Farming Systems Research

Report on the February 1986 Inter Center Workshop on Farming Systems Research (FSR) held at ICRISAT Center, Hyderabad, India. The Workshop, which was suggested by TAC, which noted that 14% of the system's resources was devoted to farming systems in some form. The meeting was intended to help centers develop a unified understanding of how FSR should be approached, to assess the relevance, impact, and priority of such research in the CGIAR, and to outline its future directions. It drew on the stripe review of 1978 on this subject. A statement by representatives of the nine IARCs attending is attached.Agenda document, TAC 39th Meeting, March 1986

Co-designing climate-smart farming systems with local stakeholders: A methodological framework for achieving large-scale change

The literature is increasing on how to prioritize climate-smart options with stakeholders but relatively few examples exist on how to co-design climate-smart farming systems with them, in particular with smallholder farmers. This article presents a methodological framework to co-design climate-smart farming systems with local stakeholders (farmers, scientists, NGOs) so that large-scale change can be achieved. This framework is based on the lessons learned during a research project conducted in Honduras and Colombia from 2015 to 2017. Seven phases are suggested to engage a process of co-conception of climate-smart farming systems that might enable implementation at scale: (1) “exploration of the initial situation,” which identifies local stakeholders potentially interested in being involved in the process, existing farming systems, and specific constraints to the implementation of climate-smart agriculture (CSA); (2) “co-definition of an innovation platform,” which defines the structure and the rules of functioning for a platform favoring the involvement of local stakeholders in the process; (3) “shared diagnosis,” which defines the main challenges to be solved by the innovation platform; (4) “identification and ex ante assessment of new farming systems,” which assess the potential performances of solutions prioritized by the members of the innovation platform under CSA pillars; (5) “experimentation,” which tests the prioritized solutions on-farm; (6) “assessment of the co-design process of climate-smart farming systems,” which validates the ability of the process to reach its initial objectives, particularly in terms of new farming systems but also in terms of capacity building; and (7) “definition of strategies for scaling up/out,” which addresses the scaling of the co-design process. For each phase, specific tools or methodologies are used: focus groups, social network analysis, theory of change, life-cycle assessment, and on-farm experiments. Each phase is illustrated with results obtained in Colombia or Honduras

Fungi in Danish soils under organic and conventional farming

A multi-soil study was conducted in Denmark including 29 sites, 8 classified as ‘Organic’, 11 as ‘Conventional with manure and synthetic fertilisers’ and 10 as ‘Conventional with synthetic fertilisers’. The variability of fungal abundance within the three farming systems and the long-term effects of different farming systems on fungal propagules in soil were evaluated. Fungal abundance showed large variations within all three farming systems and this variability reduced the possibility to obtain general conclusions on fungal composition in soils under different farming systems. This was illustrated by the results on total propagule numbers of filamentous fungi and yeasts. Penicillium spp. and Gliocladium roseum were more abundant under organic than conventional farming, while Trichoderma spp. were most abundant in conventionally farmed soils with synthetic fertilisers. These results were not altered after adjusting for possible differences in basic soil properties like total-C and N, extractable P, CEC, base saturation and soil density. The paper discusses whether the differences in fungal abundance are characteristics of a farming system itself or associated with certain management factors being more prevalent in one farming system than the other

Comparing energy use and greenhouse gas emissions in organic and conventional farming systems in the Netherlands

Results are presented of a model study comparing energy use and greenhouse gas emissions in organic and conventional farming systems in the Netherlands. Calculations have been performed for model farms, designed on the basis of current organic and conventional farming practices. Energy use and greenhouse gas emissions per hectare on organic farms are lower than on conventional farms, particularly in dairy farming. Energy use and greenhouse gas emissions per Mg of milk in organic dairy farming is about 80 and 90%, respectively of that in conventional dairy farming. Energy use and greenhouse gas emission per Mg product in organic crop production is 5-40 and 7-17%, respectively higher than in conventional systems. The wide ranges found in crop production reflect large differences among individual crops

Lowland farming system inefficiency in Benin (West Africa):

This paper uses a directional distance function and a single truncated bootstrap approach to investigate inefficiency of lowland farming systems in the Benin Republic. First, we employed a dual approach to estimate and decompose short-run profit inefficiency of each farming system into pure technical, allocative and scale inefficiency and also into input and output inefficiency. Second, an econometric analysis of factors affecting the inefficiency was generated using a single truncated bootstrap procedure to improve inefficiency analysis statistically and obtain consistent estimates. In the short run, scale, allocative and output inefficiency were found to be the main sources of inefficiency. Based on inefficiency results, the inefficiency of lowland farming systems is the most diverse. Compared to a vegetable farming system, technical inefficiency is significantly higher if farmers switch to a rice farming system. Scale, allocative, output, and input inefficiency are significantly lower with an integrated ricevegetable farming system and there was high prevalence of increasing returns to scale in the integrated rice-vegetable farming system. Water control and lowland farming systems are complements and play a significant role in the level of inefficiency. Input inefficiency shows the difficulty that the producers face in adjusting the quality and quantity of seeds and fertilizers. The paper provides empirical support for efforts to promote an integrated rice-vegetable farming system in West Africa lowlands to increase food security. Keywords Lowlands . Inefficiency . Bootstrap . Beni

Maintaining ecological soil functions - techniques in organic farming systems

The ecological soil functions (e.g. habitat and living space, production and utilization, ecological regulation) have to be taken into account and maintained by farming systems. Organic farming systems can provide for this by using suitable crop rotations, manure management methods and tillage techniques

Research, values, and ethics in organic agriculture - examples from sustainability, precaution, nature quality, and animal welfare

Agricultural systems are characterised by involving both natural and social systems. Organic farming, in particular, has developed as part of a wider organic movement incorporating producers, manufacturers and consumers. The organic movement is based on explicit rules as well as broader formulated principles and goals for farming and manufacturing, which are connected to underlying values and perceptions of the relationship between human and nature. This paper is concerned with the challenges to research entailed by the ethical issues in organic farming and the interplay of values and facts in agricultural research

Environmentally Sustainable Issues in Philippine Agriculture

Farming and fishing are major sources of livelihood in rural households in the Philippines. Farming systems in the country are complex, multi-faceted, and geared to promote efficient production and a steady source of income. However, these have also wrought unwanted consequences on the environment, notably soil erosion, water pollution, groundwater depletion, loss of natural habitats, and loss of biological diversity. Farming systems are affected by exogenous environmental factors; in turn, the farming systems also affect agricultural production resource bases. Initiatives from various sectors to mitigate the adverse environmental impacts of farming systems and to protect the agricultural production bases are in place in terms of policies, programs, and action projects.Philippines, agriculture, environment, sustainability

Participatory Common Learning in Groups of Dairy Farmers in Uganda (FFS approach) and Danish Stable Schools

Farmer Field Schools (FFS) is a well-known concept, which is widely used in many types of farming systems in the Global South. In this report different approaches to FFS adjusted to Ugandan smallholder dairy systems and to Danish organic dairy systems are explored and discussed. The report is based on a Master Thesis in Health Anthropology and a mini manual to the so-called Stable Schools. Improvements of farming practices should be based on the context of the individual farm and include the goals of the farmer and the farming system. This should be the case in all types of farming systems. Viewing learning as a social phenomenon and process, as well as an interaction between the learner and the learning environment (including other farmers) may give opportunities for context based innovations and developments towards a common goal in a group of farmers. It is also seen as a result of common transformative learning and legitimate peripheral participation in a social learning environment

NDICEA as a user friendly model tool for crop rotation planning in organic farming

For organic farming systems, the challenge is to become more specific in practices to maintain high standards in sustainability. Soil processes need to be clearly understood if rotations and manure applications are to become more precise. Simulation models like the NDICEA model help in the design and maintenance of these farming systems. These models play a key-role in the design of organic precision farming. The NDICEA model has been calibrated for a number of long-term crop rotation experiments. Recently, the model was validated using research data from more than 35 organic farms all over the country. The model is used to calculate soil-specific mineralization rates in precision applications. In a new easy-to-use application, it was developed to design crop rotations and evaluate performance of crop rotations. This application is used to evaluate the sustainability of farming systems