CAP-reform and the provision of non-commodity outputs in Brandenburg

This paper presents an attempt to model the response of selected farms to decoupled direct payments and the associated impact on the provision of a defined set of non-commodity outputs (NCO’s) using a combined modelling approach consisting of the AgriPoliS and MODAM models. AgriPoliS focuses on the socio-economic dimension of multifunctionality at the individual farm and regional levels and explicitly models heterogeneous farms (in size, location and efficiency) within a competitive and dynamic environment. The linear-programming model MODAM allows a detailed representation of production processes and their impact on the environmental dimension of multifunctionality at the farm level. We simulate the impact of a uniform area payment and a fully decoupled single farm payment. Our case study region is the district Ostprignitz-Ruppin in Brandenburg. Results show that the decoupling schemes create a trade-off between the NCO’s and that adjustment reactions differ between farms depending on their legal form, size, and production.decoupling, multifunctionality, non-commodity outputs, modelling, simulation, policy analysis, ecological indicators, Agricultural and Food Policy, Land Economics/Use,

GIS-fuzzy logic approach for building indices: regional feasibility and natural potential of ranching in tropical wetland

The regional feasibility of ranching (RFR) index was obtained in order to evaluate the productive potential of farms in the Pantanal. Five indicators were selected by expert and employed for the developing of the index. One of the five indicators corresponded to the natural potential for livestock ranching (NPLR) index which was generated by GIS-fuzzy logic. Fuzzy inference process, involving definitions of membership functions, fuzzy set operations and inference rules was implemented and validated with the participation of primary stakeholders. Different scenarios were simulated in a batch, next validated and adjusted with the participation of stakeholders. Both procedures were performed by the use of the Webfuzzy software. The NPLR and RFR index values, calculated for the pilot ranch, corresponded to the expectations of both expert and stakeholders. Fuzzy logic combined with landscape metric seems to be suitable for the definition of the productive natural potential of ranches to produce livestock in the Pantanal. The indices can assess the regional feasibility of ranching, contributing to decision-making of stakeholders.\u

Applications of Emerging Smart Technologies in Farming Systems: A Review

The future of farming systems depends mainly on adopting innovative intelligent and smart technologies The agricultural sector s growth and progress are more critical to human survival than any other industry Extensive multidisciplinary research is happening worldwide for adopting intelligent technologies in farming systems Nevertheless when it comes to handling realistic challenges in making autonomous decisions and predictive solutions in farming applications of Information Communications Technologies ICT need to be utilized more Information derived from data worked best on year-to-year outcomes disease risk market patterns prices or customer needs and ultimately facilitated farmers in decision-making to increase crop and livestock production Innovative technologies allow the analysis and correlation of information on seed quality soil types infestation agents weather conditions etc This review analysis highlights the concept methods and applications of various futuristic cognitive innovative technologies along with their critical roles played in different aspects of farming systems like Artificial Intelligence AI IoT Neural Networks utilization of unmanned vehicles UAV Big data analytics Blok chain technology et

Determination of the best quail eggs using simple additive weighting

Eggs are livestock products contributed greatly to the achievement of the nutritional adequacy of the public; the egg is a food that is very good for children who are growing because it contains nutrients such as a complete protein, fat, vitamins and minerals that are easy to digest. One of the eggs are much in demand by children are quail eggs. The nutritional value of quail eggs is not less than the nutritional value of eggs containing 12.8% protein and 11.5% fat. Quail eggs are good quality will have good nutritional value anyway. To determine the quality of a good quail eggs will require an expert system. The method used in determining the quality of a good quail eggs using Simple Additive weighting method. The criteria in this research that egg size, style/color of the shell, the shell thickness, shell texture, shape and cleanliness of quail eggs. With the expert system is expected to assist farmers in determining the quail eggs quail egg quality so that the people can consume quail eggs that have good nutritional value. The results of this study showed an alternative ranking first in C with a value of 0.95, ranking second D with a value of 0.7208, ranking third E with a value of 0675, ranking the fourth A with a value of 0.4542 and ranking last in the B with a value of 0.4541

Decision support systems for large dam planning and operation in Africa

Decision support systems/ Dams/ Planning/ Operations/ Social impact/ Environmental effects

Downscaling Africa’s Drought Forecasts through Integration of Indigenous and Scientific Drought Forecasts Using Fuzzy Cognitive Maps

In the wake of increased drought occurrences being witnessed in Sub-Saharan Africa, more localized and contextualized drought mitigation strategies are on the agendas of many researchers and policy makers in the region. The integration of indigenous knowledge on droughts with seasonal climate forecasts is one such strategy. The main challenge facing this integration, however, is the formal representation of highly-structured and holistic indigenous knowledge. In this paper, we demonstrate how the use of fuzzy cognitive mapping can address this challenge. Indigenous knowledge on droughts from five communities was modeled and represented using fuzzy cognitive maps. Maps from one of these case communities were then used in the implementation of the integration framework, called itiki

Quantile regression forests-based modeling and environmental indicators for decision support in broiler farming

An efficient and sustainable animal production requires fine-tuning and control of all the parameters involved. But this is not a simple task. Animal farming is a complex biological system in which environmental parameters and management practices interact in a dynamic way. In addition, the typical non-linear response of biological processes implies that relationships across parameters that are critical to assure animal welfare and performance are difficult to determine. In this paper a novel decision support system based on environmental indicators and on weights, leg problems and mortality rates is proposed to address this issue. The data-driven modeling process is performed by a quantile regression forests approach that allows estimating growth, welfare and mortality parameters on the basis of environmental deviations from optimal farm conditions. Resulting models also provide confidence intervals able to deal with uncertainty. They are deployed in farm, offering an accessible tool for farmers, veterinarians and technical personnel. Experimental results involving 20 flocks of broiler meat chickens from different farms show the validity of the system, obtaining robust prediction intervals and high accuracy, namely over 81% for every model. The in-field use of the proposed approach will facilitate an efficient and animal welfare-friendly production management.This project was funded by the Spanish Ministry of Economy and Competitivity, General Directorate for Science and Technology, National Research Program ’Retos de la Sociedad’ Project #AGL2013-49173-C2-1-R P.I. Inma Estevez and #AGL2013-49173-C2-2-R. The authors wish to thank to AN and the farmers for facilitating access to their farms for data collection