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Environmental concerns are gradually reducing the global yield capacity of agricultural systems, with climate change representing the most significant challenge. Globally, Potatoes are the most essential non-cereal crop. Therefore, understanding the potential impacts of climate change on potato production is crucial for maintaining future global food security. This study aims to explore the roles played by PGPMs in two distinct regions, which are characterized by different climatic conditions, to assess their influence on two potato varieties, namely Siena and Bellini. Inoculation with these strains, particularly the Aureobasidium pullulans strains Ach1-1 and Ach1-2, resulted in significant improvements in growth and yield. In 2018, impressive yields of 194.1 kg/0.05 ha and 186.6 kg/0.05 ha were recorded for the two strains, with the Ain Taoujdate site achieving yields of 157.1 kg/0.05 ha and 151.1 kg/0.05 ha for each of the two strains. Additionally, further observations revealed that the Siena variety is more susceptible to rot than the Bellini variety. However, Ach1-1 and Ach1-2 strains had a significant effect on this rot, showcasing their potential to mitigate this negative issue in the Bellini variety. These promising results underscore the potential of PGPMs to enhance potato production in the Fez–Meknes region of Morocco, contributing to global food security amid climate change.

Remote sensing (RS) data and geographic information system (GIS) techniques were used to monitor the changes in the Oasis agroecosystem of the pre-Saharan province of Errachidia, southeastern Morocco. The land use and land cover (LULC) change of the agroecosystem of this province was processed using Landsat time series with 5-year intervals of the last thirty years. The normalized difference vegetation index (NDVI) and the maximum likelihood classification (MLC) were categorized into five classes, including water bodies, cultivated land, bare land, built-up, and desertified land. The overall accuracy of the MLC maps was estimated to be higher than 90%. The finding showed a degradation trend represented by an increase in desertified lands, which tripled in the ten last years, passing from 20.62% in 2011 to 58.49% in 2022. The findings also depicted a decreasing trend in the cultivated area in this period passing from 174.2 km2 in 1991 to 82.2 km2 in 2022. Using NDWI, Landsat images from 1991 to 2021 depicted a strong association between the water reserve in Hassan Eddakhil dam in the upstream area and the LULC changes. The oases from the dam (upstream) to Er-Rissani (downstream) recorded high rates of decline with an increasing trend of desertification due to drought and overuse mainly of groundwater. The outputs of this research effort constitute a significant source of information that may be used to support further research and decision-makers to manage arid ecosystems and achieve the sustainable development goals (SDGs), precisely the SDGs 15 (Life on land).

<p>An adequate water supply is essential for the growth and development of crops. When rainfall is insufficient, irrigation is necessary to meet crop water needs. It is a crucial and strategic aspect of economic and social development. To combat climate change, there is a need to adopt irrigation management techniques that increase and stabilize agricultural production while saving water, using intelligent agricultural water technologies. Internet of things (IoT) based technologies can achieve optimal use of water resources. This article introduces a smart realtime irrigation management system based on the internet of things. It provides optimal management of irrigation decisions using real-time weather and soil moisture data, as well as data from precipitation forecasts. The proposed algorithm is developed in real-time based on the IoT, enabling us to guide irrigation and control the amount of water in agricultural applications. The system uses real-time data analysis of climate, soil, and crop data to provide flexible planning of the irrigation system’s use. A case study from the Fez-Meknes region in Morocco is presented to demonstrate the proposed system’s effectiveness</p>

Abstract The North African steppe areas represent a heritage of great economic and ecological importance. These areas, which were once prosperous, are currently experiencing significant degradation and a decrease in productivity due to several factors. The objective of this study was to evaluate the dynamics of the steppe vegetation, identify the responsible factors, and present perspectives for their management and restoration. The methodological approach adopted for the characterization of climatic and socioeconomic conditions and the analysis of vegetation dynamics combined classical geomatics methods with a data mining method by mobilizing several sources and on important temporal horizons. This study was optimized by using the Google Earth Engine platform. Results showed that steppe areas are characterized by their plant richness and great potential for resilience despite their low vegetation cover. The analysis of the dynamics of change has highlighted a regressive trend in steppe vegetation during the study period (1995–2020). This study has been able to highlight the extent of the dynamics of the steppes in the study area during the last 26 years and to identify the human activity as the main trigger for the transformation that steppe areas are currently undergoing. Such results improve our knowledge of these areas and open perspectives for their management.

<span lang="EN-US">As in Industry 4.0 era, the impact of the internet of things (IoT) on the advancement of the agricultural sector is constantly increasing. IoT enables automation, precision, and efficiency in traditional farming methods, opening up new possibilities for agricultural advancement. Furthermore, many IoT-based smart farming systems are designed based on fog and edge architecture. Fog computing provides computing, storage, and networking services to latency-sensitive applications (such as Agribots-agricultural robots-drones, and IoT-based healthcare monitoring systems), instead of sending data to the cloud. However, due to the limited computing and storage resources of fog nodes used in smart farming, designing a modules placement scheme for resources management is a major challenge for fog based smart farming applications. In this paper, our proposed module placement algorithm aims to achieve efficient resource utilization of fog nodes and reduce application <span>delay and network usage in Fog-based smart farming applications. To evaluate the efficacy of our proposal, the simulation was done using iFogSim. Results show that the proposed approach is able to achieve significant</span> reductions in latency and network usage.</span>

Firms strive to become agile as part of their organization’s transformation to face the changes spurred by the digital world. Thus, this study aims to provide new and insightful findings to assist firms in carrying out digital transformations through agility. We surveyed agility practitioners currently operating in companies undergoing or within digital transformation. Our findings suggest that agility and digital transformation are still in their early stages and that they may coexist. Moreover, the study supported that if agility is well-enabled, it can assist an organization's digital transformation by leveraging the following components, namely agile culture, collaboration, value-co-creation, experimentation, willingness to take risks, continuous improvement, and organizational learning, seizing market opportunities, competitiveness, and agile leadership. In addition, the study identified the pain points that companies encounter in this process, including employee resistance to change. Finally, the findings represent a first step toward a shared understanding of ways to carry out digital transformations through agility and serve to guide future research work while also assisting practitioners in implementing digital transformation effectively.

Drought is a powerful natural hazard that has significant effects on ecosystems amid the constant threats posed by climate change. This study investigates agricultural drought in a semi-arid Mediterranean basin through the interconnections among four indices: precipitation (meteorological reanalysis), vegetation development, thermal stress, and soil water deficit (remote sensing observations). While drought seems to be a clear concept with effective assessment tools (e.g., SPI and SPEI), the definition of drought periods is blurrier. This article examines the main drivers of agricultural drought, precipitation, soil moisture deficit, incipient vegetation development, and rising soil surface temperature. Their temporal connections in various agrosystems of the basin and the determination of drought periods by revisiting the run theory were investigated. The Pearson correlations at different spatial scales showed a medium to low level of agreement between the indices, which was explained by the geographical heterogeneity and the climatic variability between the agrosystems within the basin. It was also shown that the cascade of impacts expected from lower precipitations was revealed by the cross-correlation analysis. The connection between precipitation deficit and vegetation remains significant for at least one month for most pairs of indices, especially during drought events, suggesting that agricultural drought spells can be connected in time through the three or four selected indices. Short-, mid-, and long-term impacts of precipitation deficiencies on soil moisture, vegetation, and temperature were revealed. As expected, the more instantaneous variables of soil moisture and surface temperature showed no lag with precipitation. Vegetation anomalies at the monthly time step showed a two-month lag with a preceding effect of vegetation to precipitation. Finally, the determination of drought events and stages with varying thresholds on the run theory showed large variability in duration, magnitude, and intensity according to the choice of both normality and dryness thresholds.

La crise pandémique de Covid-19 a eu un impact profond sur le changement numérique à l'échelle mondiale. Elle a accéléré de nombreuses tendances numériques existantes et a suscité de nouvelles évolutions dans divers secteurs. La numérisation des entreprises, la digitalisation et l'e-commerce sont autant de principaux aspects du changement numérique. À ce propos, la digitalisation des entreprises est un processus continu intégrant activement dans tous les aspects de ses activités et de sa culture pour améliorer ses performances et sa compétitivité. En parallèle, l'e-commerce fondé sur la confiance en ligne consiste à mettre en place des plateformes digitales, ayant comme objectif, la vente des produits ou des services en ligne. À cet égard, notre problématique de recherche se focalise sur la question de savoir si la digitalisation a un impact significatif sur le secteur du commerce électronique. Pour ce faire, une analyse théorique et conceptuelle a été menée, en examinant les enjeux et les aspects théoriques tout en se basant sur une revue documentaire incluant des références au corpus théorique ainsi qu'à diverses études et rapports.