Motivational Factors for Entering into Agri-preneurship : A Study among Successful Agri-preneurs of Kerala

Agri-preneurship is a solution to many economic problems faced by India in general and agriculturists in particular. It can significantly contribute to rural development. This study seeks to understand the factors which motivate people to start and lead to the success of agripreneurship. Primary data were collected from 60 respondents using a structured interview schedule. It was found that the highest motivational factor for entering into the agripreneurship field was ‘Knowledge about the business’ followed by ‘self-satisfaction’. There was no significant difference among motivational factors with regard to age group

Weed survey of spring cereals in New Brunswick

En 1986 et 1987, un inventaire des mauvaises herbes a été effectué dans 187 champs de céréales de printemps au Nouveau-Brunswick. Au total, 76 espèces ont été identifiées, 40 d'entre elles étant considérées comme importantes sur le plan agronomique. Environ 50% des espèces étaient vivaces. L'ortie royale (Galeopsis tetrahit), le chiendent (Agropyron repens), la petite oseille (Rumex acetosella), la marguerite blanche (Chrysanthemum leucanthemum), la spargoute des champs (Spergula arvensis) et la stellaire moyenne (Stellaria média) avaient les plus hautes valeurs d'abondance relative. Le chiendent et l'ortie royale avaient les plus fortes densités à 8,0 et 7,1 plantes m-2, respectivement. La densité de mauvaises herbes la plus élevée (103 plantes m-2) a été observée chez l'avoine (Avena sativa) cultivée à la suite de plantes fourragères. La plus faible densité a été détectée chez le blé (Triticum aestivum) suite à une culture de pomme de terre (Solanum tuberosum). La plupart des espèces abondantes étaient tolérantes au MCPA, l'herbicide le plus fréquemment utilisé. Les agriculteurs pourraient lutter plus efficacement contre les mauvaises herbes dans les céréales en choisissant un herbitolérantes au MCPA ou au 2,4-D, et a en pré-plantation ou en post-récolte ses herbes vivaces.During 1986 and 1987, a weed survey of 187 New Brunswick cereal fields was conducted. A total of 76 species were identified of which 40 were considered agronomically important. About 50% of the species were perennial. Hemp-nettle (Galeopsis tetrahit), quack grass (Agropyron repens), sheep sorrel (Rumex acetosella), ox-eye daisy (Chrysanthemum leucanthemum), corn spurry (Spergula arvensis), and chickweed (Stellaria média) had the highest relative abundance values. Quack grass and hemp-nettle had the highest densities at 8.0 and 7.1 plants m-2, respectively. The highest weed density (103 plants m-2) was found in oats (Avena sativa) grown after a forage crop. The lowest density (24 plants m-2) was found in wheat (Triticum aestivum) grown after potatoes (Solarium tuberosum). Most of the abundant species were tolerant to MCPA, the most commonly used herbicide. Farmers could make major improvements in cereal weed control by choosing a herbicide that would control species tolerant to MCPA or 2,4-D, and using preplant or postharvest weed control to minimize the impact of perennial weeds

Emerging technology and auditing practice : analysis for future directions

Purpose – The purpose of this paper is to explore the effects of emerging technology (technology adoption, perceived benefits, technological challenges and ease of use) and the auditing practice of accounting professionals. Design/methodology/approach – The primary method of data collection was a questionnaire directed to newly practicing chartered accountants who are partners of sole proprietorship or partnership firms in India. The data were analyzed by using partial least squares structural equation modeling (PLS-SEM). Findings – The findings revealed that there is a positive and significant relationship between characteristics of emerging technology (technology adoption, technological challenges and ease of use) and auditing practice, while factors of the perceived benefits had a negative relationship with auditing practice. Research limitations/implications – The study model would aid technology enabled audit research by giving a platform for a new study to investigate further detailed solutions to emerging information technology determinants. Practical implications – This study illustrates how tools technique perceived benefit motivates sole proprietorship practicing auditors to adopt emerging technology- enabled auditing software for auditing client’s financial statements. Further, this study has added to the information technology auditing literature and might add benefits to the numerous other audit firms to adopt in emerging technology tools their audit firm. Social implications – Audit firms, generally sole proprietorship and partnership firms, should be given enough awareness about the latest audit software tools to carry out their audit tasks efficiently. Originality/value – The study findings highlight benefits of emerging technology-enabled auditing practice among owners/partners of the sole proprietorship or partnership firms, which is not extensively discussed in the prior studies. Furthermore, it broadens knowledge of perceived benefit, technological challenges and ease of use in technology-enabled audit software in the auditing and accounting literature.info:eu-repo/semantics/publishedVersio

From Molecular Descriptors to Intrinsic Fish Toxicity of Chemicals:An Alternative Approach to Chemical Prioritization

The European and U.S. chemical agencies have listed approximately 800k chemicals about which knowledge of potential risks to human health and the environment is lacking. Filling these data gaps experimentally is impossible, so in silico approaches and prediction are essential. Many existing models are however limited by assumptions (e.g., linearity and continuity) and small training sets. In this study, we present a supervised direct classification model that connects molecular descriptors to toxicity. Categories can be driven by either data (using k-means clustering) or defined by regulation. This was tested via 907 experimentally defined 96 h LC50 values for acute fish toxicity. Our classification model explained ≈90% of the variance in our data for the training set and ≈80% for the test set. This strategy gave a 5-fold decrease in the frequency of incorrect categorization compared to a quantitative structure-activity relationship (QSAR) regression model. Our model was subsequently employed to predict the toxicity categories of ≈32k chemicals. A comparison between the model-based applicability domain (AD) and the training set AD was performed, suggesting that the training set-based AD is a more adequate way to avoid extrapolation when using such models. The better performance of our direct classification model compared to that of QSAR methods makes this approach a viable tool for assessing the hazards and risks of chemicals

Motivational Factors for Entering into Agri-preneurship : A Study among Successful Agri-preneurs of Kerala

Agri-preneurship is a solution to many economic problems faced by India in general and agriculturists in particular. It can significantly contribute to rural development. This study seeks to understand the factors which motivate people to start and lead to the success of agripreneurship. Primary data were collected from 60 respondents using a structured interview schedule. It was found that the highest motivational factor for entering into the agripreneurship field was ‘Knowledge about the business’ followed by ‘self-satisfaction’. There was no significant difference among motivational factors with regard to age group

Species Composition and Community Structure of Dung Beetles Attracted to Dung of Gaur and Elephant in the Moist Forests of South Western Ghats

The community structure of dung beetles attracted to dung of gaur, Bos gaurus (H. Smith) (Artiodactyla: Bovidae) and Asian elephant, Elephas maximus Linnaeus (Proboscidea: Elephantidae), is reported from the moist forests of Western Ghats, in South India. The dominance of dwellers over rollers, presence of many endemic species, predominance of regional species and higher incidence of the old world roller, Ochicanthon laetum, make the dung beetle community in the moist forests of the region unusual. The dominance of dwellers and the lower presence of rollers make the functional guild structure of the dung beetle community of the region different from assemblages in the moist forests of south East Asia and Neotropics, and more similar to the community found in Ivory Coast forests. The ability of taxonomic diversity indices to relate variation in dung physical quality with phylogenetic structure of dung beetle assemblage is highlighted. Comparatively higher taxonomic diversity and evenness of dung beetle assemblage attracted to elephant dung rather than to gaur dung is attributed to the heterogeneous nature of elephant dung. Further analyses of community structure of dung beetles across the moist forests of Western Ghats are needed to ascertain whether the abundance of dwellers is a regional pattern specific to the transitional Wayanad forests of south Western Ghats

Direct injection liquid chromatography-tandem mass spectrometry as a sensitive and high-throughput method for the quantitative surveillance of antimicrobials in wastewater

Environmental antimicrobial pollution and antimicrobial resistance pose a threat to environmental and human health. Wastewater analysis has been identified as a promising tool for antimicrobial monitoring and the back-estimation of antimicrobial consumption, but current pretreatment methods are tedious and complicated, limiting their scope for high-throughput analysis. A sensitive direct injection method for the quantification of 109 antimicrobials and their metabolites in wastewater samples was developed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method was validated for both wastewater influent and effluent in terms of specificity, calibration range, matrix effect, filtration loss, accuracy, precision, limit of detection (LOD), and limit of quantification (LOQ). Most analytes achieved calibration of R2 &gt; 0.99, and the calibration range was from 0.0002 to 150 μg L−1. Recoveries ranged consistently between ~50 % and ~100 % and losses were attributed to sample filtration. Method LOQs were determined as low as 0.0003 μg L−1, and acceptable accuracy (75 %–125 %) and precision (within 25 %) were achieved for &gt;90 % of the analytes. The method was subsequently further assessed using wastewater of raw influent and treated effluent collected from 6 Australian wastewater treatment plants in 2021. In total, 37 analytes were detected in influent and 22 in effluent. Most of them could be quantified at concentrations ranging from 0.0053 to 160 μg L−1, with benzalkonium chloride-C12, amoxicilloic acid, and cephalexin detected at the highest concentrations. The current study provides a straightforward analytical method for antimicrobial monitoring in wastewater with a fast and simple pretreatment procedure.</p