Use of twitter data for waste minimisation in beef supply chain

Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well

Biological control of Alphitobius diaperinus with Steinernema rarum CUL and Heterorhabditis bacteriophora SMC and feasibility of application in rice hull

Chemical insecticides often are not efficient in reducing Alphitobius diaperinus populations in poultry farms and have induced insect resistance. Entomopathogenic nematodes (EPNs) appear as an alternative to pest biocontrol agents; however, their efficiency on rice hull litter is still unknown. The aim of this study was to evaluate the potential of Steinernema rarum (CUL isolate), Heterorhabditis bacteriophora (SMC isolate) and their symbiotic bacteria as biocontrol agents of A. diaperinus larvae and adults in rice hull litter. Mortality of insect adults and fifth- and seventh-instar larvae was determined in Petri dishes containing filter paper or rice hull. The effect of Xenorhabdus szentirmaii and Photorhabdus luminescens on L7 and adults in rice hull substrate was also evaluated. Moreover, the effectiveness of the EPNs was assessed in bags in an environment simulating the prevailing conditions in a broiler chicken farm. Under laboratory conditions, insect mortality was significantly affected by EPN species, substrate, insect stage and time after application. Mortality of L5 and L7 caused by EPNs in rice hulls reached a peak of 64 and 57.3 %, respectively, whereas symbiotic bacteria applied on rice hull showed low mortality rate at both insect stages. In the simulated poultry farm conditions, S. rarum and H. bacteriophora caused up to 40.8 and 50.4 % mortality of A. diaperinus larvae, respectively, but with adult mortality being low for both species. We conclude that infective juveniles from S. rarum CUL and H. bacteriophora SMC isolates can be used as biological control agents of A. diaperinus larvae in chicken litter containing rice hulls.Fil: del Valle, Eleodoro Eduardo. Universidad Nacional del Litoral. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Frizzo, Laureano Sebastian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Malmierca, Melisa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Zbrun, María Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Ciencias Veterinarias del Litoral. Universidad Nacional del Litoral. Facultad de Ciencias Veterinarias. Instituto de Ciencias Veterinarias del Litoral; ArgentinaFil: Lax, Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Zoología Aplicada; ArgentinaFil: Doucet, Marcelo Edmundo. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Centro de Zoología Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Diversidad y Ecología Animal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Diversidad y Ecología Animal; Argentin

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project

The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity