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Book (stand-alone)FAO/INFOODS Guidelines for Converting Units, Denominators and Expressions. Version 1.0 2012
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Conversion of food data is done in the areas of nutrition (i.e. food composition and dietary assessment) and food safety (exposure assessment), and when reporting analytical data, including their publication in scientific articles. Food composition data are expressed in a variety of ways, depending on national conventions, practices of various institutions and journals requirements. However, to aggregate or compare data from diverse sources, it is often necessary to convert them. -
Book (stand-alone)FAO/INFOODS Guidelines for Checking Food Composition Data prior to the Publication of a User Table/Database-Version 1.0 2012
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Food composition data play an essential role in many sectors, including nutrition, health, agriculture, environment, food labelling and trade (Burlingame, 2004; Greenfield and Southgate, 2003; Pennington, 2008). Over the last 25 years, INFOODS has developed many international standards, guidelines and tools to obtain harmonized food composition data. They contain criteria for analytical data, guidelines on component identifiers, data compilation, food nomenclature, interchange and quality evalua tion (INFOODS, 2012a; Greenfield and Southgate, 2003; Klensin et al., 1989; Rand et al., 1991; Truswell et al.,1991). They were supplemented by guidelines from others such as EuroFIR (EuroFIR, 2012a; Westenbrink et al., 2009). However, as there are no guidelines on the validation/verification of data prior to publishing them in a user table/database (DB), INFOODS and FAO decided to develop such guidelines through the INFOODS network. The document was constructed on the assumption that the user t able/DB was developed according to the criteria set by Greenfield and Southgate (2003, pp.14-15) as outlined in Figure 1. It reflects the different stages of food composition database management until the production of user tables/DBs. Checks should be performed at all levels of the food composition database (FCDB) and a final check is recommended before the release of a user table/DB. The checks described in this document are related to compiled/aggregated data before publication in user tables /DBs. The objective of this document is to outline comprehensively the internal checks to be carried out on the food composition data and documentation prior to their publication in the user table/DB (section 3). For those compilers not yet familiar with the compilation and publication procedures of food composition data, a section on general issues (section 2) was added to give a brief overview of important issues which are useful for a better understanding of the checks and for keeping the c hecks as short as possible, i.e. without the need for further explanations. which provide further useful information for those with less experience in database compilation -
Book (series)Research on the measurement of post-harvest losses
Minimum losses by commodity and region: insights from the literature
2021Also available in:
No results found.The reduction of agricultural losses, especially among smallholder farmers, should be an essential component of food security strategies in developing countries. Loss reduction strategies should be informed by evidence on optimal loss levels, or the point below which loss reduction efforts become economically unviable, characterized by reduction costs greater than benefits. Information on minimum losses can help provide a benchmark for farm management, formulation of policies, and investment decisions. This study connects information on minimum losses with farming practices or production technologies, to help in assessing the effectiveness of loss reduction practices and of the underlying policies and incentives that promote them. While most empirical research and data collection activities on losses tend to focus on average losses, this paper provides evidence on minimum losses levels for several commodities and regions of the world.
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