22 pages, The objective of this study was to provide a comprehensive overview of the recent advancements in the use of deep learning (DL) in the agricultural sector. The author conducted a review of studies published between 2016 and 2022 to highlight the various applications of DL in agriculture, which include counting fruits, managing water, crop management, soil management, weed detection, seed classification, yield prediction, disease detection, and harvesting. The author found that DL’s ability to learn from large datasets has great promise for the transformation of the agriculture industry, but there are challenges, such as the difficulty of compiling datasets, the cost of computational power, and the shortage of DL experts. The author aimed to address these challenges by presenting his survey as a resource for future research and development regarding the use of DL in agriculture.
16 pages, Climate change is impacting the ecological, social and technological aspects of urban gardens. Gardens experience threats (e.g., water scarcity) but are also responding through adaptation strategies (e.g., selecting drought-resilient plants). A synthetic overview of how urban gardens are affected by climate change and responding to climate change is unclear. Here, we systematically reviewed articles and book chapters published in the last two decades (2000–2022) to illustrate the relationship between climate change and urban gardening. From 72 documents analyzed with Nvivo Software, we found that there has been an increase in academic publications. Universities from the US (14) and Germany (9) universities are the dominant producers. Evidence shows that climate change can have negative impacts on cities, people and urban food. Suggestions on how to build the adaptation capacity of urban gardens include collecting rainwater, changing plant selection, changing planting times, applying vegetative cover on the soil and other practices. For cities, community and allotment gardens are helpful for adaptation, mitigation and resilience. This includes the capacity to regulate the microclimate, to reduce urban heat island effects and to buffer urban floods, the power to capture carbon, the ability to create social networks and other socio-environmental benefits for urban climate planning.
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