Public Goods and Farming

FarmDain, a Decision Support System for Dairy Sheep and Goat Production

Managing a milk zone in the dairy industry is demanding. Data necessary for efficient management are difficult to acquire because they usually must be collected in organized and standardized ways. On the other hand, software practices constantly provide new tools that can go beyond simple record-keeping practices and add value to the data. In this work, FarmDain is a novel web-based application for sheep and goat management. It aims to improve milk production and processing by digitizing the value chain in data acquisition, processing and visualization between dairy production businesses and their milk suppliers. FarmDain uses state-of-the-art software technologies to model the data collection process and provides a straightforward user interface to facilitate data processing and visualization. Using the app in a case study carried out for 12 months in a dairy sheep farm resulted in lower feeding cost per milked ewe by 5.5% when ewes were allocated into high and low milk production groups compared to the scenario of remaining in one single group. Furthermore, based on reports provided by the app, culling and genetic selection decisions were made to improve the overall farm performance. Similar practices were applied in all farms optimizing their productivity, which led to increased profitability for farms and the Dairy Factory.

Sustainability assessment of short food supply chains (SFSC): developing and testing a rapid assessment tool in one African and three European city regions

Recent literature demonstrates the contribution of short food supply chains (SFSC) to regional economies and sustainable food systems, and acknowledges their role as drivers for sustainable development. Moreover, different types of SFSC have been supported by urban food policies (UFP) over the few last years and actors from the food chain became part of new institutional settings for urban food policies. However, evidence from the sustainability impact assessment (SIA) of these SFSC in urban contexts is limited. Our paper presents an approach for the development of an SIA framework for different SFSC types. In addition, a practical application of the tool in four metropolitan regions (Berlin, London, Ljubljana and Nairobi) is tested. The conceptual development of the SIA framework is based on an in-depth analysis of existing SIA frameworks and methods for assessing the sustainability of agriculture, food chains and food systems and adapted to the specific needs of analysing SFSC in metropolitan regions. The operational value and utility of the framework and the tool were tested with social and natural scientists and local stakeholders. The assessment results demonstrate that SFSC seems to be more sustainable than the baseline (long global food chains) in the social dimension, but also feature specific strengths and weaknesses concerning their economic and environmental sustainability. This might give an indication for regional adjusted strategies and food chain innovations that improve the sustainability performance may be required. We found the tool useful for framing the dialogue between food chain actors, consumers and policy, because it makes benefits and trade-offs of the chain types operating in an urban-rural context more visible and communicable.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10460-021-10288-w.

A Decision Support System for Economically Sustainable Sheep and Goat Farming

Simple Summary

The viability of the European sheep and goat sector is threatened by market, policy, social and technical challenges. To address such challenges, innovations for efficient farm management, especially with decision support capabilities, are considered a strategic priority. The iSAGEDSS is a web application, based on the Happy GoatS solution, which allows dairy and meat small ruminant farmers to make annual management plans by testing future what-if scenarios. It is designed for the meat sheep production system in the United Kingdom and Spain, the dairy sheep production system in France and Greece and the dairy goat production system in Greece. Moreover, it addresses all important farm parameters (flock size, production, processing, grazing, feeding, income and costs and farm prices) and utilizing an energy and protein-based algorithm for nutritional management assessment it produces reports, which are focused on profitability and productivity. Environmental-related figures are also estimated. Results are illustrated with simple and easily understood charts and plots. Case study application results showed high prediction accuracy and demonstrated the ability of the system to promote efficient farm management. In this regard, iSAGEDSS is expected to help farmers to adjust to the challenges faced by the sector and remain sustainable.

Abstract

The European sheep and goat sector is characterized by low professionalization and management training. Moreover, it is fragmented in terms of production aims and farming systems. Here, iSAGEDSS, a web-based application allowing dairy and meat small ruminant farmers in different countries to make annual management plans by testing future scenarios, is presented. Data were obtained for the meat sheep (United Kingdom and Spain), dairy sheep (France and Greece) and dairy goat production systems (Greece) from partners of the Innovation for Sustainable Sheep and Goat Production in Europe (iSAGE) project. These were used to set default values and ranges for all important farm parameters in each system and country. An algorithm was developed assessing nutritional management and its impact on production and financial performance. Reports focus on profitability, productivity and environmental sustainability. A case study in three dairy sheep farms in Greece was performed. In each case, an evaluation scenario was created using actual farm data that were compared with the estimated ones. Two scenarios testing management decisions for gross margin maximization and milk pricing fluctuations were created. Application results showed high prediction accuracy for gross margin and production estimation (error of circa 9% and 4%, respectively). Moreover, the ability to promote financial, production and grazing management efficiency was demonstrated.