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Sensors in Agriculture

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ISBN: 9783038974123 / 9783038974130 Year: Pages: 346 DOI: 10.3390/books978-3-03897-413-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Sensors in Agriculture

Author:
ISBN: 9783038977445 / 9783038977452 Year: Pages: 354 DOI: 10.3390/books978-3-03897-745-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-06-26 08:44:06
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Abstract

Agriculture requires technical solutions for increasing production while lessening environmental impact by reducing the application of agro-chemicals and increasing the use of environmentally friendly management practices. A benefit of this is the reduction of production costs. Sensor technologies produce tools to achieve the abovementioned goals. The explosive technological advances and developments in recent years have enormously facilitated the attainment of these objectives, removing many barriers for their implementation, including the reservations expressed by farmers. Precision agriculture and ‘smart farming’ are emerging areas where sensor-based technologies play an important role. Farmers, researchers, and technical manufacturers are joining their efforts to find efficient solutions, improvements in production, and reductions in costs. This book brings together recent research and developments concerning novel sensors and their applications in agriculture. Sensors in agriculture are based on the requirements of farmers, according to the farming operations that need to be addressed.

Keywords

wireless sensor network (WSN) --- Wi-SUN --- vine --- mandarin orange --- thermal image --- fluorescent measurement --- X-ray fluorescence spectroscopy --- visible and near-infrared reflectance spectroscopy --- heavy metal contamination --- spectral pre-processing --- feature selection --- machine-learning --- LiDAR --- light-beam --- plant localization --- Kinect --- leaf area index --- radiative transfer model --- neural networks --- GF-1 satellite --- wide field view --- big data --- geo-information --- plant phenotyping --- grapevine breeding --- Vitis vinifera --- ambient intelligence --- wireless sensor --- fuzzy logic --- smart irrigation --- virtual organizations of agents --- CIE-Lab --- precision plant protection --- optical sensor --- weed control --- classification --- NIR hyperspectral imaging --- chemometrics analysis --- weeds --- UAS --- RPAS --- one-class --- machine learning --- remote sensing --- geoinformatics --- plant disease --- pest --- deep convolutional neural networks --- real-time processing --- detection --- hyperspectral imaging --- soil type classification --- total nitrogen --- texture features --- data fusion --- Fusarium --- near-infrared --- spectroscopy --- hulled barely --- partial least squares-discriminant analysis --- remote sensing --- precision agriculture --- crop monitoring --- data fusion --- speckle --- diffusion --- scattering --- biological sensing --- apparent soil electrical conductivity --- ECa-directed soil sampling --- electromagnetic induction --- proximal sensor --- response surface sampling --- salt tolerance --- boron tolerance --- soil mapping --- soil salinity --- spatial variability --- irrigation --- energy balance --- water management --- semi-arid regions --- on-line vis-NIR measurement --- total nitrogen --- total carbon --- spiking --- gradient boosted machines --- artificial neural networks --- random forests --- rice --- striped stem-borer --- hyperspectral imaging --- texture feature --- data fusion --- greenhouse --- wireless sensor network --- data fusion --- dynamic weight --- dataset --- agriculture --- obstacle detection --- computer vision --- cameras --- stereo imaging --- thermal imaging --- LiDAR --- radar --- object tracking --- crop area --- remote sensing image classification --- area frame sampling --- stratification --- regression estimator --- agriculture --- meat spoilage --- vegetable oil --- quality assessment --- electronic nose --- electrochemical sensors --- spectral analysis --- feature selection --- genetic algorithms --- classification --- vegetation indices --- vineyard --- diseases --- spatial data --- sensor --- data fusion --- change of support --- geostatistics --- precision agriculture --- management zones --- event detection --- back propagation model --- multivariate water quality parameters --- time-series data --- spatial-temporal model --- connected dominating set --- water supply network --- SS-OCT --- Capsicum annuum --- germination --- salt concentration --- deep learning --- clover-grass --- precision agriculture --- dry matter composition --- proximity sensing --- 3D reconstruction --- RGB-D sensor --- crop inspection platform --- water depth sensors --- soil moisture sensors --- temperature sensors --- rice field monitoring --- irrigation --- silage --- packing density --- moisture content --- compound sensor --- simultaneous measurement --- birth sensor --- bovine embedded hardware --- ambient intelligence --- virtual organizations of agents --- Fusarium --- near infrared --- discrimination --- hulled barely --- naked barley --- wheat --- dielectric probe --- apple shelf-life --- dielectric dispersion --- electronic nose --- pest scouting --- pest management --- gas sensor --- noninvasive detection --- nitrogen --- near infrared sensors --- drying temperature --- SPA-MLR --- PLS --- CARS --- hyperspectral camera --- handheld --- sensor evaluation --- case studies --- soil --- moisture --- sensor --- landslide --- rice leaves --- chromium content --- laser-induced breakdown spectroscopy --- laser wavelength --- preprocessing methods --- agricultural land --- field crops --- land cover --- photograph-grid method --- remote sensing --- data validation and calibration --- mobile app --- wireless sensor networks (WSN) --- energy efficiency --- distributed systems --- processing of sensed data --- WSN distribution algorithms --- recognition patterns --- agriculture

Plant Genetics and Molecular Breeding

Author:
ISBN: 9783039211753 / 9783039211760 Year: Pages: 628 DOI: 10.3390/books978-3-03921-176-0 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology
Added to DOAB on : 2019-08-28 11:21:27
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Abstract

The development of new plant varieties is a long and tedious process involving the generation of large seedling populations for the selection of the best individuals. While the ability of breeders to generate large populations is almost unlimited, the selection of these seedlings is the main factor limiting the generation of new cultivars. Molecular studies for the development of marker-assisted selection (MAS) strategies are particularly useful when the evaluation of the character is expensive, time-consuming, or with long juvenile periods. The papers published in the Special Issue “Plant Genetics and Molecular Breeding” report highly novel results and testable new models for the integrative analysis of genetic (phenotyping and transmission of agronomic characters), physiology (flowering, ripening, organ development), genomic (DNA regions responsible for the different agronomic characters), transcriptomic (gene expression analysis of the characters), proteomic (proteins and enzymes involved in the expression of the characters), metabolomic (secondary metabolites), and epigenetic (DNA methylation and histone modifications) approaches for the development of new MAS strategies. These molecular approaches together with an increasingly accurate phenotyping will facilitate the breeding of new climate-resilient varieties resistant to abiotic and biotic stress, with suitable productivity and quality, to extend the adaptation and viability of the current varieties.

Keywords

sugarcane --- cry2A gene --- particle bombardment --- stem borer --- resistance --- NPK fertilizers --- agronomic traits --- molecular markers --- quantitative trait loci --- common wild rice --- Promoter --- Green tissue-specific expression --- light-induced --- transgenic chrysanthemum --- WRKY transcription factor --- salt stress --- gene expression --- DgWRKY2 --- Cucumis sativus L. --- RNA-Seq --- DEGs --- sucrose --- ABA --- drought stress --- Aechmea fasciata --- squamosa promoter binding protein-like --- flowering time --- plant architecture --- bromeliad --- Oryza sativa --- endosperm development --- rice quality --- WB1 --- the modified MutMap method --- abiotic stress --- Cicer arietinum --- candidate genes --- genetics --- heat-stress --- molecular breeding --- metallothionein --- Brassica --- Brassica napus --- As3+ stress --- broccoli --- cytoplasmic male sterile --- bud abortion --- gene expression --- transcriptome --- RNA-Seq --- sesame --- genome-wide association study --- yield --- QTL --- candidate gene --- cabbage --- yellow-green-leaf mutant --- recombination-suppressed region --- bulk segregant RNA-seq --- differentially expressed genes --- marker–trait association --- haplotype block --- genes --- root traits --- D-genome --- genotyping-by-sequencing --- single nucleotide polymorphism --- durum wheat --- bread wheat --- complex traits --- Brassica oleracea --- Ogura-CMS --- iTRAQ --- transcriptome --- pollen development --- rice --- OsCDPK1 --- seed development, starch biosynthesis --- endosperm appearance --- Chimonanthus praecox --- nectary --- floral scent --- gene expression --- Prunus --- flowering --- bisulfite sequencing --- genomics --- epigenetics --- breeding --- AP2/ERF genes --- Bryum argenteum --- transcriptome --- gene expression --- stress tolerance --- SmJMT --- transgenic --- Salvia miltiorrhiza --- overexpression --- transcriptome --- phenolic acids --- Idesia polycarpa var --- glycine --- FAD2 --- linoleic acid --- oleic acid --- anther wall --- tapetum --- pollen accumulation --- OsGPAT3 --- rice --- cytoplasmic male sterility (CMS) --- phytohormones --- differentially expressed genes --- pollen development --- Brassica napus --- Rosa rugosa --- RrGT2 gene --- Clone --- VIGS --- Overexpression --- Tobacco --- Flower color --- Anthocyanin --- sugarcane --- WRKY --- subcellular localization --- gene expression pattern --- protein-protein interaction --- transient overexpression --- soybean --- branching --- genome-wide association study (GWAS) --- near-isogenic line (NIL) --- BRANCHED1 (BRC1) --- TCP transcription factor --- Zea mays L. --- MADS transcription factor --- ZmES22 --- starch --- flowering time --- gene-by-gene interaction --- Hd1 --- Ghd7 --- rice --- yield trait --- Oryza sativa L. --- leaf shape --- yield trait --- molecular breeding --- hybrid rice --- nutrient use efficiency --- quantitative trait loci (QTLs), molecular markers --- agronomic efficiency --- partial factor productivity --- P. suffruticosa --- R2R3-MYB --- overexpression --- anthocyanin --- transcriptional regulation --- ethylene-responsive factor --- Actinidia deliciosa --- AdRAP2.3 --- gene expression --- waterlogging stress --- regulation --- Chrysanthemum morifolium --- WUS --- CYC2 --- gynomonoecy --- reproductive organ --- flower symmetry --- Hs1pro-1 --- cZR3 --- gene pyramiding --- Heterodera schachtii --- resistance --- tomato --- Elongated Internode (EI) --- QTL --- GA2ox7 --- n/a

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eng (3)


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2019 (3)