurrently, poultry disease management emerges as a paramount challenge, leading to significant threats to food security and economic stability. Leveraging cutting-edge technology offers promising avenues to devise strategies that not only bolster farm profitability but also mitigate environmental impacts and foster the well-being of both animals and humans. This study systematically reviews the latest literature concerning poultry disease diagnosis based on deep learning techniques, elucidating the clinical manifestations associated with various ailments. The analysis indicates that emerging technological solutions, especially image processing and deep learning (DL), substantially outperform conventional manual inspection methods in early disease detection and warning in the poultry sector. Such innovations underscore their potential for revolutionizing poultry health management and disease mitigation.</span>

PRODUCTION OF ORGANIC GOODS OF THE RABBIT BREEDING AT DIFFERENT TECHNOLOGIES OF MAINTENANCE OF RABBITS

For the prospects of the rabbit breeding of present time optimal direction of development are individual and farmer economies, with the middle population of doe-rabbit. For the profitable conduct of the rabbit breeding except general principles of maintenance and growing, it is expedient to take into account the pedigree features of rabbits. Most distribution for the rabbit breeders of our country meat and hide of breed got: grey and white giants, butterfly, silvery, less popularity is used by the meat breeds of rabbits: New Zealand white and Californian.
 Main advantage of the rabbit breeding are an economy of areas and absence of capital apartments for growing of population of rabbits, in the modern rabbit breeding the systems of maintenance of rabbits are used in cages – outside, with the partial or complete process of mechanization: feeding and give to drink, moving away of wastes. At cellular maintenance of rabbits the most rational organization of works is provided on a supervision and reproduction. Cellular maintenance of rabbits gives an opportunity to carry out and control all processes and effectively to conduct veterinary and prophylactic measures. The table of contents of rabbits in cages provides a receipt from them of high-quality selfish products and carcass of kind fattened. For growing of different breeds of rabbits optimal economic indicators are the breeding of 30 female rabbits and more, at such population recoupment presents three years.
 The efficiency of management and high profitability of organic rabbit farms is ensured thanks to small capital investments in equipment and cages, early maturity and multi-fertility of rabbits, intensive growth of rabbits and rapid change of generations, obtaining products of high quality and quantity in a short time. The use of modern improved cage systems, high-quality feed and balanced rations for sexual age groups of rabbits allows to optimize the operating costs of the rabbit farm, and properly adjusted logistics of rabbit breeding products ensures constant profit at optimal profitability.

Efficiency, risk, and profitability of rainfed rice farming in South Sulawesi, Indonesia

Rice farming is a business that has many risks, and production risks cause fluctuations in production. Productivity influences farming income and profitability. An increase and decrease in production will affect revenue or profitability. The purpose of this study is to analyze the technical efficiency, production risk, and profitability of rainfed lowland rice farming. This research was conducted in two regencies in South Sulawesi Province, namely Maros Regency and Pangkajene Islands Regency. The sample of this study was 100 farmers in rainfed rice fields. This research used quantitative methods with a survey approach. Data were collected using observation, recording, and interview instruments, and were then analyzed using quantitative description coupled with a t-test for independent samples. The results showed that rainfed lowland rice farming in Maros Regency and Pangkajene and Archipelago Regency was technically efficient. Rainfed lowland rice farming in Maros Regency and Pangkajene Regency and Islands is at risk. Rainfed lowland rice farming in Maros Regency and Pangkajene Regency and the islands using profitability analysis generates income and profit, and is feasible to cultivate. Farmers need to use production inputs as recommended to increase production reduce production risk and efficiently use inputs.JEL Classification D10; Q00; Q12

Effects of mineral and vitamin supplementation on pregnancy rates in Nelore cattle submitted to FTAI programs with different reactivity scores

A high-reactivity herd temperament reduces productivity and profitability in cattle farming. In Bos taurus indicus (Nellore) cattle, we hypothesized that a higher reactivity score is associated with a lower pregnancy rate, and that injectable supplementation with minerals (Cu, Zn, Mn, Se) and vitamins (A, E) would increase the pregnancy rate and reduce embryonic mortality in very reactive cows. Injectable supplement or control treatments were administered on days 25 and 10 before fixed-time artificial insemination (FTAI; Day 0 : day of FTAI). We selected 1722 cows 45 ± 7 days postpartum, with different behavioral reactivity levels, and a series of measures related to reproduction were measured. The cows were randomly grouped and received sc 1 mL/50 kg live weight of the supplement (n = 872) or placebo (n = 850), 25 and 10 days before the FTAI protocol (Day–25 and Day–10 respectively). On Day −10, devices containing 1 g progesterone were inserted into the vagina, and 2 mg estradiol benzoate was applied intramuscularly. On Day–2, the devices were removed and 530 µg of sodium d-cloprostenol, 300 IU of equine chorionic gonadotropin, and 1 mg of estradiol cypionate were applied. At 48 h after final injection, the cows were subjected to FTAI (Day 0). On Day - 25 (25 days before IATF), temperament was graded as 3 to 12 using composite reactivity score (RS), which evaluates movement and breathing while the animal is in the cattle chute, and their escape velocity, and was used to classify cows as calm (RS ≤ 4; n = 590), reactive (RS 5 to 8; n = 573), and very reactive (RS ≥ 9; n = 559). On Day 0, calm cows had a higher largest follicle diameter on the FTAI compared to reactive and very reactive (14.4 + 0.2 vs. 13.6 + 0.4 and 13.2 + 0.2 mm, respectively; P = 0.03). Interactions were observed, where supplemented cows compared to those no supplemented had higher pregnancy on Day 30 (P = 0.04; 60.00 vs. 54.10 % calm and 58.00 vs. 52.50 % very reactive) and Day 60 (P = 0.03; 58.70 vs. 47.90 % calm, 52.20 vs. 49.10 % reactive and 48.40 vs. 41.30 % very reactive) and reduced embryonic loss at 30 to 60 d (P = 0.04; 2.00 vs. 6.10 % calm, 4.20 vs. 8.40 % reactive and 9.60 vs. 11.20 % very reactive). Supplementation on Days–25 and–10 improved pregnancy rates and reduced embryonic in calm and very reactive cows.

CHARACTERISTICS OF VEGETABLE FARMERS WITH INTEGRATED CROPTING PATTERNS AND ITS IMPLICATIONS FOR THE APPLICATION OF FARMING TECHNOLOGY

This paper is the first to investigate the characteristics of chili and celery farmers in dry land agroecosystems with wet climates and their implications for the application of farming technology. The obstacle faced is the limited use of existing seeds and labor, so that additional use of superior varieties of seeds and additional labor from outside the family is still needed. The paper also analyzes the production costs and benefits of chili and celery farming, taking into account the labor costs in the family. The results of research on red chili farming with celery show that this business is profitable with a total profit of IDR. 20,553,500,-. This farming business has provided profits with celery production of 405 kg, red chili production of 585 kg, and BEP price of IDR 15,495/kg celery and IDR 14,143/kg red chili. The R/C ratio value is 2.95 and the B/C ratio is 1.95, indicating that the farming business observed is profitable and worth pursuing. The novelty of this paper is that it introduces a new perspective on the adaptation and innovation of chili and celery farmers in dry land agroecosystems with wet climates, based on the FSA (Farming System Analysis) concept. The paper also provides empirical evidence of the effectiveness and feasibility of chili and celery farming in the region. The paper contributes to the literature on agricultural development and technology by highlighting the role of farmer characteristics and farming technology in enhancing the productivity and profitability of chili and celery farming.

ANALYSIS OF INSTITUTIONAL ENGINEERING IN ONE OF THE WET CLIMATE DRY LAND AGROECOSYSTEM VEGETABLE PLANTING

This study is the first to apply a relationship approach between farmer groups and other supporting institutions to develop a farming system and rice crop institutions in a region. The study aims to solve the problems faced by rice farmers in Rawa Medang village, West Tanjung Jabung Regency, by facilitating the adoption of sustainable rice farming system technology through institutional cooperation. The methodology used in this study applies the Participatory Research Appraisal (PRA) method, to explore the problems faced by rice farmers. Alternative interventions include the formation of several farmer groups or Gapoktan, named Joint Enterprises, a short discussion about the rice farming system, looking at the urgent needs of farmer groups, and connecting them with supporting institutions. Based on the PRA results, the problems prioritized are (1) Rice stem disease by Blas, (2) The presence of snail pests, (3) Seedlings, (4) Capital, (5) Subsidized fertilizer, (6) Meetings between groups, and (7) Technical guidance for rice plants. The novelty of this study is that it introduces a new framework of institutional engineering analysis supporting rice farming technology, based on the FSA (Farming System Analysis) concept. The study also provides empirical evidence of the effectiveness of the relationship approach in improving the productivity and profitability of rice farming in the region. The study contributes to the literature on agricultural development and innovation by highlighting the role of institutional cooperation in enhancing the adoption of sustainable rice farming system technology.

Profit Efficiency among Dairy Farmers in Southern India: An Application of Stochastic Frontier Profit Function.

Background: Dairy farming has emerged as an important profitable enterprise in India as it is a source of income, especially for small and marginal farmers;the study aims to understand the reasons for increased profit of dairy farmers of South Indian states. Methods: The present study was undertaken in Southern Indian states during 2020-21 to estimate the profit efficiency of milk producers across different herd-size categories. Result: Maximum likelihood estimates (MLE) of specified profit function revealed that overall, prices of green fodder (0.1873), prices of concentrate (0.1072), veterinary service rate (0.0569) and herd size (0.7545), had a positive and significant impact on normalized profits, whereas prices of dry fodder (-0.0277) and labour wages (-0.1652) had a negative and significant impact on normalized profits, respectively. Overall, the mean profit efficiency of dairy farmers was found to be 58.65 per cent indicating 41.35 per cent of profit efficiency was lost due to technical and allocative inefficiencies in milk production. Results from the profit inefficiency model revealed that overall, education, herd size, herd composition and experience in dairy farming had a negative and significant impact on profit inefficiency.

Unveiling the Genetic Symphony: Harnessing CRISPR-Cas Genome Editing for Effective Insect Pest Management.

Phytophagous insects pose a significant threat to global crop yield and food security. The need for increased agricultural output while reducing dependence on harmful synthetic insecticides necessitates the implementation of innovative methods. The utilization of CRISPR-Cas (Clustered regularly interspaced short palindromic repeats) technology to develop insect pest-resistant plants is believed to be a highly effective approach in reducing production expenses and enhancing the profitability of farms. Insect genome research provides vital insights into gene functions, allowing for a better knowledge of insect biology, adaptability, and the development of targeted pest management and disease prevention measures. The CRISPR-Cas gene editing technique has the capability to modify the DNA of insects, either to trigger a gene drive or to overcome their resistance to specific insecticides. The advancements in CRISPR technology and its various applications have shown potential in developing insect-resistant varieties of plants and other strategies for effective pest management through a sustainable approach. This could have significant consequences for ensuring food security. This approach involves using genome editing to create modified insects or crop plants. The article critically analyzed and discussed the potential and challenges associated with exploring and utilizing CRISPR-Cas technology for reducing insect pest pressure in crop plants.

Sustainable agricultural practices in South Asia: A comprehensive review

Abstract Overpopulation is a root cause that impedes food production and supply to the continuously growing population. Since agriculture is the primary source of food production, producers are inclined towards various unsustainable agriculture practices contributing to climate change. Therefore, sustainable agricultural practices have gained the spotlight to reduce the risk of climate change and increase crop yields. Specifically, South Asian countries take a significant hit with respect to agriculture and climate change because much of the population is earning their livelihood through agriculture. We conducted a comprehensive review to map different sustainable agriculture practices and understand how these practices impact climate change, the livelihood of farmers, and food security in South Asia. A systematic search carried out on PubMed (NCBI) and Scopus (Elsevier), resulted in the inclusion of 42 articles for analysis. The review identified agroforestry and organic farming as the most commonly used practices in the South Asian region, followed by zero tillage practices, use of hybrid seeds, residue and integrated pest management, and cropping systems. These sustainable agriculture practices ensure that sufficient food can be produced to feed the rising population with efficient use of natural resources. In addition, sustainable agriculture gains economic profitability for farmers and improved employment opportunities for women. Since sustainable agricultural practices are the best way forward, we recommend encouraging it by incentivizing the farmers. Due to contextual variations, future research can focus on identifying best practices for specific contexts.

Trout Production in District Ganderbal – An Analysis of Economic Challenges

The present study carried during the year 2022-23, worked on the impact of the introduction of genetically improved strains of rainbow trout on the economy of the fish farmers, in comparison to the normal strains. The economy of 40 farmers in groups of 20 Normal stock (NS) and Genetically Improved Stock (GIS) each was conducted and interviewed using a pre-tested questionnaire. The investigation showed that fixed capital investment on sample farm was Rs.1.25 lakh per raceway in both the set ups. The major share of investment was for the construction of raceway, which accounted for 68.53% of total investment on sample farms. The share of total variable cost was 58.37% in NS and 48.50 in GIS per cent and fixed cost was 41.62 in NS and 51.49 in GIS group. Feed was the major cost component accounting for about 46.43 per cent of the total cost in NS, while as it was reduced to 37.15% in GIS, thereby encouraging as a key factor in deciding profitability of trout farming. Resource use efficiency showed that feed was overutilized while labor was under-utilized in NS, while as it was optimally utilized in GIS group. The returns to scale in trout production of 1.25 indicates increasing returns to scale in trout production. High price of feed and seed are found to be the major constraints in trout culture. The B-C ratio worked out to be 1.37 in NS group and 1.87 in GIS group, indicating the economic feasibility of trout farming in the Kashmir valley, and better economic profile of farmers farming GIS strain.