LEADER 05993nam 22008295 450 001 9911031561103321 005 20251001130539.0 010 $a3-031-99954-1 024 7 $a10.1007/978-3-031-99954-3 035 $a(CKB)41520952600041 035 $a(MiAaPQ)EBC32323418 035 $a(Au-PeEL)EBL32323418 035 $a(DE-He213)978-3-031-99954-3 035 $a(EXLCZ)9941520952600041 100 $a20251001d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEmpowering Wheat Cultivation with GIS, Digital Approaches and Artificial Intelligence /$fedited by Nusret Zencirci, Faheem Shehzad Baloch, Jin-Ying Gou, Velimir Mladenov, Sotirios Fragkostefanakis, Marta da Silva Lopes, Ephrem Habyarimana, Hakan Ulukan, Asuman Kaplan Evlice 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (426 pages) 225 1 $aBiomedical and Life Sciences Series 311 08$a3-031-99953-3 327 $aSecuring Wheat Cultivation for Global Food Safety -- Climate Change in Wheat (Triticum spp.) Under the Light of Remote Sensing, Digital Evolution, Artificial intelligence -- Geographic Information Systems, Remote Sensing, Agroecosystems, Global Databases and Agricultural Planning -- Big Data Utilisation In Wheat Genetic Resources -- High Throughput Phenotyping in Wheat -- Combination of High Throughput Phenotyping and Genomics in Precise Wheat Breeding -- Predictive Modeling of Wheat Production in Turkiye: A NARX Network Approach Incorporating Climatic and Economic Factors -- Weather Forecasting and State-of-the-art Soil Analysis in Irrigated Precision Wheat Production -- How Low-Cost UAVs Could Revolutionize Field Research as a Substitute for Traditional Agronomic Measurements in Crop Phenotyping? -- Perfecting Wheat Quality, Quality Analysis, and Production Processes via Digital and Artificial Intelligence Approaches -- Infrared Sensing for Wheat Biochemical Analysis: Methods and Protocols -- Modern Approaches to Wheat Diseases -- Weed Management Approaches with GIS, Digital Approaches and Artificial Intelligence in Wheat Cultivation -- Smart Farming for Sustainable Wheat Intensification. 330 $aThe global population is projected to exceed 9 billion by 2050, leading to imminent food shortages not only for the current but also future generations. Anticipated increases in appetite coming 50 years will pose significant challenges to food production. This demand will exert additional pressure on agriculture for the escalating need for food. On one hand, research indicates a 60% increase in food production is necessary to accommodate the projected 9 billion people, on the other hand, a substantial portion of the population is grappling with various micronutrient deficiencies, such as iron, zinc, iodine, vitamin A, and folic acid, a condition referred to as "hidden hunger." Hence, it is imperative to exert substantial efforts towards developing improved cultivars under enhanced technological conditions. Concerns about climate change are anticipated to profoundly affect soil water availability, carbon storage, and crop yields. Droughts in the Mediterranean and Africa are expected to worsen during certain seasons. Each year, climate change leads to substantial losses in agricultural production, with a worsening scenario in the future. Wheat breeding has witnessed significant advancements with the wheat genomics, whole-genome sequencing, high-throughput phenotyping, genome-editing technologies, and marker-assisted breeding. These enable genome-based breeding to produce higher enough yielding by 2050. Speed breeding has a crucial role in the incorporation of new genes into breeding pipelines, facilitating the creation of innovative homozygous advanced lines, and accelerating the identification and functional characterization of new genes. Climate change and recent technological advancements necessitate efficient utilization of remote sensing, digital tools, and artificial intelligence approaches, have gained prominence in wheat agriculture. This book aims to encompass both past and upcoming research activities in this domain. It serves as a valuable resource for wheat breeders interested in leveraging modern data technologies in their research endeavours. 410 0$aBiomedical and Life Sciences Series 606 $aAgriculture 606 $aPlant biotechnology 606 $aStress (Physiology) 606 $aPlants 606 $aPlant genetics 606 $aAutomatic control 606 $aRobotics 606 $aAutomation 606 $aAgriculture 606 $aPlant Biotechnology 606 $aPlant Stress Responses 606 $aPlant Genetics 606 $aControl, Robotics, Automation 615 0$aAgriculture. 615 0$aPlant biotechnology. 615 0$aStress (Physiology) 615 0$aPlants. 615 0$aPlant genetics. 615 0$aAutomatic control. 615 0$aRobotics. 615 0$aAutomation. 615 14$aAgriculture. 615 24$aPlant Biotechnology. 615 24$aPlant Stress Responses. 615 24$aPlant Genetics. 615 24$aControl, Robotics, Automation. 676 $a630 700 $aZencirci$b Nusret$01775444 701 $aBaloch$b Faheem Shehzad$01775443 701 $aGou$b Jin-Ying$01850700 701 $aMladenov$b Velimir$01850701 701 $aFragkostefanakis$b Sotirios$01850702 701 $ada Silva Lopes$b Marta$01850703 701 $aHabyarimana$b Ephrem$01069595 701 $aUlukan$b Hakan$01850704 701 $aKaplan Evlice$b Asuman$01850705 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911031561103321 996 $aEmpowering Wheat Cultivation with GIS, Digital Approaches and Artificial Intelligence$94443902 997 $aUNINA