Organic farming at the farm level - Scenarioes for the future development

The purpose of this report is to present possible impacts of new technology and changes in legislation on the profitability of different types of organic farms. The aim is also to look at both the current and future trends in the organic area in Denmark. Besides the economic aspects, the report also shows the nutrient surplus for selected organic farms. Analyses carried out at the Food and Resource Economic Institute (FOI) have previ-ously shown that price premiums of up to 50% on pig meat and 20% on arable farm products is needed to make the organic production profitable. The price premium on cereals and dairy products have in the 1990’ties been higher than required, but in re-cent years the price premium has dropped, leading to low profitability, especially on arable farms. The organic farms in Denmark consist mainly of two types of farms, full time dairy farms and part time arable farms. The dairy farms constitute 25% of the farms, 50% of the area and they have 80% of the livestock units. The part-time arable farms con-stitute 60% of the farms, 28% of the organic area and they have 5% of the livestock units. Previous predictions made by FOI regarding more part-time farms converting to organic farming have been fulfilled, whereas the conversion to organic pig production has been much lower than expected. Both dairy and arable farms are facing new threats as the organic milk production is still much higher than the consumption, and as the profitability on small arable farms is low. The aim of the project is, therefore, to look at the impact of new technology on the profitability of organic farming. As organic farming in Denmark has experienced leg-islative changes leading to lower use of imported feedstuffs, it was also an aim to look at the impact of legislative changes, allowing only 100% organic feed, straw and ma-nure. To analyse this eight case farms were selected as typical organic farms. They con-sisted of 3 dairy farms, 4 arable farms and 1 pig farm. The area and the production on these case farms were based on interviews with local consultants, but they are not ac-tual farms found in Denmark. The intension was to present the typical future organic farm in terms of size, area and crop rotation. The yields and the machinery on these farms were determined in close co-operation with researchers at Danish Institute of Agricultural Sciences (Bygholm). The analyses regarding the profit shows on case farms a profit on the dairy and pig farms and a negative result on the arable case farms. This is comparable with net prof-its found nationally on organic farms in 2002. The capital invested in machinery on case farms is lower than found on actual organic farms due to the optimization proce-dure used to find the right level of machinery. The analyses also show that there does not seem to be significant differences in the machinery costs between conventional and organic farms. The analysis is based on 16 organic and 14 conventional study farms, which makes costs comparable. The ma-chinery costs on the case farms are in line with machinery costs on organic study farms, where most farms have costs between 3,000 and 7,000 DKK per ha (100 DKK = 13.4 €). The impact of new technology is analysed, focusing on the technologies which are found to be available in the near future and where the first trials look promising. The technologies analysed include robotic weeding, band streaming before sowing, use of GPS when applying animal manure and automatic milking using a robot. Both weed management technologies are found to be profitable and to be recommended for fur-ther development. The purpose is to remove weeds inside the row. GPS might give some economic benefits, but will be more profitable in a scenario with restrictions on nitrogen use. More trials have to be conducted to determine whether GPS is profit-able. Automatic milking is not a technology exclusive to the organic sector. The analyses show that if the capacity is well used it might be profitable. As a whole, the technologies do not seem to have a major impact on the future development in the or-ganic sector as the focus is on relatively specialised crops which cover a small area. For the technologies which can be used more widely, the improvement in income is limited. The difference between organic production and conventional farming has diminished over recent years as conventional farmers use less pesticide and mineral fertiliser. Furthermore, the European rules for organic farming might change. The possible im-pact of changes in legislation has, therefore, been analysed. The changes include the following restrictions: • 100% organic feed (requirement from 2005 on dairy farms) • 100% organic straw (no import of conventional straw) • 100% organic manure (no import of conventional manure) 100% organic feed has already been introduced for dairy farms in Denmark, whereas for pig farms it will increase feed costs by 10-17%, but the production will still be profitable. Using 100% organic straw will increase income on arable farms a little and lower the income on livestock farms with few cereal crop areas. The 100% organic manure scenario will reduce the manure (slurry and farm yard ma-nure) used in the organic sector by approximately 20% and increase the price from 5 to approximately 10 DKK per kg N. The effect is a decrease in application of 10 kg effective N per ha. The analyses show that dairy farms will increase their export and apply less than today, whereas arable farms will only reduce their N application a lit-tle. The loss in income among the arable farms is, in the calculation, almost the same as the gains made by the dairy farms, as the yield reductions are limited. However, in the analyses, it is expected that arable farms already today pay for manure imports, which is often not the case. This implies that the costs for organic arable farms found in this analysis under estimate the actual costs. This will also make it more difficult for con-ventional farms to export their manure. Another assumption is that transportation costs are minimal. However, this legislation will imply transportation of manure from livestock intensive areas to arable areas. The total cost of this is roughly estimated at 10-13 million DKK or 700-1,000 DKK per ha for the arable farms in Zealand which receive the manure. Alternatively, the arable farms would have to either have their own livestock or farm without the use of animal manure. The conclusion is that such a legislation will reduce the income on arable farms and increase the income on dairy farms and that it would lead to a change in the regional distribution of farms as livestock and arable farms would have to be located close to each other to reduce transportation costs. For dairy and arable farms located close to each other, such legislation would not necessarily lead to much lower profit for the farms seen as a whole as the animal manure might be utilised bet-ter. Whether the prices for agricultural products could increase in case where they are 100% organic, is questionable and is, therefore, not included in the calculation. In the last chapter, the nutrient balance is estimated on the case farms in the baseline and with a 100% organic manure scenario. The nutrient balance in the baseline shows a nitrogen surplus of 47-110 kg N per ha. The most difficult input to estimate is the N-fixation, which varies with yield and application of animal manure. The case farms have a phosphorus (P) surplus of around zero. For potassium (K) some farms have a surplus others a deficit of up to 90 kg K per ha. In the 100% organic manure scenario, the lower manure application affects the sur-plus more than the slightly lower yields, leading to lower N-surplus, P deficit and lar-ger K deficit than in the baseline scenario. It should be noted that attempts in terms of applying other P and K sources have not been included. The final chapter deals with conclusions and perspectives on the future of organic farming at the farm level. For the dairy farms, there needs to be a better balance be-tween production and demand. This will probably lead to a reduction in the amount of milk which is given the price premium by 30-40%. In the case where these farms stop as organic farms they will reduce the organic area by 30,000 ha. The organic area could therefore be reduced to 130,000 ha. With the lower organic area it is not likely that the organic milk production will exceed 10% of the total Danish milk production. However, it is also likely that farms which stop organic production will continue with an environmentally friendly production not using pesticides and with a limit on the nitrogen application. Many organic farmers have, over the years, come to appreciate this type of production. So although some might change back to conventional farm-ing, they will still use less pesticides than conventional farmers and use the crop rota-tion more actively in order to reduce N-leaching. A smaller organic dairy sector will make the 100% organic manure scenario more costly as the amount of organic ma-nure is lower. The small part time arable farms will probably carry on as the main income comes from outside farming. The challenge is to make efficient large arable farms profitable and in order to do so, they will have to be very large and be efficient. The trend will probably continue away from a subsidy for organic production and to-wards a subsidy for the environmental benefits. The current subsidy level in Denmark is not likely to be increased and the price premium seems to be declining. This indi-cates that the organic as well as the conventional farms will have to be more efficient to be profitable

Precision Agriculture for Crop and Livestock Farming—Brief Review

In the last few decades, agriculture has played an important role in the worldwide economy. The need to produce more food for a rapidly growing population is creating pressure on crop and animal production and a negative impact to the environment. On the other hand, smart farming technologies are becoming increasingly common in modern agriculture to assist in optimizing agricultural and livestock production and minimizing the wastes and costs. Precision agriculture (PA) is a technology-enabled, data-driven approach to farming management that observes, measures, and analyzes the needs of individual fields and crops. Precision livestock farming (PLF), relying on the automatic monitoring of individual animals, is used for animal growth, milk production, and the detection of diseases as well as to monitor animal behavior and their physical environment, among others. This study aims to briefly review recent scientific and technological trends in PA and their application in crop and livestock farming, serving as a simple research guide for the researcher and farmer in the application of technology to agriculture. The development and operation of PA applications involve several steps and techniques that need to be investigated further to make the developed systems accurate and implementable in commercial environments.info:eu-repo/semantics/publishedVersio

Advanced Knowledge Application in Practice

The integration and interdependency of the world economy leads towards the creation of a global market that offers more opportunities, but is also more complex and competitive than ever before. Therefore widespread research activity is necessary if one is to remain successful on the market. This book is the result of research and development activities from a number of researchers worldwide, covering concrete fields of research

Care in digital farming - from acting on to living with

Development of digital technology to handle complex situations in agriculture hasfor long time mainly been technology driven, resulting in limited adoption. Thisthesis aims to: 1) Introduce methods and theories from the research field of humancomputerinteraction in the agricultural domain to improve design and developmentprocesses of digital technology. 2) Introduce the concept of care to increaseknowledge about farmers' technology use in their socio-technical system (practice),as well as to introduce a relational perspective in agriculture. The two systemicallydescribed complex decision situations are fertilization with a decision supportsystem, that uses satellite images and automated milking systems. 3) Evaluate twodifferent theoretical lenses to study the concept of care in practice, DistributedCognition and Activity Theory. The studies of farmers' socio-technical systemsshow that farmers develop an enhanced professional vision to interpret data from thetechnology and learn more about the field/crop or the cow. New technology changesthe relationship between the farmer and the field/crop or cow, but the experiencedfarmer supplements what they see through the technology with direct contact with,for example, the cow. The need for a stockperson’s eye is thus at least as great afterthe introduction of robots in milk production. A relational perspective involves anunderstanding of our mutual dependence with the crop or the cow in these examples,as well as nature and its ecosystem services. Introduction of the concept of care anda relational approach, meaning that farming is to live with, not just act on, cansupport the transformation of agriculture that we know is necessary. In thistransformational process, technology has an important role to play. However, it mustbe developed in cooperation and dialog with end-users to fit in their socio-technicalecologicalsystem and thus support their care

Typologies of Dairy Farms with Automatic Milking System in Northwest Spain and Farmers’ Satisfaction

The aim of this study was to determine the characteristics of the dairy farms that installed an automatic milking system (AMS). A survey of 38 dairy farms with AMS, in Galicia (Spain), collected information on quantitative and qualitative variables. Following elimination of redundant variables, categorical principal component analysis identified 4 factors accounting for 43.7% of the total variance. Using these factors, the farms studied were subjected to hierarchical cluster analysis which differentiated 4 types of farms: (A) farms with more leisure and quality of life where the AMS covered the expectations of farmers (29%); (B) farms that removed cows more often due to AMS and farmers with more stress (34%); (C) farms with little leisure and farmers with no successor (21%); (D) large farms with many fulltime employees (FTE) where the AMS had covered farmer’s expectations the least (11%). Generally the farms were based on a family structure with a high percentage of FTE. With the adoption of AMS these farms sought to increase milk production, save labour and have more flexibility. With 87% of farms with free cow traffic the activity that took the most of the farmer’s time was fetching cows for milking (1 h/day). Nearly 58% of farmers were completely satisfied with their AMS, although this value reached 91% in farms with herd sizes below the average which were better adapted to the use of one AMS.The authors are grateful for the financial support granted by the Autonomous Government of Galicia through the Directorate General for Research & Development (PGIDT/PGIDIT Project, Ref: 07MRU013291PR)S

Digitalisation in Agriculture: Knowledge and Learning Requirements of German Dairy Farmers

Purpose: This study aims at investigating how digitalisation (in the sense of industry 4.0) has changed the work of farmers and how they experience the changes from more traditional work to digitalised agriculture. It also investigates what knowledge farmers require on digitalised farms and how they acquire it. Dairy farming was used as domain of investigation since it, unlike other industries, has strongly been affected by digitalisation throughout the last years.Method: Exploratory interviews with 10 livestock farmers working on digitalised dairy farms were analysed using qualitative content analysis. A deductive and inductive coding strategy was used. Findings: Farming work has changed from more manual tasks towards symbol manipulation and data processing. Farmers must be able to use computers and other digital devices to retrieve and analyse sensor data that allow them to monitor and control the processes on their farm. For this new kind of work, farmers require elaborated mental models that link traditional farming knowledge with knowledge about digital systems, including a strong understanding of production processes underlying their farm. Learning is mostly based on instructions offered by manufacturers of the new technology as well as informal and non-formal learning modes. Even younger farmers report that digital technology was not sufficiently covered in their (vocational) degrees. In general, farmers emphasises the positive effects of digitalisation both on their working as well as private life. Conclusions: Farmers should be aware of the opportunities as well as the potential drawbacks of the digitalisation of work processes in agriculture. Providers of agricultural education (like vocational schools or training institutes) need to incorporate the knowledge and skills required to work in digitalised environments (e.g., data literacy) in their syllabi. Further studies are required to assess how digitalisation changes farming practices and what knowledge as well as skills linked to these developments are required in the future