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778 results for “Tomato”
Climate and Crop variables of tomato greenhouse simulation
<p>Climate and growth variables of a simulated tomato greenhouse are shown.</p> <p>Description of columns:</p> <p>----------------------------------</p> <p>'DateTime' : Time Stamp [dd-MM-yyyy hh:mm:ss]</p> <p>'Cppm' : outdoor Concentration of CO2 [ppm]</p> <p>'Wind' : wind velocity [m/s]</p> <p>'HR' : exterior relative humidity [%]</p> <p>'Rad' : exterior radiation [W/m^2]</p> <p>'Temp' : outdoor temperature [K]</p> <p>'Temp__Tcover' : temperature of cover [K]</p> <p>'Temp__Tair' : temperature of air [K]</p> <p>'Temp__Tfloor' : temperature of floor [K]</p> <p>'Temp__Tsoil' : temperature of soil [K]</p> <p>'QT__QT' : heat loss of crop by evapotranspiration [W]</p> <p>'QS__R_int' : Indoor Radiation [W/m^2]</p> <p>'Gas__C_w' : Absolute Humidity [kg/m^3]</p> <p>'Gas__C_c' : CO2 Concentration [kg/m^3]</p> <p>'Gas__rho_i' : Air density [kg/m^3]</p> <p>'Gas__C_c_ppm' : CO2 Concentration [ppm]</p> <p>'Gas__HRInt' : Indoor relative humidity [%]</p> <p>'R' : Ratio of ventilation [1/s]</p> <p>'Windows__value' : percent open window [%]</p> <p>'Screen__value' : percent open screen [%]</p> <p>'Carbon__Cbuff' : dry carbon in buffer by square meter of cultivation [kg/m^2]</p> <p>'Carbon__Cfruit' : dry carbon in fruit by square meter of cultivation [kg/m^2]</p> <p>'Carbon__Cleaf' : dry carbon in leaf by square meter of cultivation [kg/m^2]</p> <p>'Carbon__Cstem' : dry carbon in stem by square meter of cultivation [kg/m^2]</p> <p>'Tsum' : Acumulative temperature [ºC day]</p> <p>'C_Total' : total dry carbon by square meter of cultivation [kg/m^2]</p> <p>'WC' : water capacity of crop [kg/m^2]</p> <p>'LAI' : leaf area index [-]</p> <p>'CC' : CO2 flux from crop to air</p> <p>'VPD' : Vapor pressure deficit [Pa]</p> <p>'Water__WaterFlows__WaterUptake' : Water uptake of crop by square meter of cultivation [kg/(sm^2)]</p> <p><br> </p>
Breeding tomato flavor: modeling consumer preferences of tomato landraces (raw data)
<p>Raw dataset associated with the publication:</p> <p><strong>Breeding tomato flavor: modeling consumer preferences of tomato landraces.</strong></p> <p>Villena, J.<sup>a</sup>, Moreno, C.<sup>a</sup>, Roselló, S.<sup>b</sup>, Beltran, J.<sup> c</sup>, Cebolla-Cornejo, J.<sup>d</sup>, Moreno, M.M.<sup>a*</sup></p> <p><em><sup>a</sup></em><em>University of Castilla-La Mancha, Higher Technical School of Agricultural Engineering in Ciudad Real, Ronda de Calatrava 7, 13071, Ciudad Real, Spain</em></p> <p><em><sup>b</sup></em><em>Joint Research Unit UJI-UPV ‐ Improvement of agri‐food quality. Agricultural Sciences and Natural Environment Department, Universitat Jaume I, Avda. Sos Baynat s/n, 12071 Castelló de la Plana, Spain</em></p> <p><em><sup>c </sup></em><em>Research Institute for Pesticides and Water (IUPA).</em> <em>Universitat Jaume I, Avda. </em><em>Sos Baynat s/n, 12071 Castelló de la Plana, Spain</em></p> <p><em><sup>d</sup></em><em>Joint Research Unit UJI-UPV ‐ Improvement of agri‐food quality. </em><em>COMAV. Universitat Politècnica de València, Cno. de Vera s/n, 46022 València, Spain</em></p> <p>*Corresponding author</p> <p> </p> <p> </p> <p>To be published in the journal Scientia horticulturae</p>
Figure 7. The outcomes of the Monitoring and Control of the Greenhouse soil and climate Conditions for tomato crops-Design and Development a Control and Monitoring System for Greenhouse Conditions Based-On Multi Agent System
<p>In the past generation greenhouses it was enough to have one cabled measurement point in<br> the middle to provide the information to the greenhouse automation system. The system itself was<br> usually simple without opportunities to control locally heating, lights, ventilation or some other<br> activity, which was affecting the greenhouse interior climate. The optimal greenhouse climate and<br> soil adjustment can enable us to improve productivity and to achieve remarkable energy savings. In<br> this paper we proposed a multi-agent methodology for integrated management systems in<br> greenhouses. In this regards wireless sensor networks play a vital role to monitor greenhouse and<br> environment parameters. Each controlled process of the greenhouse environment is modeled as an<br> autonomous agent with its own inputs, its own outputs and its own interactions with the other<br> agents. Each agent acts autonomously, as it knows a priori the desired environmental set-points. In<br> this way, any possible conflicting decisions of conventional environmental control methodologies<br> are resolved through negotiations between the agents so that the possible optimal integrated solution<br> is achieved. The developed system is simple, cost effective, and easily installable.</p>
LAB4SUPPLY- WEEKLY PRICES TOMATO IN SPAIN
<p>Weekly prices received by the producer and paid by the consumer for the period 2012-2022. Product: tomato</p>
Figure 5 in Hydrogen peroxide is involved in drought stress long-distance signaling controlling early stomatal closure in tomato plants
Figure 5. Growth analysis of shoots and roots of tomato BS II0020 grown under irrigated or drought conditions. (A) fresh weight; (b) dry weight; (c) foliar area; (d) height. Control plants received full irrigation throughout the experiment. The values are the means of each treatment (n= 4), followed by the standard error. The letters over the bars represent the differences in the means between biochemical treatments within each condition, and the asterisks the differences of the same biochemical treatment between the conditions, calculated by Scott-knott test at 5% probability.
Figure 4 in Hydrogen peroxide is involved in drought stress long-distance signaling controlling early stomatal closure in tomato plants
Figure 4. Open stomata (a) and water loss by detached leaves (b) of tomato BS II0020. The values are the means of each treatment (n= 4), followed by the standard error. The letters over the bars represent the differences in the means among biochemical treatments within each condition, and the asterisks the differences of the same biochemical treatment between the conditions, calculated by Scott-knott test at 5% probability.
Figure 1 in Hydrogen peroxide is involved in drought stress long-distance signaling controlling early stomatal closure in tomato plants
Figure 1. Growth analysis of tomato BS II0020 grown in split-root scheme under full or partial irrigation. (a) fresh weight; (b) dry weight; (c) foliar area; (d) height. Control plants received full irrigation throughout the experiment. The values are the means of each treatment (n= 4), followed by the standard error. The letters over the bars represent the differences in the means between biochemical treatments within each condition, and the asterisks the differences of the same biochemical treatment between the conditions, calculated by Scott-knott test at 5% probability.
Figure 7 in Hydrogen peroxide is involved in drought stress long-distance signaling controlling early stomatal closure in tomato plants
Figure 7. Schematic representation of the proposed model for the role of H 2O2 in drought stress responses in tomato plants before and after the decline in shoot turgor. Thus, when there is a mild drought stress, the H O produced by the roots can travel to the shoot 2 2 where it will induce stomatal closure and thus reduce water loss, even before there is a reduction in the leaves water status. On the other hand, when drought stress becomes severe, other signals become part of the drought response complex, such as hormones, pH changes and electrical current, among others. Currently, H O appears to exert a lesser effect on drought signaling. *Several signals, such 2 2 as hormones, chemical elements, reactive nitrogen species, electrical currents, hydraulic signals and pH changes (Christmann et al., 2013; Silva et al., 2015; Karuppanapandian et al., 2017; Huber et al., 2019; Fichman and Mittler, 2020; Mahmood et al., 2020).
Figure 3 in Hydrogen peroxide is involved in drought stress long-distance signaling controlling early stomatal closure in tomato plants
Figure 3. Water relations of tomato BS II0020 grown in split-root scheme under full or partial irrigation. (a) relative water content; (b) total transpiration of plants throughout the evaluation period; (c) transpiration per cm2 of leaf area; (d) water use efficiency. Control plants received full irrigation throughout the experiment. The values are the means of each treatment (n= 4), followed by the standard error. The letters over the bars represent the differences in the means among biochemical treatments within each condition, and the asterisks the differences of the same biochemical treatment between the conditions, calculated by Scott-knott test at 5% probability.
Figure 1 in Methods of application of salicylic acid as attenuator of salt stress in cherry tomato
Figure 1. Air temperature (maximum and minimum) and mean relative air humidity observed in the internal area of the greenhouse during the experimental period.
Figure 2 in Methods of application of salicylic acid as attenuator of salt stress in cherry tomato
Figure 2. Two-dimensional projection of the scores of the principal components for the factors salinity levels (S) and methods of application of salicylic acid (M) (A) and the variables analyzed (B) in the first two principal components (PC and PC ).
Figure 10 in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 10. Nucleotide sequence alignment of the ITS (ITS1, 5.8S rDNA and ITS4) region of the C. sphaerospermum isolate 10 and the other isolates already recorded in NCBI.
Figure 8 in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 8. Nucleotide sequence alignment of the ITS (ITS1, 5.8S rDNA and ITS4) region of the C. sphaerospermum isolate 9 and the other isolates already recorded in NCBI.
Figure 5. A phylogenetic tree was generated using the neighbor-joining method which shows the genetic relationship between C. sphaerospermum 2 in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 5. A phylogenetic tree was generated using the neighbor-joining method which shows the genetic relationship between C. sphaerospermum 2 (as indicated in red circle) and the other C. sphaerospermum isolates deposited in GenBank (NCBI)
Figure 3. A in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 3. A phylogenetic tree constructed by the neighbor-joining method depending on a comparison of the nucleotide sequences obtained from the C. sphaerospermum isolates (1-13).
Figure 2 in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 2. The similarity and difference in the nucleotide sequences of the C. sphaerospermum isolates (1-13) identified in the present study. Similar nucleotides are stated in dots. Numbers given on the right side of the figure represent the nucleotide sequences obtained from the C. sphaerospermum isolates.
Figure 1. 1 in Morphological and molecular identification of Cladosporium sphaerospermum isolates collected from tomato plant residues
Figure 1. 1% Agarose gel electrophoresis of PCR products amplified using the primer pair ITS1 and ITS4 from the C. sphaerospermum isolates (1-13) obtained from tomato plant residues collected from different regions of Najaf and Karbala provinces. M: 1Kbp DNA Ladder (Promega, USA).
Fig. 1 in Impacts of azadirachtin and chlorantraniliprole on the developmental stages of pirate bug predators (Hemiptera: Anthocoridae) of the tomato pinworm Tuta absoluta (Lepidoptera: Gelechiidae)
Fig. 1. Longevity (days ± SE) of nymphs of Amphiareus constrictus exposed to azadirachtin and chlorantraniliprole via three routes of exposure (ingestion, residue contact and direct spray). *Comparison between two bars is statistically significant (t-test, P <0.05).
Fig. 4 in Impacts of azadirachtin and chlorantraniliprole on the developmental stages of pirate bug predators (Hemiptera: Anthocoridae) of the tomato pinworm Tuta absoluta (Lepidoptera: Gelechiidae)
Fig. 4. Proportion of nymphs of Blaptostethus pallescens that reached the adult stage afer early exposure to azadirachtin and chlorantraniliprole via three routes of exposure (ingestion, residue contact and direct spray). *Comparison between two bars is statistically significant (survival analysis/log rank test, P <0.05).
Fig. 1 in First report of economic injury to tomato due to Zeugodacus tau (Diptera: Tephritidae): relative abundance and effects of cultivar and season on injury
Fig. 1. Seasonal pattern of Zeugodacus tau male adults (mean ± SE) captured by Cue-lure-based traps in tomato in (a) season 1, and (b) season 2.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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