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Artificial Intelligence in Agriculture 2023年第3期9卷 46-60页

作者： Sèton Calmette Ariane Houetohossou Vinasetan Ratheil Houndji Castro Gbêmêmali Hounmenou Rachidatou Sikirou Romain Lucas Glele Kakaï Laboratoire de Biomathématiques et d'Estimations Forestières Faculty of Agronomic SciencesUniversity of Abomey-Calavi04 BP 1525CotonouBenin Institut de Formation et de Recherche en Informatique University of Abomey-Calavi01 BP 526CotonouBenin Laboratoire de Défense des Cultures Centre de Recherches Agricoles d'AgonkanmeyInstitut National des Recherches Agricoles du Bénin(INRAB)01 BP 884CotonouBenin

Deep Learning(DL),a type of Machine Learning,has gained significant interest in many fields,including agriculture.This paper aims to shed light on deep learning techniques used in agriculture for abiotic and biotic stress detection in fruits and vegetables,their benefits,and the challenges faced by users.Scientific papers were collected from Web of Science,Scopus,Google Scholar,Springer,and Directory of Open Access Journals(DOAJ)using combinations of specific keywords such as:’Deep Learning’OR’Artificial Intelligence’in combination with fruit disease’,vegetable disease’,‘fruit stress',OR‘vegetable stress'following PRISMA guidelines.From the initial 818 papers identified using the keywords,132 were reviewed after excluding books,reviews,and the irrelevant.The recovered scientific papers were from 2003 to 2022;93%addressed biotic stress on fruits and vegetables.The most common biotic stresses on species are fungal diseases(grey spots,brown spots,black spots,downy mildew,powdery mildew,and anthracnose).Few studies were interested in abiotic stresses(nutrient deficiency,water stress,light intensity,and heavy metal contamination).Deep Learning and Convolutional Neural Networks were the most used keywords,with GoogleNet(18.28%),ResNet50(16.67%),and VGG16(16.67%)as the most used architectures.Fifty-two percent of the data used to compile these models come from the fields,followed by data obtained online.Precision problems due to unbalanced classes and the small size of some databases were also analyzed.We provided the research gaps and some perspectives from the reviewed papers.Further research works are required for a deep understanding of the use of machine learning techniques in fruit and vegetable studies:collection of large datasets according to different scenarios on fruit and vegetable diseases,evaluation of the effect of climatic variability on the fruit and vegetable yield using AI methods and more abiotic stress studies.

关键词： Deep learning Prediction Fruits Vegetables Stress agricultural yield

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Strategies to mitigate the adverse effect of drought stress on crop plants-influences of soil bacteria:A review

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Pedosphere 2021年第3期31卷 496-509页

作者： Priyanka CHANDRA Amoolya WUNNAVA Pooja VERMA Amaresh CHANDRA Rakesh Kumar SHARMA Indian Council of agricultural Research(ICAR) Central Soil Salinity Research InstituteKarnalHaryana 132001India Department of Biosciences Manipal University JaipurRajasthanJaipur 303007India Indian Council of agricultural Research(ICAR) Indian Institute of Sugarcane ResearchUttar PradeshLucknow 226002India

Drought stress affects plant growth and causes significant issues in meeting global demand for food crops and fodder.Drought can cause physiological,physicochemical,and morphological changes in plants,which negatively affects plant growth and productivity.To combat this under the increasing global threat of water shortage and rapid population expansion,it is crucial to develop strategies to meet global food demands.Plant growth-promoting rhizobacteria(PGPR)may provide a safe solution to enhancing crop yields through various mechanisms.These soil bacteria can provide drought tolerance to crop plants,allowing them to survive and thrive in water-scarce conditions.Productions of phytohormones,free radical-scavenging enzymes,and stress-combating enzymes that can increase tolerance to drought-induced stress are key features of plant-associated microbial communities.This review summarizes the beneficial properties of microbes that help plants tolerate water scarcity and highlights the bacterial mechanisms that enhance drought tolerance in plants.

关键词： abiotic stress agricultural yield drought tolerance food crops microbe PGPR rhizobactoria water deficit

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The Impact of Water Scarcity on Food Security in Iraq

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Journal of Civil Engineering and Architecture 2023年第9期17卷 441-456页

作者： Varoujan K.Sissakian Nadhir Al-Ansari Nasrat Adamo Jan Laue Komar University of Science and Technology Sulaymaniyah 46004Iraq Lulea University of Technology Lulea 97187Sweden Sågaregränd 3 Norrköping 60358Sweden

Iraq is part of the Fertile Crescent with the two large rivers:Tigris and Euphrates and their tributaries that secure the required quantity and quality of water to the Iraqi population for their different uses;including agriculture,industry,and other domestic requirements.During the last decades,however,the quantity and quality of water in these rivers decreased causing water scarcity in the country.This scarcity is having severe impacts on food security in Iraq since large cultivated areas in different parts of the country that grow different agricultural products have been abandoned due to lack of water.The worsening situation is attributed mainly to global climate changes including decreasing rainfall amounts,increase in air temperature,and insufficient water inflows in the two main rivers and their tributaries.This last issue is exasperated by the unfair water sharing policies of the riparian countries namely Turkey and Iran.In writing this article relevant data from different sources were used.Numerous published reports and papers dealing with this important issue were consulted,while at the same time,the long experience of the authors in these very important issues was also drawn upon to elucidate the difficulties that are current today and those expected in the future in this field.

关键词： Water scarcity food security agricultural yield global change dry marshes fertile crescent.

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