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Argentina substantially contributes to the global organic agriculture and food sector due to its large areas of organically managed agricultural land. However, most of the organic production is foreseen for export. Overall, food supply for the domestic organic market is hardly tapped. This study investigates the current importance of organic agriculture and food production as well as its consumption within the country. The novelty of the study also lies in the observation, documentation and analysis of latest stakeholder-driven developments towards organic agriculture and food. The publication allows to make the Argentinian organic market significantly more visible for the international audience.
Food losses occur for many reasons at all stages of supply chains for fruits, vegetables and potatoes. They cause immense economic, environmental and social costs – not only in developing countries but also in developed countries. According to the European Commission, about 90 million tonnes of food are wasted annually in Europe alone. However, particularly for the early stages of supply chains for fruits, vegetables and potatoes there is still a lack of reliable data. Thus, one objective of this study is to contribute to the quantification of food losses between field and retail, where the main focus is set on potatoes, apples, carrots, strawberries and asparagus. Furthermore, neither reasons why products are removed from the supply chains nor their alternative uses are fully examined yet. This is why, the study takes a look on those issues, too. Results are based on data from an online survey among producers of fruits, vegetables and potatoes in North-Rhine Westphalia, Germany and on interviews with producers and other supply chain experts. Findings suggest that the products’ size and form, their storage capabilities and food safety issues have big impacts on food losses. Despite a small sample size, these findings are in line with recent studies.
Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit
(2017)
(1) Background: The aim of the study was to use innovative sensor technology for non-destructive determination and prediction of optimum harvest date (OHD), using sweet cherry as a model fruit, based on different ripening parameters. (2) Methods: Two cherry varieties in two growing systems viz. field and polytunnel in two years were employed. The fruit quality parameters such as fruit weight and size proved unsuitable to detect OHD alone due to their dependence on crop load, climatic conditions, cultural practices, and season. Coloration during cherry ripening was characterized by a complete decline of green chlorophyll and saturation of the red anthocyanins, and was measured with a portable sensor viz. spectrometer 3-4 weeks before expected harvest until 2 weeks after harvest. (3) Results: Expressed as green NDVI (normalized differential vegetation index) and red NAI (normalized anthocyanin index) values, NAI increased from -0.5 (unripe) to +0.7 to +0.8 in mature fruit and remained at this saturation level with overripe fruits, irrespective of variety, treatment, and year. A model was developed to predict the OHD, which coincided with when NDVI reached and exceeded zero and the first derivative of NAI asymptotically approached zero. (4) Conclusion: The use of this sensor technology appears suitable for several cherry varieties and growing systems to predict the optimum harvest date.