Quality and safety improvements in informal milk markets and implications for food safety policy

Milk marketing in Assam, NE India remains predominantly in the informal sector; there is also growing concern among consumers about the purity and quality of milk marketed by informal milk vendors and the possible health risk posed by it. ILRI’s study on milk safety (ILRI 2008) indicates that most of the milk samples (including pasteurized and UHT) available in Assam do not meet quality standards from the standpoint of physical quality, adulterants and bacterial load (total bacterial count and coliform count). In 2009, a training and certification program was initiated to improve milk handling among milk traders who are the main conduits of milk being marketed in Assam. The impact of the program on milk value chain actors was assessed through a prospective matched cohort study using a double difference design. Data was collected from surveys of producers, milk vendors, and consumers. Rapid diagnostic tests on milk samples were conducted to assess levels of hazards from presence of pathogens in milk traded in informal milk markets. Estimates of economic benefits show positive effects in terms of increased average profit margins and value added. Sector level benefits as approximated from micro-level estimates of economic indicators show that traditional dairy value chain in Kamrup generates about 0.8 million rupees value added per day; this translates to an annual estimate of economic impact in Kamrup of at least US$ 5.6 million. Given the important economic contribution of traditional dairy value chain, public policy that affects informal milk markets and actors will need to be based on risk and not hazard, and improving capacity for risk assessment and incentives for better risk management will support the continued viability of the traditional dairy sector in Assam. Keywords: smallholder dairy, informal milk markets, food safety polic

Sensitivity and specificity of detection methods for erythropoietin doping in cyclists

Recombinant human erythropoietin (rHuEPO) is used as doping a substance. Anti-doping efforts include urine and blood testing and monitoring the athlete biological passport (ABP). As data on the performance of these methods are incomplete, this study aimed to evaluate the performance of two common urine assays and the ABP. In a randomized, double-blinded, placebo-controlled trial, 48 trained cyclists received a mean dose of 6000 IU rHuEPO (epoetin beta) or placebo by weekly injection for eight weeks. Seven timed urine and blood samples were collected per subject. Urine samples were analyzed by sarcosyl-PAGE and isoelectric focusing methods in the accredited DoCoLab in Ghent. A selection of samples, including any with false presumptive findings, underwent a second sarcosyl-PAGE confirmation analysis. Hematological parameters were used to construct a module similar to the ABP and analyzed by two evaluators from an Athlete Passport Management Unit. Sensitivity of the sarcosyl-PAGE and isoelectric focusing assays for the detection of erythropoietin abuse were 63.8% and 58.6%, respectively, with a false presumptive finding rate of 4.3% and 6%. None of the false presumptive findings tested positive in the confirmation analysis. Sensitivity was highest between 2 and 6 days after dosing, and dropped rapidly outside this window. Sensitivity of the ABP was 91.3%. Specificity of the urine assays was high; however, the detection window of rHuEPO was narrow, leading to questionable sensitivity. The ABP, integrating longitudinal data, is more sensitive, but there are still subjects that evade detection. Combining these methods might improve performance, but will not resolve all observed shortcomings

The pig sector in North East India: status, constraints and opportunities

Contributed paper prepared for presentation at the international symposium ‘Sustainable Land Use and Rural Development in Mountainous Regions of Southeast Asia’, Hanoi, 21-23 July 201

An improved optimization technique for estimation of solar photovoltaic parameters

The nonlinear current vs voltage (I-V) characteristics of solar PV make its modelling difficult. Optimization techniques are the best tool for identifying the parameters of nonlinear models. Even though, there are different optimization techniques used for parameter estimation of solar PV, still the best optimized results are not achieved to date. In this paper, Wind Driven Optimization (WDO) technique is proposed as the new method for identifying the parameters of solar PV. The accuracy and convergence time of the proposed method is compared with results of Pattern Search (PS), Genetic Algorithm (GA), and Simulated Annealing (SA) for single diode and double diode models of solar PV. Furthermore, for performance validation, the parameters obtained through WDO are compared with hybrid Bee Pollinator Flower Pollination Algorithm (BPFPA), Flower Pollination Algorithm (FPA), Generalized Oppositional Teaching Learning Based Optimization (GOTLBO), Artificial Bee Swarm Optimization (ABSO), and Harmony Search (HS). The obtained results clearly reveal that WDO algorithm can provide accurate optimized values with less number of iterations at different environmental conditions. Therefore, the WDO can be recommended as the best optimization algorithm for parameter estimation of solar PV