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   big genetic data analysis to predict features in cross-breeding to increase food yields  
   
نویسنده vij priya ,prashant patil manisha
منبع بيوتكنولوژي كشاورزي - 1403 - دوره : 16 - شماره : 4 - صفحه:237 -250
چکیده    Objectiveplant breeders (pb) have significantly improved agricultural output and quality by utilizing modern scientific and technological developments. costs have decreased and the pb process has quickened due to the development of genomic tools and sequencing, especially since the human genome project. addressing global issues pertaining to water resources and food security requires this progress. high-throughput phenotyping, precision agriculture, and crop-scouting have all been improved by the integration of cutting-edge technology such sensor systems, satellite images, robots, big data analytics, and genomics. these developments contribute to the growth of digital agriculture, which has the potential to transform pb by taking a more interdisciplinary approach. to examine the method by which new developments in digital agriculture, genomics, and sensor technologies are changing plant breeding, enhancing crop quality and productivity, and tackling global issues with water resource management and food security.resultsplant breeding has become faster and less expensive due to the combination of genetic tools, sequencing techniques, and contemporary agricultural technologies. precision agriculture has greatly increased high-throughput phenotyping and crop scouting, by using technology like robotics, big data analytics, and satellite photography. these developments aid in the creation of sustainable, more effective farming methods.conclusionsan innovative approach for crop improvement is being developed by the ongoing integration of multidisciplinary technologies in plant breeding. it is anticipated that enhanced genomics and digital agriculture would improve plant breeders’ capacities, allowing them to tackle the escalating problems of food and water security in a world that is becoming more interconnected by the day..
کلیدواژه big data ,cross breeding ,food yield ,prediction
آدرس kalinga university, department of cs & it, india, kalinga university, department of cs & it, india
پست الکترونیکی patil.manisha@kalingauniversity.ac.in
 
   big genetic data analysis to predict features in cross-breeding to increase food yields  
   
Authors vij priya ,prashant patil manisha
Abstract    objectiveplant breeders (pb) have significantly improved agricultural output and quality by utilizing modern scientific and technological developments. costs have decreased and the pb process has quickened due to the development of genomic tools and sequencing, especially since the human genome project. addressing global issues pertaining to water resources and food security requires this progress. high-throughput phenotyping, precision agriculture, and crop-scouting have all been improved by the integration of cutting-edge technology such sensor systems, satellite images, robots, big data analytics, and genomics. these developments contribute to the growth of digital agriculture, which has the potential to transform pb by taking a more interdisciplinary approach. to examine the method by which new developments in digital agriculture, genomics, and sensor technologies are changing plant breeding, enhancing crop quality and productivity, and tackling global issues with water resource management and food security.resultsplant breeding has become faster and less expensive due to the combination of genetic tools, sequencing techniques, and contemporary agricultural technologies. precision agriculture has greatly increased high-throughput phenotyping and crop scouting, by using technology like robotics, big data analytics, and satellite photography. these developments aid in the creation of sustainable, more effective farming methods.conclusionsan innovative approach for crop improvement is being developed by the ongoing integration of multidisciplinary technologies in plant breeding. it is anticipated that enhanced genomics and digital agriculture would improve plant breeders’ capacities, allowing them to tackle the escalating problems of food and water security in a world that is becoming more interconnected by the day..
Keywords big data ,cross breeding ,food yield ,prediction
 
 

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