Higher Variable Costs Research Articles

Optimizing Eurasian Perch Production: Innovative Aquaculture in Earthen Ponds Using RAS and RAMPS-Economic Perspective.

Aquaculture in rural areas, carried out in accordance with current EU requirements, aims to contribute significantly to the conservation of the biodiversity of aquatic resources, the protection of which is a prerequisite for sustainable economic and social development. The objective of this study was to present the conceptual and technical framework and to analyze the costs and profitability of producing the consumer-attractive Eurasian perch (Perca fluviatilis L.) based on the untapped potential of hatchery infrastructure and dedicated earthen ponds for common carp (Cyprinus carpio L.) production. The experiments were conducted under Polish conditions, but the results/methods can be successfully applied in other countries, mainly in Central and Eastern Europe, where production in earthen ponds is the basis of aquaculture production. The analysis of the profitability of the venture shows that the cost structure was dominated by labor and feed inputs. Despite high variable costs, this type of production can be profitable and contribute to food security and economic development in line with the EU's Blue Growth Strategy. The article also analyzes the potential opportunities and risks of fish production based on the Recirculating Aquaculture System (RAS) and the Recirculating Aquaculture Multitrophic Pond System (RAMPS).

Understanding the illegal drug supply chain structure: a value chain analysis of the supply of hashish to Europe

Despite the social, health, law enforcement, and economic importance of illegal drug supply, the lack of information and understanding regarding these supply chains stands out. This paper carries out a disaggregated analysis of the structure of the hashish supply chain from Morocco to Europe to explain the value contributions at each level, the end-price formation, and the supply chain management practices. The methodology adopted is based on a mixed method of data collection where the primary data are gathered from field interviews with cannabis producers and dealers and secondary information is obtained from official statistics, research papers, informational reports, and documentaries. We review supply and value chain frameworks through the lens of cost–benefit analysis. Our main findings show an unequal contribution on the part of the different levels of distribution, with end-user prices increasing by 7000% of the cost of production during the supply chain. The chain also has high variable costs but limited fixed ones, exacerbating the lack of stability and fostering continuous adaptation. We also detect a reluctance to raise end-user prices but a great propensity to change quality. This research may have implications for several stakeholders. In the case of dealers, we find that they have created a supply-push system thanks to their dominant power, leaning on information sharing as a source of resilience. In the case of law enforcement, we delve into the operational functioning of the drug chain and the reasons for its survival. For financial investigation operations, unknown or unrealized economic parameters are quantified. For development agencies, the need to implement alternative development programs for producers is evidenced. Finally, for health authorities, we highlight the consequences of seizures and prohibitions of hashish trafficking on the deterioration of the quality of hashish and the subsequently added health hazards for end-users.

Identifying High Direct Variable Costs of Open Carpal Tunnel Release Patients Using Time-Driven Activity-Based Costing

To improve value in health care delivery, a deeper understanding of the cost drivers in hand surgery is necessary. Time-driven activity-based costing (TDABC) more accurately reflects true resource use compared with traditional accounting methods. This study used TDABC to explore the facility cost of carpal tunnel release and identify preoperative characteristics of high-cost patients. Using TDABC, we calculated the facility costs of 516 consecutive patients undergoing open carpal tunnel release at an orthopedic specialty hospital between 2015 and 2021. Patients in the top decile cost were defined as high-cost patients. Multivariable logistic regression was used to determine preoperative characteristics (age, sex, body mass index, race, ethnicity, Elixhauser comorbidity index, American Society of Anesthesiology score, preoperative Disabilities of the Arm, Shoulder and Hand score, Short-Form 12, and anesthesia type) independently associated with high-cost patients. Surgery-related personnel costs were the main driver (38.0%) of total facility costs, followed by preoperative personnel costs (21.3%). There was a 1.8-fold variation in facility cost between patients in the 90th and 10th percentiles ($774.69 vs $431.35), with the widest cost variations belonging to medication costs ($17.67 vs $1.85; variation, 9.6-fold) and other supply costs ($213.56 vs $65.56; variation, 3.3-fold). Using multivariable regression, predictors of high cost were patient age and use of general anesthesia. Total facility costs correlated strongly with the total operating room time and incision to closure time. Efforts to decrease operating room time may translate into reduced personnel costs and greater cost savings. Multidisciplinary initiatives to control medication expenses for patients at risk of high costs may narrow the existing variation in costs. Economic and Decision Analysis II.

Reinforcement Learning Enabled Autonomous Manufacturing Using Transfer Learning and Probabilistic Reward Modeling

Here we propose a reinforcement learning enabled physical autonomous manufacturing system (AMS) that is capable of learning the manufacturing process parameters to autonomously fabricate a complex-geometry artifact with desired performance characteristics. The poor sample efficiency of traditional RL algorithms challenges real-world manufacturing decision making due to a high variable cost from raw material, machine utilization, and labor costs. To make decision making sample efficient, we propose to leverage a first-principles based source task for training, transfer effective representations from trained knowledge, and then use these representations to interact with the physical system to learn a probabilistic model of the target reward function. We deploy this idea to a novel dataset obtained from a custom physical AMS machine that can autonomously manufacture phononic crystals, a complex geometry artifact with spectral response as performance characteristic. We demonstrate that our method uses as low as 25 artifacts to model the interesting part of the target reward function and find an artifact with high reward. This task typically requires manual design of phononic crystals and extensive empirical iterations on the order of hundreds.

ECONOMIC ANALYSIS OF RICE-PRAWN-FISH FARMING PRACTICES IN SOUTH-WEST COASTAL BANGLADESH

A field survey through questionnaire was conducted in rice-prawn (Macrobrachium rosenbergii)-fish culture ghers in six villages of Khulna, Satkhira and Bagerhat districts of south-west Bangladesh during March to December, 2008 to assess present culture practices. About 10-25% of the total area of land was converted for building canals and dikes and the remaining area were used for rice cultivation. Boro with prawn and fish appeared to have positive impact on the economic return as well as on the livelihood of the farmers. After harvesting rice, total area were used for prawn and fish culture. Cost benefit analysis revealed that the seed cost of prawn was the highest variable cost. Higher seed cost of prawn and fish can be reduced by ensuring the available supply of seed in proper time. The average Net Return (NR) was BDT 72,395±4,6943 ha-1yr-1 and the Rate of Return (RR) of the rice-prawn-fish farming was 14.64%. Compared with mono crop culture system, the rice-prawn-fish integrated farming in ghers appeared to be economically viable, socially acceptable and environmentally sustainable.

Shrimp farmers perceptions on factors affecting shrimp productivity in integrated mangrove-shrimp systems in Ca Mau, Vietnam

Vietnamese mangroves in the Mekong Delta have been degraded and lost by war, coastal development and aquaculture since the 1950s. However, to promote replanting and support local livelihoods Ca Mau province issued 20-year mangrove leases to local farmers in 1991 for 70:30 forest:exploitation, which was later changed to 60:40 in 2010. Extensive integrated mangrove-shrimp systems were particularly attractive to poor farmers and understanding their perceptions on factors affecting productivity as well as socio-economic, technical and financial characteristics can aid solutions to better management. Shrimp productivity is variable and concern from the local producers that this could be because of age of mangrove stands in the systems led to this study. Forty-six households were selected at random based on different mangrove ages (2–4, 5–7, 9–12 and > 12 years old) in Lam Hai commune, Ca Mau province. The structured questionnaires with both quantitative and qualitative methods, a participatory approach, principal component analysis (PCA), and analytic hierarchy process (AHP) were employed to evaluate the effects of mangrove ages on pond environment and shrimp productivity. The average farm area was 4.9 ± 1.9 ha, with forest:exploitation ratio of 60:40. Mean shrimp productivity was 188.1 ± 94.7 kg ha−1 yr−1 and this was not significantly different between the four ages of mangrove systems. High variable costs of pond dredging meant the lowest profit margin was recorded in >12 years old mangrove stands but the highest profit margin was found in 9–12 years. Water level management was identified as a key factor in stepwise regression analysis. The farmers’ responses to the criteria for integrated mangrove-shrimp pond management under different mangrove age systems differ and are discussed.

Alternative payment models for durable and potentially curative therapies: The case of gene therapy for haemophilia A

AbstractIntroductionThe emergence of durable and potentially curative cell and gene therapies (also known as advanced therapy medicinal products) with high price tags is challenging conventional health care payment systems. Among these are gene therapies in various phases of development for haemophilia A and B. The emergence of these therapies comes with clinical and economic uncertainties for payers, providers, patients, and manufacturers. These include uncertainties about expression of the intended physiological response, patient outcomes, and duration of treatment effect, along with potentially high upfront costs, variable additional costs, and uncertainties about uptake of the therapy among indicated patient populations. These clinical and economic uncertainties raise interest among payers, providers, and manufacturers in risk‐sharing arrangements, including alternative payment models (APMs).SummaryAPMs differ from traditional fee‐for‐service payment for health care. For example, some APMs are designed to reward clinicians and provider organizations for delivering high‐quality and cost‐effective care. The APMs described here, outcomes‐based models (or value‐ or performance‐based models) and finance‐based models, are designed to mitigate or otherwise manage financial risks associated with health care payment, including instances in which patient outcomes for costly therapies are uncertain. We examine how such APMs may be applicable in the context of emerging gene therapies for haemophilia A, including considerations in determining whether any particular APM may be most suitable.KEY POINTS OF CONSIDERATION Gene therapies for haemophilia are among the emerging durable and potentially curative cell and gene therapies with high price tags that are challenging conventional payment systems. These therapies present clinical and economic uncertainties for payers, providers, patients, and manufacturers, including regarding expression of the intended physiological response, duration of treatment effect, patient outcomes, potentially high upfront costs and variable additional costs, and uptake among potentially indicated, diverse patient subgroups. These uncertainties raise interest among payers, manufacturers, and providers in risk‐sharing arrangements, including alternative payment models (APMs) such as various outcomes‐based and finance‐based models. This paper describes a taxonomy of APMs. Then, for the particular context of gene therapy for haemophilia A, we present a set of factors to be considered when determining whether an APM risk‐sharing arrangement may be appropriate for a given gene therapy, and, if so, which APM may be most suitable. [Correction added on 21 February 2022, after first online publication: the ‘Key Points of Consideration’ have been added in this version.]

Cost and returns of milk production in selected arid district of Rajasthan

The significance of the sector further increase in arid western Rajasthan where frequent droughts are the primary concern. Milch animals are kept as farming household from very long time in India. The Bikaner district of Rajasthan is selected for the study purposively as it is having largest cattle population and another reason for selecting the district is that if has higher indigenous cattle population in the area is second largest enterprise after crop production. Predetermined samples of 180 farmers, selected farmers were categorized into small, medium and large herd-size categories using cumulative square root frequency method. It was evaluated region wise cost of concentrate of indigenous cows; green fodder and total feed cost per day per indigenous cow were highest for canal irrigated region causing highest variable cost also. Due to good feed, the returns were highest in the area. It was found by the perusal of result that per litre cost of milk production was highest for unirrigated region followed by canal irrigated region and least by tube well irrigated region but average per day milk production and net return per day per buffalo was highest on tube well irrigated region followed by canal irrigated region and least unirrigated region, respectively.

What is different about different net-zero carbon electricity systems?

In deeply decarbonized electricity systems with significant shares of variable renewable energy, the additional availability of at least one firm electricity generating technology can overcome reliability challenges and substantially reduce electricity costs. Firm resources can operate at any time of the year and for as long as needed to maintain electricity system reliability. Low- and zero-carbon firm technologies include flexible resources with high variable and low capital costs, such as biogas or hydrogen combustion, capital-intensive resources with low or zero variable cost, including nuclear and geothermal, as well as intermediate resources such as natural gas plants with carbon capture and sequestration (CCS). This paper explains the distinct roles of nuclear, CCS, and combustion of zero-carbon fuels in decarbonized electricity systems as examples of each class of firm resources. We analyze and compare results from three long-term electricity system capacity expansion models for California and the U.S. Western Interconnection, demonstrating robustness of our conclusions to different model assumptions and domains. Individually, each firm technology delivers substantial cost reductions relative to portfolios restricted to wind, solar, and energy storage alone. Additionally, because each technology occupies a distinctive functional niche in the electricity system, having all of these technologies available optimizes the utilization rate of each resource and reduces system costs by up to 10% relative to cases with just one class of firm resource. The analysis highlights the benefits of an expansive range of technology options to meet emissions reductions goals for the power sector while maintaining operational reliability and affordability.

DIFFERENTIATION OF OIL PRODUCTION BREAK-EVEN LEVEL AMONG WORLD OIL COMPANIES

The issue of modern development in the oil industry has become extremely urgent. In 2020, for the first time in history, the exchange price of oil crossed the negative threshold, radically changing the understanding of economic processes in the industry. This paper examines the consequences of this stressful situation in the context of the financial stability of global oil companies in conjunction with ensuring the budgetary balance for resource-exporting countries. In the course of the study, the factors that influence the pricing in the oil market have been clarified. The authors have calculated break-even oil prices for the world’s largest oil companies Saudi Aramco (SAU), ExxonMobil (USA), British Petroleum (GBR), and Rosneft (RUS). An analysis of the fiscal break-even of oil prices has shown that Russia, compared to the Gulf countries, has a greater margin of budgetary stability, since the break-even price of oil is several times lower than in Iran, Iraq, and Saudi Arabia. Based on the assessment of the operating leverage of the oil companies, a limit was set for the decline in profits as a result of the drop in oil production. The calculation of the target price for large global companies has shown that Rosneft has the highest price level due to high variable costs, and the target price for Saudi Aramco is approximately at the same level. ExxonMobil and BP’s target price levels are lower. The results obtained confirm the need to continue searching for solutions to optimize costs to lower the breakeven level of oil production. Keywords: oil, break-even price, prime cost, pricing factors, budget balance, oil market, price shocks. JEL Classifications: L21, G31, Q49 DOI: https://doi.org/10.32479/ijeep.11260

Intelligent and efficient? An empirical analysis of human–AI collaboration for truck drivers in retail logistics

PurposeTechnological advances regarding artificial intelligence (AI) are affecting the transport sector. Although fully autonomous delivery, or self-driving trucks, are not operating currently, various AI applications have become fixed components of cargo vehicles. Since many research approaches primarily concentrate on the technical aspects of assistance systems (ASs), the economic question of how to improve efficiency is seldom addressed. Therefore, the purpose of this paper is to apply an efficiency analysis to measure the performance of truck drivers supplying retail stores.Design/methodology/approachFor this comparative study, 90 professional truck drivers in three groups are compared with (1) trucks without AS, (2) trucks with AS that cannot be turned off and (3) trucks with AS that can be turned off. First, we build a model investigating the impact of performance expectation, effort expectation, social influence and facilitating conditions on the behavioural intention to use AS. Second, we explore the impact of truck drivers' behavioural intention on actual technology use, misuse and disuse; operationalize these constructs; and merge them with our behavioural constructs to create one econometric model.FindingsThe human–AI system was found to be the most efficient. Additionally, behavioural intention to use ASs did not lead to actual usage in the AI-alone observation group, but did in the human–AI group. Several in-depth analyses showed that the AI-alone group used AS at a higher level than the human–AI group, but manipulations through, for example, kickdowns or manual break operations led to conscious overriding of the cruise control system and, consequently, to higher diesel consumption, higher variable costs and lower efficiency of transport logistical operations.Research limitations/implicationsEfficiency analysis with data envelopment analysis is, by design, limited by the applied input and output factors.Originality/valueThis study represents one of the first quantitative efficiency analyses of the impact of digitalization on transport performance (i.e. truck driver efficiency). Furthermore, we build an econometric model combining behavioural aspects with actual technology usage in a real application scenario.

Postharvest losses and mitigating technologies: evidence from Upper East Region of Ghana

Abstract Post-harvest losses (PHL) have been identified as a crucial challenge to achieving food and nutrition security in sub-Saharan Africa. Access to reliable data and standardized methods of estimating PHL are a twin barrier to developing long term mitigation options and policies to reduce PHL. This study assessed PHL in 6 districts of the Upper East Region of Ghana to facilitate planning and dissemination of mitigating strategies. The second part involved participatory evaluation of improved storage technologies to reduce PHL in two vulnerable crops (maize and cowpea). Overall, farmers’ declared PHL were higher across the crops compared to laboratory measurement. Crops recording higher PHL were in order of cowpea (17.3%), Bambara nut (11.5%), groundnut (8.9%) and maize (8.2%). By disseminating appropriate technologies to farmers, PHL were reduced to 3.1% from 36.7% in maize and 6.4% from 77.8% in cowpea during 12 months of storage. In spite of the high PHL, the respondents showed low technical and resource capabilities to minimize losses. Other factors contributing to PHL were the small-scale nature of production, and high cost of improved techniques tailored for same smallholders. Although the improved storage methods were associated with high variable costs, all the treatments showed positive stream of discounted net benefits .

Platform Sourcing Decisions in Ride-Hailing: Autonomous Vehicles vs. Human Drivers

We consider a ride-hailing platform with two supply sources: a fleet of autonomous vehicles (AVs) and a population of self-interested human drivers. The platform faces a tradeoff: while human drivers can have higher variable cost than AVs, they are only paid if used. Due to the interaction between wage, human driver participation level, and AV deployment quantity, the required wage is non-monotone. At first, as the human joining fraction increases, the prevailing wage decreases because the platform deploys fewer AVs, reducing competition. However, at larger human joining fractions, the wage increases and human-served rides become less profitable, so the platform increases its AV deployment quantity to compensate. The increased competition from AVs necessitates still higher wages and triggers a feedback loop or race to the top for the platform with itself, which limits human driver recruitment. Accordingly, access to a larger AV fleet can actually hurt the platform because it cannot credibly commit to a deployment quantity, and we show that the platform could indeed earn substantially more profit if it could pre-commit. Nevertheless, we prove that by appropriately adjusting the AV fleet size, the platform can achieve the same profit as with full commitment power.

Stochastic frontier analysis of catfish (Clarias gariepinus) aquaculture agribusiness for sustainable fisheries development: Evidence from Nigeria

Technical efficiency assessment and enhancement is critical to sustainable fisheries development in Nigeria. This study examines stochastic frontier of catfish aquaculture agribusiness for sustainable fisheries development. Purposive sampling technique was employed to select 110 catfish farmers in areas with high density catfish farms. Primary data were collected directly from catfish farmers using structured questionnaire. The analytical tools used were descriptive statistics, net farm income, stochastic frontier production function (SPF) and t-statistics. The result shows that most of the catfish farmers were young people within the productive age of 40-49 years. Catfish farmers had obtained various levels of formal education. Finding shows that feeds cost was the highest variable cost (72.75%). Feed had a positive and significant relationship (P<0.05) with catfish output. Mean technical efficiency is 53.49%. The estimated variance (δ2s=0.2125) is statistically significant (P<0.05), indicating that profit inefficiency is highly significant among catfish farmers. Estimated Gamma (γ) value of 0.26 implies that 26% of the total variation in catfish profit efficiency is due to the joint effect of technical inefficiency factors. The most significant efficiency factors are fish feed and pond size. The age and educational status of farmers are the most important determining factors of inefficiency in catfish production system. Lack of finance was the most serious constraint faced by catfish farmers. The study recommended that catfish farmers should form cooperative unions to facilitate their access to cooperative funding.

Impact of electric vehicles: Will German households pay less for electricity?

High energy efficiencies imply that electric mobility is regarded as an important technological option to reduce greenhouse gas emissions from the transport sector. However, electric vehicles (EVs) also have impacts on electricity grids and electricity generation. Hence, this paper explores how private EVs affect residential electricity prices in Germany. We examine effects of EVs on electricity generation, the contribution of controlled charging and impacts on distribution grid grids. We show that in 2030, private EVs can reduce the electricity prices for households since at distribution grid level, the additional electricity demand increases the overall utilisation of the grid and lowers specific costs. Because the additional load of EVs leads to an increased usage of power plants with higher variable costs, there is the opposite effect on electricity generation costs, although limited by controlled charging. Overall, the effect of rising electricity generation costs is usually overcompensated by falling specific grid charges.

Long Term Energy Storage in Highly Renewable Systems

Increasing penetrations of intermittent renewable energy generation introduce novel balancing and reliability challenges for electricity systems. Mismatches between renewable energy production and electricity demand cause periods of overgeneration and periods of undergeneration. These latter energy deficit periods will result in reliability challenges unless additional balancing solutions are employed. Energy deficits can range from a few hours to days to seasons to years. A least cost energy system will best meet these balancing challenges with diverse investments in energy infrastructure, depending on technology costs, natural resource availability, interconnectedness, and evolving load patterns, including flexible loads. Short-term and long-term storage applications may both be part of this portfolio. This study looks at storage in isolation to show the types of tradeoffs present between one storage resource and another in providing balancing services. The best storage technologies to balance the system depend on the duration of deficit events it is designed to mitigate. This paper compares the economics of different storage technology types in providing the range of short-term to long-term storage applications. The results compare quantities of conceptual storage technologies at different price points and quantities of clean gas generation to serve balancing needs as part of a least cost portfolio. We examine the tradeoffs between gas generation with low capital costs but high variable costs when burning clean fuels, and the alternative conceptual storage technologies, showing why clean gas capacity may play a role in least cost resource portfolios in decarbonized electricity systems.

Optimal Policies for Inventory Systems with Piecewise-Linear Concave Ordering Costs

We study infinite-horizon stochastic inventory problems with general demand distributions and piecewise linear concave ordering costs. Such costs arise in the important cases of quantity discounts or multiple suppliers. We consider the case of concave cost involving two linear segments. This corresponds to the case of one supplier with a fixed cost, a variable cost up to a given order quantity, and a quantity discount beyond that or, equivalently, the case of two suppliers, one with a low fixed cost along with a high variable cost and the other with a high fixed cost along with a low variable cost. We show that certain three and four parameter generalizations of the classical (s,S) policy are optimal. Our contributions consist of generalizing the demand, solving a functional Bellman equation for the value function that arises in the infinite-horizon framework, and providing an explicit solution in a special case of the exponential demand. We also give conditions under which our generalizations of the (s,S) policy reduce to the standard (s,S) policy. Finally and importantly, our method is also new in the sense that we construct explicitly the value function and we do not therefore need to utilize the notion of K-convexity used in the literature of inventory problems with fixed costs.

Cotton pests classification in field-based images using deep residual networks

Pests in agriculture are a major cause of losses in crops worldwide. Cotton is an important source of textile fiber, and insect pests and their management are the highest variable cost in cotton production. Identifying the most harmful cotton pests in field conditions helps acting for environmentally acceptable and yet economically effective strategies. This research proposes a classification system for major cotton pests (primary and secondary). A new ground-truth dataset containing RGB cotton field images is presented, along with a novel deep residual learning design to classify major pests automatically from given images. Performance is evaluated against other convolutional neural networks and the proposed ResNet34∗ model achieved the highest accuracy with f-score of 0.98.

Cost and Return of Selling Processed Sunflower Versus Unprocessed Sunflower by Smallholder Farmers in Dodoma Region, Tanzania

This research assessed the motivation of farmers to sell sunflower oil and in seed form and its effects on profitability. Data was collected through survey of 194 smallholder farmers in Dodoma region. The gross margin model was used to analyze profitability and was compared using the difference of mean test between households that sell oil and those who sell in seed form. Tobit Regression Model was used to analyze the factors that affect the proportion of sunflower sold as seeds. Results show that, higher variable costs were observed to farmers who processing sunflower; but higher gross margins were observed to farmers who process sunflower. This implied that farmers selling sunflower oil are more profitable than those farmers selling in seed form. Sunflower oil price, amount of sunflower harvested, size of household, farmer groups have significant and positive relationships with the proportion of sunflower sold as seed. The distance to the nearest machine is negatively and significantly associated with the proportion of sunflower sold as seed. Farmers should be encouraged to process sunflower before sale through training and extension. Access to yield-enhancing inputs, marketing or processing in groups, private entrepreneurs set up processing plants closer to farmers, invest mobile processing through improvement of the rural road network are some interventions proposed in this study to help farmers reduce transactions costs of processing.

PENAMBAHAN PROBIOTIK LACTOBACILLUS ACIDOPHILUS DAN BIFIDOBACTERIUM SP TERHADAP ANALISIS USAHA AYAM PETELUR YANG DIINFEKSI ESCHERICHIA COLI

The purpose of this study was to determine the use of probiotics Lactobacillus acidophilus and Bifidobacterium sp on variable cost, income and profit layers hens was infected with Escherichia coli. About 120 layers at 25 weeks of age were randomized into six treatments. The treatment consisted of factors a (infection and non-infection Escherichia coli) and factor b (basal feed, AGP and probiotics). The results of the study gave probiotics an effect (p 0.05) on variable cost. There was interaction between probiotic and infection factors (p 0.05) between probiotic and infection factors on variable cost. The highest variable cost was found in the treatment of non-infectious probiotics is Rp 13.594, the highest income was treated with non-infectious probiotics is Rp 26.564, the highest profit was treated with non-infectious probiotics is Rp 12.969. It could be concluded that the administration of probiotics can produce good production performance.