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Molecular and Metabolic Mechanisms Associated with Fleshy Fruit Quality

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Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889452729 Year: Pages: 436 DOI: 10.3389/978-2-88945-272-9 Language: English
Publisher: Frontiers Media SA
Subject: Science (General) --- Botany --- Physiology
Added to DOAB on : 2018-02-27 16:16:44
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Abstract

Fleshy Fruits are a late acquisition of plant evolution. In addition of protecting the seeds, these specialized organs unique to plants were developed to promote seed dispersal via the contribution of frugivorous animals. Fruit development and ripening is a complex process and understanding the underlying genetic and molecular program is a very active field of research. Part of the ripening process is directed to build up quality traits such as color, texture and aroma that make the fruit attractive and palatable. As fruit consumers, humans have developed a time long interaction with fruits which contributed to make the fruit ripening attributes conform our needs and preferences. This issue of Frontiers in Plant Science is intended to cover the most recent advances in our understanding of different aspects of fleshy fruit biology, including the genetic, molecular and metabolic mechanisms associated to each of the fruit quality traits. It is also of prime importance to consider the effects of environmental cues, cultural practices and postharvest methods, and to decipher the mechanism by which they impact fruit quality traits. Most of our knowledge of fleshy fruit development, ripening and quality traits comes from work done in a reduced number of species that are not only of economic importance but can also benefit from a number of genetic and genomic tools available to their specific research communities. For instance, working with tomato and grape offers several advantages since the genome sequences of these two fleshy fruit species have been deciphered and a wide range of biological and genetic resources have been developed. Ripening mutants are available for tomato which constitutes the main model system for fruit functional genomics. In addition, tomato is used as a reference species for climacteric fruit which ripening is controlled by the phytohormone ethylene. Likewise, grape is a reference species for non-climacteric fruit even though no single master switches controlling ripening initiation have been uncovered yet. In the last period, the genome sequence of an increased number of fruit crop species became available which creates a suitable situation for research communities around crops to get organized and information to be shared through public repositories. On the other hand, the availability of genome-wide expression profiling technologies has enabled an easier study of global transcriptional changes in fruit species where the sequenced genome is not yet available. In this issue authors will present recent progress including original data as well as authoritative reviews on our understanding of fleshy fruit biology focusing on tomato and grape as model species.

Plant Innate Immunity 2.0

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ISBN: 9783038975809 Year: Pages: 386 DOI: 10.3390/books978-3-03897-581-6 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Biology --- Science (General)
Added to DOAB on : 2019-04-05 10:34:31
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Plants possess a rather complex and efficient immune system. During their evolutionary history, plants have developed various defense strategies in order to recognize and distinguishing between self and non-self, and face pathogens and animal pests. Accordingly, to study the plant innate immunity represents a new frontier in the plant pathology and crop protection fields. This book is structured in 6 sections. The first part introduces some basic and general aspects of the plant innate immunity and crop protection. Sections 2–5 focus on fungal and oomycete diseases (section 2), bacterial and phytoplasma diseases (section 3), virus diseases (section 4), and insect pests (section 5), with a number of case studies and plant–pathogen/pest interactions. The last section deals with plant disease detection and control. The book aims to highlight new trends in these relevant areas of plant sciences, providing a global perspective that is useful for future and innovative ideas.

Keywords

dieback --- disease management --- Lasiodiplodia theobromae --- mango --- pathogenicity --- Bromoviridae --- plant–virus interactions --- plant defense response --- Prune dwarf virus --- replication process --- systemic and local movement --- plant proteases --- plant immunity --- MTI --- ETI --- SAR --- ISR --- RNA silencing --- RTNLB --- Agrobacterium --- biotic stress responses --- calcium --- calcium signature --- calmodulin --- CMLs --- CDPKs --- plant immunity --- symbiosis --- cell wall --- cellulose synthase --- hypersensitive response --- pathogenesis related-protein 2 --- plant-virus interaction --- Potato virus Y --- ultrastructure --- aphid resistance --- Arabidopsis thaliana --- hydroperoxide lyase --- Macrosiphum euphorbiae --- Myzus persicae --- Solanum lycopersicum --- ?-3 fatty acid desaturase --- Arabidopsis --- azelaic acid --- glycerol-3-phosphate --- light dependent signalling --- methyl salicylate --- N-hydroxypipecolic acid --- pipecolic acid --- salicylic acid --- SAR signalling --- spectral distribution of light --- tobacco --- rice --- Chilo suppressalis --- mitogen-activated protein kinase 4 --- jasmonic acid --- salicylic acid --- ethylene --- herbivore-induced defense response --- downy mildew --- grapevine --- PRRs --- PTI --- VaHAESA --- bismerthiazol --- rice --- induced defense responses --- chemical elicitors --- Sogatella furcifera --- defense-related signaling pathways --- tomato gray mold --- tomato leaf mold --- Bacillus subtilis --- biological control --- Capsicum annuum --- Ralstonia solanacearum --- CaWRKY40b --- immunity --- negative regulator --- transcriptional modulation --- Capsicum annuum --- CaWRKY22 --- immunity --- Ralstonia Solanacearum --- WRKY networks --- metabolomics --- plant defence --- plant–microbe interactions --- priming --- pre-conditioning --- citrus decline disease --- Citrus sinensis --- Bakraee --- “Candidatus Liberibacter” --- “Candidatus Phytoplasma” --- microbiota --- innate immunity --- basal defense --- rice blast --- Magnaporthe oryzae --- proteomics --- iTRAQ --- candidate disease resistance gene --- disease resistance --- downy mildew --- garden impatiens --- leaf transcriptome --- New Guinea impatiens --- RNA-Seq --- polyphenol oxidase --- Camellia sinensis --- Ectropis obliqua --- wounding --- regurgitant --- rice --- OsGID1 --- gibberellin --- herbivore-induced plant defenses --- Nilaparvata lugens --- plant protection products --- agrochemicals --- sustainable crop protection --- food security

Salinity Tolerance in Plants

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ISBN: 9783039210268 / 9783039210275 Year: Pages: 422 DOI: 10.3390/books978-3-03921-027-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Biochemistry
Added to DOAB on : 2019-06-26 10:09:00
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Salt stress is one of the most damaging abiotic stresses because most crop plants are susceptible to salinity to different degrees. According to the FAO, about 800 million Has of land are affected by salinity worldwide. Unfortunately, this situation will worsen in the context of climate change, where there will be an overall increase in temperature and a decrease in average annual rainfall worldwide. This Special Issue presents different research works and reviews on the response of plants to salinity, focused from different points of view: physiological, biochemical, and molecular levels. Although an important part of the studies on the response to salinity have been carried out with Arabidopsis plants, the use of other species with agronomic interest is also notable, including woody plants. Most of the conducted studies in this Special Issue were focused on the identification and characterization of candidate genes for salt tolerance in higher plants. This identification would provide valuable information about the molecular and genetic mechanisms involved in the salt tolerance response, and it also supplies important resources to breeding programs for salt tolerance in plants.

Keywords

Arabidopsis --- Brassica napus --- ion homeostasis --- melatonin --- NaCl stress --- nitric oxide --- redox homeostasis --- Chlamydomonas reinhardtii --- bZIP transcription factors --- salt stress --- transcriptional regulation --- photosynthesis --- lipid accumulation --- Apocyni Veneti Folium --- salt stress --- multiple bioactive constituents --- physiological changes --- multivariate statistical analysis --- banana (Musa acuminata L.) --- ROP --- genome-wide identification --- abiotic stress --- salt stress --- MaROP5g --- rice --- genome-wide association study --- salt stress --- germination --- natural variation --- Chlamydomonas reinhardtii --- salt stress --- transcriptome analysis --- impairment of photosynthesis --- underpinnings of salt stress responses --- chlorophyll fluorescence --- J8-1 plum line --- mandelonitrile --- Prunus domestica --- redox signalling --- salicylic acid --- salt-stress --- soluble nutrients --- Arabidopsis thaliana --- VOZ --- transcription factor --- salt stress --- transcriptional activator --- chlorophyll fluorescence --- lipid peroxidation --- Na+ --- photosynthesis --- photosystem --- RNA binding protein --- nucleolin --- salt stress --- photosynthesis --- light saturation point --- booting stage --- transcriptome --- grapevine --- salt stress --- ROS detoxification --- phytohormone --- transcription factors --- Arabidopsis --- CDPK --- ion homeostasis --- NMT --- ROS --- salt stress --- antioxidant enzymes --- Arabidopsis thaliana --- ascorbate cycle --- hydrogen peroxide --- reactive oxygen species --- salinity --- SnRK2 --- RNA-seq --- DEUs --- flax --- NaCl stress --- EST-SSR --- Salt stress --- Oryza sativa --- proteomics --- iTRAQ quantification --- cell membrane injury --- root activity --- antioxidant systems --- ion homeostasis --- melatonin --- salt stress --- signal pathway --- SsMAX2 --- Sapium sebiferum --- drought, osmotic stress --- salt stress --- redox homeostasis --- strigolactones --- ABA --- TGase --- photosynthesis --- salt stress --- polyamines --- cucumber --- abiotic stresses --- high salinity --- HKT1 --- halophytes --- glycophytes --- poplars (Populus) --- salt tolerance --- molecular mechanisms --- SOS --- ROS --- Capsicum annuum L. --- CaDHN5 --- salt stress --- osmotic stress --- dehydrin --- Gossypium arboretum --- salt tolerance --- single nucleotide polymorphisms --- association mapping. --- n/a

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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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

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