A study conducted jointly by FAO and International Analytic Group (IAG) in Vienna, Austria, using data from a proficiency test conducted by these organizations, has demonstrated that there is an urgent need to place quality control systems in, and follow good laboratory practices by, feed analysis laboratories in developing countries. A proficiency test for various constituents (proximate, macro- and micro-minerals, additives and amino acids) was conducted in which laboratories from Europe (40) and developing countries (73) participated. The data obtained allowed a comparison of the performance of these two sets of laboratories. Higher standard deviation and several folds higher coefficient of variation were obtained for the developing country laboratories. For developing country feed analysis laboratories the coefficients of variation for chemical composition parameters, macro-minerals and amino acids were higher by up to 9-fold, 14-fold, and 10-fold respectively, compared with those for European feed analysis laboratories. Also higher number of outliers were observed for developing countries (7.6-8.7% vs. 2.9-3.0%). According to Harinder Makkar of FAO who coordinated this study, “the results illustrate higher need for developing country feed analysis laboratories to improve the quality of data being generated.”
Mr. Makkar further stated that without a robust quality control system, the laboratory personnel are unable to evaluate the quality of the results being generated. Developing countries need to address this issue seriously because it could adversely impact their export and increase wastage of feed and food items for not meeting the quality and safety standards. Also generation of sound data is fundamental to implementation of nutritional principles and for getting benefits from them. For sustainable development of the livestock sector, generation of sound chemical composition data of feed ingredients and mixed or compounded feed is vital.
Feed industries are neither able to resource good quality ingredients nor prepare balanced feeds without having reliable chemical and nutritional value data on feed ingredients. In addition, without sound data on chemical composition, precision feeding or balanced feeding approaches that demand nutrient provision, as per the nutrient requirements of the animal, cannot be used. Unbalanced feeding results in lower profit to farmers, production below the genetic potential of animals, reproductive problems for example longer age of first calving and longer calving interval, animal being more prone to metabolic diseases such as milk fever and ketosis, shorter productive life, poor animal health and welfare, and excessive amounts of pollutants released to the environment
FAO in action
Some of the possible ways to improve the situation are that governments consider increasing investment for improving laboratory infrastructure and laboratory proficiency. Development of sound training programmes and their effective execution is warranted. Higher donors’ attention to this issue and provision of greater funds for developing capacity of laboratory personnel are needed. Many functional laboratories can improve the quality of the data without much investment. A culture of generating quality data needs to be practiced through a change of mindset. This can be achieved by integrating quality control systems and following good laboratory practices. FAO has taken a number of steps in this direction: produced various manuals on quality control systems in feed analysis laboratories, distributed them at no-cost and made them available on FAO website for free downloading; arranged on-line courses on risk management and quality control enhancement; and organized proficiency tests. FAO has also been providing relevant educational support to the laboratories through its network of experts. However, these efforts need to be translated into a movement within countries by formulating government policies, for example setting up of a body overseeing quality of data being generated by laboratories and the laboratory operations; and by supporting laboratories through investments and capacity development. The efforts of International organizations will only be catalytic towards furthering a culture of generation of quality data. Large impact can only be generated by government actions and policies, including promoting public-private partnerships.
The donors, besides supporting efforts that enhance quality control systems in laboratories, may also demand putting in place of a proper control mechanism for the data being generated by the laboratories in the framework of their sponsored projects. Similarly, journals while considering the work for publication in the journal may also seek information from authors on the quality control set up in their research laboratories. Certification and accreditation of laboratories by an outside agency may be encouraged but most laboratories in developing countries do not have funds to achieve this. Use of internal standards will enable the laboratory personnel to evaluate if they are producing quality data. Also creation of a network of laboratories within a country and running of annual in-country proficiency tests would contribute to furthering the proficiency of laboratories, at a relatively low cost.