Farm Net Profit Research Articles

Modeling the economic impacts of mobility scores in dairy cows under Irish spring pasture-based management

Moderate to severe forms of suboptimal mobility on dairy cows are associated with yield losses, whereas mild forms of suboptimal mobility are associated with elevated somatic cell count and an increased risk to be culled. Although the economic consequences of severe forms of suboptimal mobility (also referred as clinical lameness) have been studied extensively, the mild forms are generally ignored. Therefore, the aim of the current study was to determine the economic consequences associated with varying prevalence and forms of suboptimal mobility within spring calving, pasture-based dairy herds. A new submodel predicting mobility scores was developed and integrated within an existing pastured-based herd dynamic model. Using a daily timestep, this model simulates claw disorders, and the consequent mobility score of individual cows. The impact of a cow having varying forms of suboptimal mobility on production and reproduction was simulated. The economic impact was simulated including treatment costs, as well as the production and reproductive impacts of varying levels of suboptimal mobility. Furthermore, different genetic predispositions for mobility issues and their interaction with herd-level management associated with each level of suboptimal mobility were simulated. Overall, 13 scenarios were simulated, representing a typical spring calving, pasture-based dairy herd with 100 cows. The first scenario represents a perfect herd wherein 100% of the cows had mobility score 0 (optimal mobility) throughout the lactation. The remaining 12 scenarios represent a combination of (1) 3 different herd-management levels, and (2) 4 different levels of a genetic predisposition for suboptimal mobility. The analysis showed that a 17% decrease in farm net profit was achieved in the worst outcome (wherein just 5% of the herd had optimal mobility) compared with the perfect herd. This was due to reduced milk yield, increased culling, and increased treatment costs for mobility issues compared the ideal scenario.

Profitability Analysis of Plantain Production in Ondo East Local Government Area of Ondo State, Nigeria

The study looked into the profitability of plantain production in Ondo East Local Government Area of Ondo State, Nigeria. Although it is grown by smallholders in the study area, there were great potentials for the crop in that all parameters showed that it was profitable. The Gross Margin (GM) per hectare was 360536 Naira while the Net Farm Income or Profit was 288413 Naira per hectare. The Benefit Cost Ratio was 2.28 and Return on Investment was 1.28. Findings showed that respondents were mostly males, married, averagely educated and fell within economic viable age range. Most farmers planted Agbagba (87.5%) which is said to be the most dominant and much sought after by consumers, got their planting materials from previous year production (62.5%) and practiced de-suckering. Age, family size, farm size and plantain sole cropping had positive impact on the Net Farm Income of the respondents, while they had the problems of inadequate funding and lack of extension agents. The study concluded that there was the need for policy makers to consider and make adequate policy preparations for plantain so that Nigeria can join other plantain exporting nations and that the crop can earn the ever scarce foreign exchange for Nigeria.

Economic impact of different strategies to use sex-sorted sperm for reproductive management in seasonal-calving, pasture-based dairy herds

To maximize efficiency, profitability, and societal acceptance of modern dairy production, it is important to minimize the production of male dairy calves with poor beef merit. One solution involves using sex-sorted sperm (SS) to generate dairy replacements and breeding all other cows to an easy-calving, short-gestation bull with good beef merit. We used the Pasture Based Herd Dynamic Milk Model to investigate the effect of herd fertility and use of SS on farm net profit in a herd of 100 cows. This was completed by simulating herds with differing fertility performance (good, average, poor), and differing farm reproductive management [conventional semen (CONV) or SS with varying pregnancy per artificial insemination (P/AI) relative to CONV (i.e., relative P/AI 100%, 85%, and 70%)]. As an additional consideration, the method of allocating SS to cows was also examined. The first option used SS on random heifers and cows (S). The second option used SS on heifers and targeted high-fertility cows (SSel). The final option was similar to SSel, but used a fixed-time artificial insemination (AI) protocol to facilitate AI on the farm mating start date (SSync). For CONV, dairy breed semen was used for AI until 50 animals were pregnant (50% chance of a female calf), whereas for S, SSel, or SSync the target number of animals successfully conceiving with SS was set at 28 (based on assumed 90% chance of a female calf from pregnancies derived from SS). Beef breed semen was used on all other dams. The results indicated that the biggest effect on farm net profit was not based on whether or not SS was used, but instead was most affected by the overall fertility performance of the herd. Total farm profit decreased by 10% between the good and average fertility herds, and decreased by a further 12% between the average and poor fertility herds. In almost all situations, when the relative P/AI with SS was ≥85%, use of SS led to an overall increase of the farm net profit. There was an economic benefit of using either SSel or SSync compared with S for the average and poor fertility herds but not for the good fertility herd, highlighting an interaction between SS P/AI and overall herd fertility as well as management practices. If the relative P/AI with SS was <70%, the use of SS led to a decrease in profitability in all simulations except for SSync, highlighting the importance of a good management strategy for use of SS. The findings in this study indicated that SS has significant potential to help facilitate greater integration between the dairy and beef production sectors, as well as increase farm profitability when used appropriately.

Assessing the Effect of Modifying Milking Routines on Dairy Farm Economic and Environmental Performance

The objective of this paper was to quantify the economic and environmental effects of changing a dairy farm’s milking start times. Changing morning and evening milking start times could reduce both electricity costs and farm electricity related CO2 emissions. However, this may also involve altering farmer routines which are based on practical considerations. Hence, these changes need to be quantified both in terms of profit/emissions and in terms of how far these milking start times deviate from normal operations. The method presented in this paper optimized the combination of dairy farm infrastructure setup and morning and evening milking start times, based on a weighting variable (α) which assigned relative importance to labor utilization, farm net profit and farm electricity related CO2 emissions. Multi-objective optimization was utilized to assess trade-offs between labor utilization and net profit, as well as labor utilization and electricity related CO2 emissions. For a case study involving a 195 cow Irish dairy farm, when the relative importance of maximizing farm net profit or minimizing farm electricity related CO2 emissions was high, the least common milking start times (06:00 and 20:00) were selected. When the relative importance of labor utilization was high, the most common milking start times (07:00 and 17:00) were selected. The 195 cow farm saved €137 per annum when milking start times were changed from the most common to the least common. Reductions in electricity related CO2 emissions were also seen when the milking start times were changed from most common to least common. However, this reduction in emissions was primarily due to the addition of efficient and renewable technology to the farm. It was deduced that the monetary and environmental benefits of altering farmer milking routines were unlikely to change normal farm operating procedures.

Financial benchmarking on dairy farms: Exploring the relationship between frequency of use and farm performance

The importance of financial benchmarking has increased in recent years as European Union milk quota abolition has facilitated rapid change in the dairy sector. This study evaluates the association between usage frequency of a financial benchmarking tool [Profit Monitor (PM)] and farm changes on spring-calving pasture-based dairy farms. To this end, physical and financial data for 5,945 dairy farms, representing 20,132 farm years, for the years 2010 to 2018 were used. Farms were categorized by frequency of annual financial benchmarking over the 9-yr period into frequent PM users (7-9 yr), infrequent PM users (4-6 yr), low PM users (1-3 yr), and nonusers. We use a mixed model framework and econometric models to characterize farms and to explore characteristics and determinants of economic performance and user groups. The most frequent users of the financial benchmarking tool had the greatest increase in intensification (measured by change in farm stocking rate), productivity (measured by change in milk production per hectare), and financial performance (measured by change in farm gross output and net profit per hectare) across the study period. Infrequent and low PM users of the benchmarking tool were intermediate for all variables measured, whereas nonusers had the least change. Empirical results indicated that economic performance was positively associated with dairy specialization and pasture utilization for all groups. Despite considerable fluctuations over the observation period, the overall change in total farm net profit between 2010 and 2018 was greatest for the frequent PM users (an increase of 70%, or €37,639), followed by farms in the infrequent PM user category (a 71% increase corresponding to an increase of €28,008 in net profit); meanwhile, low PM user and nonuser categories showed increases of 69% (€26,270) and 42% (€10,977), respectively. The results of this study also clearly indicated the existence of a strong positive association between frequency of financial benchmarking and greater technical and financial efficiency. The econometric analysis revealed that financial benchmarking users are more likely than nonusers to have larger herds, and that regional differences exist in usage rates. Finally, the study concludes by suggesting that the development of simplified financial benchmarking technologies and their support are required to increase benchmarking frequency, which may also help to facilitate a more sustainable and resource efficient dairy industry.

Financial Impacts of Liver Fluke on Livestock Farms Under Climate Change-A Farm Level Assessment.

Liver fluke infection (fascioliasis) is a parasitic disease which affects the health and welfare of ruminants. It is a concern for the livestock industry and is considered as a growing threat to the industry because changing climatic conditions are projected to be more favorable to increased frequency and intensity of liver fluke outbreaks. Recent reports highlighted that the incidence and geographic range of liver fluke has increased in the UK over the last decade and estimated to increase the average risk of liver fluke in the UK due to increasing temperature and rainfall. This paper explores financial impacts of the disease with and without climate change effects on Scottish livestock farms using a farm-level economic model. The model is based on farming system analysis and uses linear programming technique to maximize farm net profit within farm resources. Farm level data from a sample of 160 Scottish livestock farms is used under a no disease baseline scenario and two disease scenarios (with and without climate change). These two disease scenarios are compared with the baseline scenario to estimate the financial impact of the disease at farm levels. The results suggest a 12% reduction in net profit on an average dairy farm compared to 6% reduction on an average beef farm under standard disease conditions. The losses increase by 2-fold on a dairy farm and 6-fold on a beef farm when climate change effects are included with disease conditions on farms. There is a large variability within farm groups with profitable farms incurring relatively lesser economic losses than non-profitable farms. There is a substantial increase in number of vulnerable farms both in dairy (+20%) and beef farms (+27%) under the disease alongside climate change conditions.

Economic assessment of Holstein-Friesian dairy cows of divergent Economic Breeding Index evaluated under seasonal calving pasture-based management

The objective of this study was to investigate the economic performance of 2 genetic groups (GG) of Holstein-Friesian dairy cows of divergent Economic Breeding Index (EBI), evaluated within 3 contrasting spring-calving pasture-based feeding treatments (FT). The study was a simulated economic appraisal, using the Moorepark Dairy Systems Model, a stochastic budgetary simulation model integrating biological data obtained from a 4-yr experiment conducted from 2013 to 2016. The 2 divergent GG were (1) high EBI representative of the top 5% nationally (elite) and (2) EBI representative of the national average (NA). The 3 FT were reflective of slight restriction to generous feeding. The elite GG had the lowest replacement rate, and therefore had lower replacement costs and an older and more productive parity structure. The elite GG consistently had higher sales of milk (on average +3% or +18,370 kg of milk) and milk solids (milk fat plus protein yield; +8.7% or +4,520 kg) compared with the NA GG across the 3 FT scenarios. Milk income was consequently greater for elite versus NA (on average +9.5% or +€21,489) cows. Livestock sales were greater (on average +13.2% or +€4,715) for NA compared with elite cows. Baseline net farm profit and net profit/ha at a base milk price of 29.5 cents per liter (3.3% protein and 3.6% fat) were on average €31,156, and €772 greater for elite compared with NA cows across the 3 FT. Greater profitability achieved with elite cows in each of the FT investigated demonstrated the adaptability of high-EBI cows across different levels of feeding intensities in seasonal pasture-based feeding systems. Sensitivity analysis of varying milk price and concentrate cost did not result in a reranking of GG for farm profit. This study clearly demonstrates the power of a suitably constructed genetic-selection index together with a well-considered breeding program to deliver genetics capable of favorable change to farm physical performance and profit over a relatively short duration.

Photovoltaic systems on dairy farms: Financial and renewable multi-objective optimization (FARMOO) analysis

The aim of this study was to develop a financial and renewable multi-objective optimization (FARMOO) method for dairy farms. Due to increased global milk production and European Union policies concerning renewable energy contributions, the optimization of dairy farms from financial and renewable standpoints is crucial. The FARMOO method found the optimal combination of dairy farm equipment and management practices, based on a trade-off parameter which quantified the relative importance of maximizing farm net profit and maximizing farm renewable contribution. A PV system model was developed and validated to assess the financial performance and renewable contribution of this technology in a dairy farming context. Seven PV system sizes were investigated, ranging from 2 kWp to 11 kWp. Multi-objective optimization using a Genetic Algorithm was implemented to find the optimal combination of equipment and management practices based on the aforementioned trade-off parameter. For a test case of a 195 cow spring calving dairy farm in Ireland, it was found that when the relative importance of farm net profit was high, a PV system was not included in the optimal farm configuration. When net profit and renewable contribution were of equal importance, the optimal farm configuration included an 11 kWp PV system with a scheduled water heating load at 10:00. Multi-objective optimization was carried out for the same test case with the goals of maximizing farm net profit and minimizing farm CO2 emissions. Under this scenario, the optimal farm configuration included an 11 kWp PV system when the relative importance of farm net profit was low. This study included a sensitivity analysis which investigated the use of a 40% grant aid on PV system capital costs. This sensitivity analysis did not significantly improve the financial feasibility of PV systems on dairy farms. Moreover, it was found that load shifting of a farm’s water heating enabled the majority of the PV system’s electricity output to be consumed. Hence the use of batteries with small PV systems on dairy farms may not be necessary. The method described in this study will be used to inform policy and provide decision support relating to PV systems on dairy farms.

ASSESSMENT OF TOMATO FARMERS’ IRRIGATION PRACTICE IN PAMPAIDA MILLENNIUM VILLAGE, IKARA LOCAL GOVERNMENT AREA, KADUNA STATE, NIGERIA

This study was conducted in Pampaida Millennium Village (PMV), Ikara Local Government Area of Kaduna State, Nigeria; during the 2009/2010 dry season to assess Tomato farmer’s irrigation water management practice using furrow irrigation. A total of 7 tomato farmers were selected out of 45 farmers for the assessment exercise. Soil moisture content was monitored throughout the growing season using gypsum blocks. The hydraulic performance of the farmer’s plots were assessed. Similarly, the seasonal water requirement and irrigation schedule for the irrigated tomato were also determined. The results showed that the highest Application Efficiency, Distribution Uniformity and Adequacy of irrigation were obtained in plots T6 (92%), T3 (89%) and T7 (92 %) respectively. The least AE, DU and AI were obtained in plot T1 as 74%, 72% and 63% respectively. The yield obtained ranged from 11.6t/ha to 22.3t/ha. The least yield was obtained in plot T2; while the highest yield was obtained in plot T1. All the assessed farmers maintained a 4day irrigation interval throughout the growing season. The highest crop water use efficiency (CWUE) of 62.80 kg/ha-mm was obtained in plot T1, with a corresponding crop water use (CWU) of 355 mm/season. The least CWUE was obtained in plot T2 (41.6kg/ha-mm) with a corresponding CWU of 399 mm/season. Based on the results obtained it can be deduced that plot T1 gives best results among the assessed farmers’ plots in terms of crop water use efficiency and effectiveness of irrigation, which maximizes net farm profit.

Dairy expansion: a case study of spring-calving pasture-based dairy production systems in Ireland

AbstractSince 1 April 2015, European dairy milk quotas have been removed resulting in the intensification of dairy production within EU countries. The aim of this study was to evaluate the physical and economic impacts of the initial intensification undertaken within Irish grazing dairy systems. Physical and financial data for 868 seasonal calving dairy farmers with records for each of the years 2013–2017 inclusive were used in this analysis. All analyses were undertaken using a mixed-model framework in PROC MIXED. The overall level of fat plus protein productivity of studied farms increased by 51% during the 5-year period through a combination of increased production per cow, increased operational scale and system intensification. Overall farm net profit was highly variable between years and was greatest in 2017 (€133 836) and least in 2016 (€65 176). When farms were characterized into milk production expansion quartiles, farms in Q1, Q2, Q3 and Q4 increased output by +7, +25, +44 and +86%, respectively. Whereas total farm profit (€/farm) declined for Q1 farms between 2013/2014 and 2016/2017 (€−5257; −7%), the greater expansion undertaken in Q2, Q3 and Q4 resulted in increases of €3046 (+4%), €20 810 (+25%) and €51 604 (+62%), respectively. In all strategies studied, farm profit increased due to a combination of increased revenues, increased pasture utilization and a dilution of per unit production costs. Further investigation of the longer term impacts of expansion is merited, not just in terms of economic indicators, but also in terms of environmental and socio-cultural change.

Timeliness affect the Net Farm Profit

Timeliness is very important in large agricultural projects, which are characterized by large areas requiring different numbers and sizes of agricultural equipment. In order to choose the best equipment, and give the right management decisions. The intelligent manager must be aware of the optimum planting time, because the varying in the time of planting on sawing date leads to loss of productivity called (Timeliness) may reach about half of the crop.Determining the optimum time for planting is important to reduce the costs of declining yield due to timeliness and to obtain the highest yield from the farm.This research aims to cover these point machine sizes and operational available time affected the crop net return. Timeliness coefficients’ equation was adjusted for famous Egyptian crops, for maximum crop yield to avoid the early or late establishment crop yield losses.

Economic and food security effects of small-scale irrigation technologies in northern Ghana

Abstract Small-scale irrigation (SSI) technologies can be useful not only to increase crop productivity and income but also as a viable adaptation practice to climate variability. A farm simulation model (FARMSIM) and data from selected SSI technologies piloted in northern Ghana under the ‘Feed the Future-Innovation Lab for Small Scale Irrigation’ (ILSSI) project were used to assess the economic feasibility of the SSI technologies and their potential to improve income and nutrition of smallholder farm households. Three dry season irrigated crops (onion, corchorus, amaranthus) grown under three agricultural water management regimes were analysed. Results show that adoption of the SSI technologies could increase the net farm profit by 154%–608% against the baseline depending on the ‘crop type - SSI technology’ combination. Nutrition levels also improved significantly as a result of the improvements in crop yields due to irrigation and use of complementary inputs. However, the results further reveal that the options that utilize capital-intensive SSI technologies such as solar-powered water pumps to grow high value cash crops are constrained by the high investment cost. Currently, farmers tend to choose low-cost SSI technologies such as a traditional watering-cans, which generate low economic returns. Improving access to credit or alternative financing schemes could mitigate the capital constraints and enable smallholders to gain more benefits from participating in market-oriented high-value irrigated production.

Financial Vulnerability of Dairy Farms Challenged by Johne's Disease to Changes in Farm Payment Support.

Johne's disease is an endemic contagious bacterial infection of ruminants which is prevalent in the United Kingdom and elsewhere. It can lower financial returns on infected farms by reducing farm productivity through output losses and control expenditures. A farm-level analysis of the economics of the disease was conducted taking account of farm variability and different disease prevalence levels. The aim was to assess the financial impacts of a livestock disease on farms and determine their financial vulnerability if farm support payments were to be removed under future policy reforms. A farm-level optimization model, ScotFarm, was used on 50 Scottish dairy farms taken from the Farm Business Survey to determine the impacts of the disease. A counterfactual comparison of five alternative “disease” scenarios with a “no-disease” scenario was carried out to evaluate economic impact of the disease. The extent of a farm's reliance on direct support payments was considered to be an indicator of their financial vulnerability. Under this definition, farms were grouped into three financial vulnerability risk categories; “low risk,” “medium risk,” and “high risk” farms. Results show that farms are estimated to incur a loss of 32% on average of their net profit under a standard disease prevalence level. Farms in the “low risk” and “medium risk” categories were estimated to have a lower financial impact of the disease (22 and 28% reduction on farm net profit, respectively) which, along with their lower reliance on farm direct support payments, indicate they would be more resilient to the disease under future changes in farm payment support. On the contrary, farms in the “high risk” category were estimated to have a reduction of 50% on their farm net profit. A majority of these farms (61%) in the “high risk” category move from being profitable to loss making under the standard disease scenario when farm support payments are removed. Of these, 15% do so because of the impact of the disease. These farms will be more vulnerable if changes were to be made in farm support payments under future agricultural policy reforms.

Grass-Legume Mixtures for Improved Soil Health in Cultivated Agroecosystem

Planting grass-legume mixtures may be a good option to improve soil health in addition to increased forage productivity, improved forage nutritive value, and net farm profit in a hay production system. A field experiment was conducted from 2011 to 2014 at Lingle, Wyoming to evaluate soil microbial biomass under different seeding proportions of two forage grasses (meadow bromegrass, Bromus biebersteinii Roem. &amp; Schult.; and orchardgrass, Dactylis glomerata L.) and one legume (alfalfa, Medicago sativa L.). Nine treatments included monoculture grass, monoculture legume, one grass and one legume mixture, two grasses and one legume mixture, and a control (not seeded with grass or legume). Monoculture grass received either no nitrogen (N) or N fertilizer (150 kg N ha−1 year−1 as urea) whereas monoculture legume, grass-legume mixtures, and control plots received no N fertilizer. The study was laid out as a randomized complete block design with three replications. The plots were harvested 3–4 times each year after the establishment year. Soil samples were collected and analyzed for microbial biomass using phospholipid fatty acid (PLFA) analysis at the end of May in 2013 and 2014. Soil samples were also analyzed for mineralizable carbon (C) and N in 2013 and 2014. The total above-ground plant biomass was higher in 50–50% mixture of grass and alfalfa than monoculture alfalfa and monoculture grass (with and without N fertilizer) during the entire study period. The application of N fertilizer to the grass hay production system had little effect on improving mineralizable soil C, N, and soil microbial biomass. However, grass-legume mixture without N fertilizer had great effect on improvement of mineralizable soil C and N, and total, bacterial, and actinomycetes microbial biomass in soil. The 50–50% mixture of grass and alfalfa performed consistently well and can be considered to use in Wyoming conditions for improving soil health and forage productivity.

Profitability analysis of paddy production: A case of agricultural zone 1, Niger State Nigeria

This study estimated the profitability of rice production among small scale farmers in Bida agricultural zone of Niger state. The study utilized a multi-stage random sampling technique to select a total of one hundred and five (105) rice farmers in the area. The data was collected through a well-structured questionnaire from four communities in the study area. Descriptive statistics and farm budgeting tools were used for the analyses. The descriptive analysis showed that the farmers are highly productive between the age range of 37- 48 years. Furthermore, results also revealed land area cultivated by the farmers to be generally below two hectares. The finding further revealed the variable cost per hectare for rice production to be $126,100 per production cycle, while total revenue of $227,500 was realized by the respondents. The results also revealed cost of labour to account for the largest portion (54.0%) of the total variable cost. This is followed by the cost of seed, fertilizer, transportation, herbicide, pesticide and bagging. The farm budgeting analysis revealed the costs and returns of rice production to be profitable with a gross margin of $101,400 and net farm profit of $98,546.4. The gross profit ratio was calculated to be 0.45 which implies that farmers are selling their rice produce at a relatively high profit percentage. Based on the results obtained from the study, it was concluded that rice production in Bida Agricultural Zone of Niger State is profitable. Hence, the cultivation of rice is an important enterprise that should be encourage, considering the fact that it is a major staple. It is therefore recommended that timely availability of farm inputs such as improved seed variety and agrochemicals will further boos trice production in the area. Furthermore, provision of credit facilities to small scale farmers is a viable policy to be pursuedJ. Bangladesh Agril. Univ. 16(1): 88-92, April 2018

Factors associated with profitability in pasture-based systems of milk production

The global dairy industry needs to reappraise the systems of milk production that are operated at farm level with specific focus on enhancing technical efficiency and competitiveness of the sector. The objective of this study was to quantify the factors associated with costs of production, profitability, and pasture use, and the effects of pasture use on financial performance of dairy farms using an internationally recognized representative database over an 8-yr period (2008 to 2015) on pasture-based systems. To examine the associated effects of several farm system and management variables on specific performance measures, a series of multiple regression models were developed. Factors evaluated included pasture use [kg of dry matter/ha and stocking rate (livestock units/ha)], grazing season length, breeding season length, milk recording, herd size, dairy farm size (ha), farmer age, discussion group membership, proportion of purchased feed, protein %, fat %, kg of milk fat and protein per cow, kg of milk fat and protein per hectare, and capital investment in machinery, livestock, and buildings. Multiple regression analysis demonstrated costs of production per hectare differed by year, geographical location, soil type, level of pasture use, proportion of purchased feed, protein %, kg of fat and protein per cow, dairy farm size, breeding season length, and capital investment in machinery, livestock, and buildings per cow. The results of the analysis revealed that farm net profit per hectare was associated with pasture use per hectare, year, location, soil type, grazing season length, proportion of purchased feed, protein %, kg of fat and protein per cow, dairy farm size, and capital investment in machinery and buildings per cow. Pasture use per hectare was associated with year, location, soil type, stocking rate, dairy farm size, fat %, protein %, kg of fat and protein per cow, farmer age, capital investment in machinery and buildings per cow, breeding season length, and discussion group membership. On average, over the 8-yr period, each additional tonne of pasture dry matter used increased gross profit by €278 and net profit by €173 on dairy farms. Conversely, a 10% increase in the proportion of purchased feed in the diet resulted in a reduction in net profit per hectare by €97 and net profit by €207 per tonne of fat and protein. Results from this study, albeit in a quota limited environment, have demonstrated that the profitability of pasture-based dairy systems is significantly associated with the proportion of pasture used at the farm level, being cognizant of the levels of purchased feed.

Herd-specific interventions to reduce antimicrobial usage in pig production without jeopardising technical and economic performance

Pig farmers are strongly encouraged to reduce their antimicrobial usage in order to reduce the risk of antimicrobial resistance. Herd-level intervention is needed to achieve national and European reduction targets. Alternative, especially preventive measures, have to be implemented to reduce the need for antimicrobial treatments. However, little is known about the feasibility, effectiveness and return on investment of such measures. The objective of this study was to assess, across four countries, the technical and economic impact of herd-specific interventions aiming at reducing antimicrobial usage in pig production while implementing alternative measures.An intervention study was conducted between February 2014 and August 2015 in 70 farrow-to-finish pig farms located in Belgium, France, Germany and Sweden. Herd-specific interventions were defined together with the farmer and the herd veterinarian. Farms were followed over one year and their antimicrobial usage and technical performance were compared with values from the year before intervention. Compliance with the intervention plan was also monitored. Changes in margin over feed cost and net farm profit were estimated in a subset of 33 Belgian and French farms with sufficient data, using deterministic and stochastic modeling.Following interventions, a substantial reduction in antimicrobial use was achieved without negative impact the overall farm technical performance. A median reduction of 47.0% of antimicrobial usage was achieved across four countries when expressed in terms of treatment incidence from birth to slaughter, corresponding to a 30.5% median reduction of antimicrobial expenditures. Farm compliance with intervention plans was high (median: 93%; min-max: 20; 100) and farms with higher compliance tended to achieve bigger reduction (ρ=-0.18, p=0.162). No association was found between achieved reduction and type or number of alternative measures implemented. Mortality in suckling piglets, weaners and fatteners, daily weight gain and feed conversion ratio did not significantly change over the course of the study, while the number of weaned piglets per sow per year slightly increased. The median change in net farm profit among Belgian and French farms was estimated to be €4.46 (Q25-Q75:-32.54; 80.50) and €1.23 (Q25-Q75:-32.55; 74.45) per sow per year using the detererministic and stochastic models, respectively. It was more influenced by a change in feed conversion ratio and daily weight gain than by a change in antimicrobial expenditures or intervention direct net cost. Therefore, costs of alternative measures should not be perceived as a barrier, but rather as an opportunity to optimise production practices for sustained productivity and improved animal health.

Controlled Release Urea Improved Nitrogen Use Efficiency and Yield of Wheat and Corn

Nitrogen fertilizer is important for improving wheat (Triticum aestivum L.) and corn (Zea mays L.) yields, but inappropriate application methods and excessive amounts lead to low N use efficiency and high N losses through leaching. To investigate the effects of controlled‐release urea (CRU) on crop yield and soil fertility, a field experiment was conducted from 2012 to 2014 in China. The 100% (180 kg ha−1) and 70% (126 kg ha−1) of the local practice N rates with CRU and urea were used. The results revealed that the release curves of CRU in the natural field corresponded well to the N requirements of wheat and corn plants, and a positive linear correlation was observed between release rates and days after buried in soil. Consequently, the CRU treatments achieved significantly higher wheat and corn yield by 8 to 12% and 9 to 11%, respectively, compared with urea treatments at the same N rate. Reducing N rate of CRU by 30% produced the same yield as with the 100% N rate of urea. The agronomic nitrogen use efficiency (NUE) was significantly increased and the leaching of soil N was reduced by CRU. The acidification rates and leaching of exchangeable Ca2+, K+, Na+ contents were reduced, base saturation and available P improved by application of CRU compared with urea. Therefore, the results suggested that a 30% decrease of CRU in the recommended application rate of N, can be an effective measure to save consumption input of N fertilizer.Core Ideas Nitrogen release rates of controlled‐release urea in field condition corresponded well to the N uptake of crop plants. A 30% decrease in the application rate of N is possible with controlled‐release urea compared to urea. The application of controlled‐release urea increased crop yield, N use efficiency, net farm profit, and soil fertility.

Extreme learning approach with wavelet transform function for forecasting wind turbine wake effect to improve wind farm efficiency

A wind turbine operating in the wake of another turbine and has a reduced power production because of a lower wind speed after rotor. The flow field in the wake behind the first row turbines is characterized by a significant deficit in wind velocity and increased levels of turbulence intensity. To maximize the wind farm net profit, the number of turbines installed in the wind farm should be different in depend on wind farm project investment parameters. Therefore modeling wake effect is necessary because it has a great influence on the actual energy output of a wind farm. In this paper, the extreme learning machine (ELM) coupled with wavelet transform (ELM-WAVELET) is used for the prediction of wind turbine wake effect in wind far. Estimation and prediction results of ELM-WAVELET model are compared with the ELM, genetic programming (GP), support vector machine (SVM) and artificial neural network (ANN) models. The following error and correlation functions are applied to evaluate the proposed models: Root Mean Square Error (RMSE), Coefficient of Determination (R2) and Pearson coefficient (r). The experimental results show that an improvement in predictive accuracy and capability of generalization can be achieved by ELM-WAVELET approach (RMSE=0.269) in comparison with the ELM (RMSE=0.27), SVM (RMSE=0.432), ANN (RMSE=0.432) and GP model (RMSE=0.433).

Determinants of informal credit delinquency among food crop farmers in rural niger delta of Nigeria

The study examined the determinants of informal credit delinquencies among food crop farmers in rural Niger Delta of Nigeria using Akwa Ibom State as a case study. A multi-stage random sampling technique was adopted to select 96 beneficiaries and structured questionnaires as well as personal interview were used to collect data. Probit and logit models were used to analyse the factors influencing credit delinquency among food crop farmers in the state. Result of the descriptive analysis of the socio-economic characteristic of respondents revealed that 93% of male and 72% of female food crop farmers had one form of formal education ranging from primary to tertiary education. Empirical result from the Probit and logit models were similar and showed that borrower’s non-farm income, credit amount received, household size, net farm profit and farm size are determinants of credit delinquencies among food crop farmers in Akwa Ibom state. The study also discovered that the probability of food crop farmers being credit delinquent is about 0.427 ceteris paribus. It is recommended that food crop farmers should form marketing co-operative societies as a means of generating additional income to augment loan obtained. Furthermore, local government authorities should set up credit programmes that should focus on soft loans to rural farmers at a subsidize interest rate.