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Abstract The paper deals with microeconometric techniques useful for the study of differences between groups of objects, methods that go beyond simple comparison of average values. Techniques for the decomposition of differences in distributions by constructing counterfactual distributions were considered. Using the Machado-Mata quantile regression approach the empirical decomposition of the inequalities in income distributions of one-person households in urban and rural areas was performed. We employed data from the Household Budget Survey for Poland in 2012. It was found that the tendency towards increased income inequalities between urban and rural residents when moving to the right of the income distribution can be observed. The rural residents are at a disadvantage. The decomposition of the inequalities revealed a growing share of the part explained by different characteristics of people and a declining share of the unexplained part, associated with the evaluation of those characteristics.

Presentation of EFSA activities on Pest Surveillance and Horizon Scanning for the International Plant Health Conference held in London, 21-23 September 2022. EU; en; PDF; PLANTS@efsa.europa.eu

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The COT reviewed the contribution of the phytoestrogens research programme and assessed its contribution to FSA’s policy aims. The statement sets out their conclusions and serves as a closing review of this research programme.

This document aims to facilitate the access and list all the outputs and materials delivered in 2022 in the context of EFSA mandates on plant pest surveillance M-2020-0114 and M-2022-0069 EU; en; PDF; PLANTS@efsa.europa.eu

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Provider Communities that are members of the Agricultural Research Federation (AgReFed) are independent, autonomous entities who retain control over their own data, data services, repositories and operations. This suite of Technical Policies specifies the technical requirements for Data Provider Communities to follow for membership to AgReFed. These policies cover the technology choices, data policy and standards, including the AgReFed Trusted Repository Policy and AgReFed FAIR Data Policy and the initial qualifying thresholds, for data to qualify as AgReFed data.

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Internet of Things and Machine Learning Applications for Smart Precision Agriculture.\u00a0IoT Applications Computing; Singh, I., Gao, Z., Massarelli, C., Eds, pp. 135-165"]} Climate Change, Monsoon Pattern Change, lack of labour, rising labour and farming cost, crop failures linked to unforeseen production caused by diseases, soil degradation, and as well as rapidly changing market prices in agricultural products are the main Challenges. Strategic planning, use of Novel Systems, and Home automation are the solutions to adversely impacting agricultural development with new future possibilities for better Human Civilization. Home automated Novel Systems having alert and notifications features incorporate strategic planning and are intelligent, effective, and efficient with many more features is also useful for the Agriculture sector. The marketplace needs massive food, and current agricultural modernization approaches call for substantial energy inputs. Economic factors play a vital role. On the other hand, increased demand for food cereals as a result of population growth has led to an increase in the cost of agricultural commodities. Internet of things (IoT) and Artificial Intelligence (AI) have changed trends in Smart Agriculture. IoT and AI assisted Home Automated and Smart Agricultural Novel Systems created new future possibilities, and helps in strategic planning and impacting from Home Automation with alerts and notifications to large agriculture fields in a positive way by working as Executive Decision Support System (EDSS). It also has the potential to minimise farmer losses, produce high yield, significantly raise the quality of produced food, lower labour costs, boosts farmer incomes, and fully achieve agricultural modernization are the important features of Novel Systems with IoT and AI assisted clever agricultural techniques along with increasing agricultural productivity and helps for Global Economy and food security for Nations. The goal of the current research paper is to review various recent trends and explore new future possibilities, strategic planning, and the Impact of IoT and AI assisted Home Automated and Smart Agricultural Novel Systems in Climate Change and Monsoon Pattern Change scenarios.