LEADER 03041nam 2200637z- 450 001 9910557608003321 005 20231214133405.0 035 $a(CKB)5400000000045322 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/79682 035 $a(EXLCZ)995400000000045322 100 $a20202203d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEnhancing Farm-Level Decision Making through Innovation 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 electronic resource (84 p.) 311 $a3-0365-3355-9 311 $a3-0365-3356-7 330 $aNew information and knowledge are important aspects of innovation in modern farming systems. There is currently an abundance of digital and data-driven solutions that can potentially transform our food systems. At a time when the general public has concerns about how food is produced and the impact of farm production systems on the environment, strategies to increase public acceptance and the sustainability of food production are required more than ever. New tools and technology can provide timely insights into aspects such as nutrient profiles, the tracking of animal or plant wellbeing, and land-use options to enhance inputs and outputs associated with the farm business. Such solutions have the ultimate aim of enhancing production efficiency and contributing to the process of learning about the advantages of the innovation, while ensuring more sustainable food supplies. At the farm level, any new information needs to be in a useful format and beneficial for management and farm decision-making. The papers in this Special Issue evaluate agri-business innovation that can enhance farm-level decision-making. 606 $aResearch & information: general$2bicssc 606 $aBiology, life sciences$2bicssc 606 $aTechnology, engineering, agriculture$2bicssc 610 $adairy cows 610 $acomputer vision 610 $abehaviors 610 $amonitoring 610 $amanagement 610 $abehavior 610 $abirth 610 $aobservations 610 $asheep 610 $aproximal 610 $asensing 610 $aLiDAR 610 $aphotogrammetry 610 $agrasslands 610 $apastures 610 $aAdversarial-VAE 610 $atomato leaf disease identification 610 $aimage generation 610 $aconvolutional neural network 610 $apotato management 610 $atuber formation stage 610 $aprecipitation patterns 615 7$aResearch & information: general 615 7$aBiology, life sciences 615 7$aTechnology, engineering, agriculture 700 $aBell$b Matt J$4edt$01328686 702 $aBell$b Matt J$4oth 906 $aBOOK 912 $a9910557608003321 996 $aEnhancing Farm-Level Decision Making through Innovation$93038824 997 $aUNINA