Fruit water content as an indication of sugar metabolism improves simulation of carbohydrate accumulation in tomato fruit

Abstract Although fleshy fruit is mainly made up of water, little is known about the impact of its water status on sugar metabolism and its composition. In order to verify whether fruit water status is an important driver of carbohydrate composition in tomato fruit, an adaptation of the SUGAR model proposed previously by M. Génard and M. Souty was used. Two versions of the model, with or without integrating the influence of fruit water content on carbohydrate metabolism, were proposed and then assessed with the data sets from two genotypes, Levovil and Cervil, grown under different conditions. The results showed that, for both genotypes, soluble sugars and starch were better fitted by the model when the effects of water content on carbohydrate metabolism were taken into consideration. Water content might play a regulatory role in the carbon metabolism from sugars to compounds other than sugars and starch in Cervil fruit, and from sugars to starch in Levovil fruit. While water content influences tomato fruit carbohydrate concentrations by both metabolism and dilution/dehydration effects in the early developmental stage, it is mainly by dilution/dehydration effects in the late stage. The possible mechanisms underlying the effect of the fruit water content on carbohydrate metabolism are also discussed.

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Modification of Carbohydrate Content in Developing Tomato Fruit

HortScience ◽

10.21273/hortsci.32.3.551e ◽

1997 ◽

Vol 32 (3) ◽

pp. 551E-551

Author(s):

Arthur A. Schaffer ◽

Marina Petreikov ◽

Daphne Miron ◽

Miriam Fogelman ◽

Moshe Spiegelman ◽

...

Keyword(s):

Carbohydrate Metabolism ◽

Metabolic Pathways ◽

Tomato Fruit ◽

Starch Synthesis ◽

Mature Fruit ◽

Immature Fruit ◽

Natural Genetic Variation ◽

Structural Carbohydrate ◽

Source Sink ◽

The Impact

The carbohydrate economy of developing tomato fruit is determined by wholeplant source–sink relationships. However, the fate of the imported photoassimilate partitioned to the fruit sink is controlled by the carbohydrate metabolism of the fruit tissue. Within the Lycopersicon spp. there exists a broad range of genetic variability for fruit carbohydrate metabolism, such as sucrose accumulation and modified ratios of fructose to glucose in the mature fruit and increased starch synthesis in the immature fruit. Metabolic pathways of carbohydrate metabolism in tomatoes, as well as natural genetic variation in the metabolic pathways, will be described. The impact of sink carbohydrate metabolism on fruit non-structural carbohydrate economy will be discussed.

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Burkholderia phytofirmans PsJN Acclimates Grapevine to Cold by Modulating Carbohydrate Metabolism

Molecular Plant-Microbe Interactions ◽

10.1094/mpmi-09-11-0245 ◽

2012 ◽

Vol 25 (4) ◽

pp. 496-504 ◽

Cited By ~ 107

Author(s):

Olivier Fernandez ◽

Andreas Theocharis ◽

Sophie Bordiec ◽

Regina Feil ◽

Lucile Jacquens ◽

...

Keyword(s):

Carbohydrate Metabolism ◽

Chlorophyll Concentration ◽

Soluble Sugars ◽

Net Photosynthesis ◽

Plant Growth Promoting Rhizobacteria ◽

Plant Growth Promoting ◽

Induced Tolerance ◽

Long Term Impact ◽

The Impact ◽

Burkholderia Phytofirmans Psjn

Low temperatures damage many temperate crops, including grapevine, which, when exposed to chilling, can be affected by symptoms ranging from reduced yield up to complete infertility. We have previously demonstrated that Burkholderia phytofirmans PsJN, a plant growth-promoting rhizobacteria (PGPR) that colonizes grapevine, is able to reduce chilling-induced damage. We hypothesized that the induced tolerance may be explained at least partly by the impact of bacteria on grapevine photosynthesis or carbohydrate metabolism during cold acclimation. To investigate this hypothesis, we monitored herein the fluctuations of photosynthesis parameters (net photosynthesis [Pn], intercellular CO2 concentration, stomatal conductances, ΦPSII, and total chlorophyll concentration), starch, soluble sugars (glucose, fructose, saccharose, mannose, raffinose, and maltose), and their precursors during 5 days of chilling exposure (4°C) on grapevine plantlets. Bacterization affects photosynthesis in a non–stomatal dependent pattern and reduced long-term impact of chilling on Pn. Furthermore, all studied carbohydrates known to be involved in cold stress tolerance accumulate in non-chilled bacterized plantlets, although some of them remained more concentrated in the latter after chilling exposure. Overall, our results suggest that modification of carbohydrate metabolism in bacterized grapevine plantlets may be one of the major effects by which this PGPR reduces chilling-induced damage.

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The Method of Plant Water Status Measurement in Sweet Potato (Ipomoea Batatas (L) Lam.)

Beccariana Botanical Research Bulletin ◽

10.30862/bbrp.v7i1.274 ◽

2010 ◽

Vol 7 (1) ◽

Author(s):

Saraswati Prabawardani

Keyword(s):

Water Content ◽

Sweet Potato ◽

Relative Water Content ◽

Water Status ◽

Plant Water Status ◽

Equilibration Time ◽

Plant Water ◽

Font Size ◽

Potato Leaf ◽

Relative Water

The measurement of plant water status such as leaf water potential (LWP) and leaf relative water content (RWC) is important part of understanding plant physiology and biomass production. Preliminary study was made to determine the optimum amount of leaf abrasion and equilibration time of sweet potato leaf inside the thermocouple psychrometer chambers. Based on the trial, the standard equilibration time curve of a Peltier thermocouple for sweet potato leaf was between 2 and 3 hours. To increase the water vapour conductance across the leaf epidermis the waxy leaf cuticle should be removed or broken by abrasion. The result showed that 4 times leaf rubbings was accepted as the most effective way to increase leaf vapour conductance of sweet potato in the psychrometer chambers. In calculating the leaf relative water content, unstressed water of sweet potato leaves require 4 hours imbibition, whereas water stressed of sweet potato leaves require 5 to 6 hours to reach the saturation time. Either leaf water potential or relative water content can be used as a parameter for plant water status in sweet potato.

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Investigating the impact of pre-processing techniques and pre-trained word embeddings in detecting Arabic health information on social media

Journal Of Big Data ◽

10.1186/s40537-021-00488-w ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Yahya Albalawi ◽

Jim Buckley ◽

Nikola S. Nikolov

Keyword(s):

Social Media ◽

Deep Learning ◽

Comprehensive Evaluation ◽

Classification Problem ◽

Data Sets ◽

Word Embeddings ◽

Data Set ◽

Lower Accuracy ◽

Health Related ◽

The Impact

AbstractThis paper presents a comprehensive evaluation of data pre-processing and word embedding techniques in the context of Arabic document classification in the domain of health-related communication on social media. We evaluate 26 text pre-processings applied to Arabic tweets within the process of training a classifier to identify health-related tweets. For this task we use the (traditional) machine learning classifiers KNN, SVM, Multinomial NB and Logistic Regression. Furthermore, we report experimental results with the deep learning architectures BLSTM and CNN for the same text classification problem. Since word embeddings are more typically used as the input layer in deep networks, in the deep learning experiments we evaluate several state-of-the-art pre-trained word embeddings with the same text pre-processing applied. To achieve these goals, we use two data sets: one for both training and testing, and another for testing the generality of our models only. Our results point to the conclusion that only four out of the 26 pre-processings improve the classification accuracy significantly. For the first data set of Arabic tweets, we found that Mazajak CBOW pre-trained word embeddings as the input to a BLSTM deep network led to the most accurate classifier with F1 score of 89.7%. For the second data set, Mazajak Skip-Gram pre-trained word embeddings as the input to BLSTM led to the most accurate model with F1 score of 75.2% and accuracy of 90.7% compared to F1 score of 90.8% achieved by Mazajak CBOW for the same architecture but with lower accuracy of 70.89%. Our results also show that the performance of the best of the traditional classifier we trained is comparable to the deep learning methods on the first dataset, but significantly worse on the second dataset.

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Survey Data Quality in Analyzing Harmonized Indicators of Protest Behavior: A Survey Data Recycling Approach

American Behavioral Scientist ◽

10.1177/00027642211021623 ◽

2021 ◽

pp. 000276422110216

Author(s):

Kazimierz M. Slomczynski ◽

Irina Tomescu-Dubrow ◽

Ilona Wysmulek

Keyword(s):

Data Processing ◽

Data Quality ◽

Survey Data ◽

A Priori ◽

Data Sets ◽

New Approach ◽

Survey Quality ◽

Survey Error ◽

Ex Post ◽

The Impact

This article proposes a new approach to analyze protest participation measured in surveys of uneven quality. Because single international survey projects cover only a fraction of the world’s nations in specific periods, researchers increasingly turn to ex-post harmonization of different survey data sets not a priori designed as comparable. However, very few scholars systematically examine the impact of the survey data quality on substantive results. We argue that the variation in source data, especially deviations from standards of survey documentation, data processing, and computer files—proposed by methodologists of Total Survey Error, Survey Quality Monitoring, and Fitness for Intended Use—is important for analyzing protest behavior. In particular, we apply the Survey Data Recycling framework to investigate the extent to which indicators of attending demonstrations and signing petitions in 1,184 national survey projects are associated with measures of data quality, controlling for variability in the questionnaire items. We demonstrate that the null hypothesis of no impact of measures of survey quality on indicators of protest participation must be rejected. Measures of survey documentation, data processing, and computer records, taken together, explain over 5% of the intersurvey variance in the proportions of the populations attending demonstrations or signing petitions.

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A Two-Stage Joint Model for Nonlinear Longitudinal Response and a Time-to-Event with Application in Transplantation Studies

Journal of Probability and Statistics ◽

10.1155/2012/194194 ◽

2012 ◽

Vol 2012 ◽

pp. 1-18 ◽

Cited By ~ 6

Author(s):

Magdalena Murawska ◽

Dimitris Rizopoulos ◽

Emmanuel Lesaffre

Keyword(s):

Empirical Bayes ◽

Cox Model ◽

Data Sets ◽

Two Stage ◽

Nonlinear Mixed Effects Model ◽

Resistance Evolution ◽

Longitudinal Response ◽

Longitudinal Measurements ◽

Subject Specific ◽

The Impact

In transplantation studies, often longitudinal measurements are collected for important markers prior to the actual transplantation. Using only the last available measurement as a baseline covariate in a survival model for the time to graft failure discards the whole longitudinal evolution. We propose a two-stage approach to handle this type of data sets using all available information. At the first stage, we summarize the longitudinal information with nonlinear mixed-effects model, and at the second stage, we include the Empirical Bayes estimates of the subject-specific parameters as predictors in the Cox model for the time to allograft failure. To take into account that the estimated subject-specific parameters are included in the model, we use a Monte Carlo approach and sample from the posterior distribution of the random effects given the observed data. Our proposal is exemplified on a study of the impact of renal resistance evolution on the graft survival.

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Capability of leaf water content and its threshold values in reflection of soil–plant water status in maize during prolonged drought

Ecological Indicators ◽

10.1016/j.ecolind.2021.107395 ◽

2021 ◽

Vol 124 ◽

pp. 107395

Author(s):

Huailin Zhou ◽

Guangsheng Zhou ◽

Qijin He ◽

Li Zhou ◽

Yuhe Ji ◽

...

Keyword(s):

Water Content ◽

Water Status ◽

Leaf Water ◽

Plant Water Status ◽

Leaf Water Content ◽

Plant Water ◽

Threshold Values ◽

Prolonged Drought

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Numerical Simulation of Non-Homogeneous Viscous Debris-Flows Based on the Smoothed Particle Hydrodynamics (SPH) Method

Water ◽

10.3390/w11112314 ◽

2019 ◽

Vol 11 (11) ◽

pp. 2314 ◽

Cited By ~ 4

Author(s):

Shu Wang ◽

Anping Shu ◽

Matteo Rubinato ◽

Mengyao Wang ◽

Jiping Qin

Keyword(s):

Debris Flow ◽

Water Content ◽

Smoothed Particle Hydrodynamics ◽

Debris Flows ◽

Sph Method ◽

Particle Hydrodynamics ◽

Sph Model ◽

Smoothed Particle ◽

The Impact ◽

Kinetic And Potential Energies

Non-homogeneous viscous debris flows are characterized by high density, impact force and destructiveness, and the complexity of the materials they are made of. This has always made these flows challenging to simulate numerically, and to reproduce experimentally debris flow processes. In this study, the formation-movement process of non-homogeneous debris flow under three different soil configurations was simulated numerically by modifying the formulation of collision, friction, and yield stresses for the existing Smoothed Particle Hydrodynamics (SPH) method. The results obtained by applying this modification to the SPH model clearly demonstrated that the configuration where fine and coarse particles are fully mixed, with no specific layering, produces more fluctuations and instability of the debris flow. The kinetic and potential energies of the fluctuating particles calculated for each scenario have been shown to be affected by the water content by focusing on small local areas. Therefore, this study provides a better understanding and new insights regarding intermittent debris flows, and explains the impact of the water content on their formation and movement processes.

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The Experiment on Soil Water Characteristic Curve Considering the Effect of Urea Concentration

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.919-921.795 ◽

2014 ◽

Vol 919-921 ◽

pp. 795-799

Author(s):

Gai Qing Dai ◽

Dong Fang Tian ◽

Yao Ruan ◽

Lang Tian ◽

You Le Wang

Keyword(s):

Water Content ◽

Soil Water ◽

Characteristic Curve ◽

Urea Concentration ◽

Test Method ◽

Materials Selection ◽

Valuable Data ◽

Soil Water Characteristic Curve ◽

Concentration Test ◽

The Impact

A new soil water characteristic curve (SWCC) experiment contemplating urea concentration is presented in the paper. We focus on the impact of the SWCC considering urea concentration test method for materials selection and introduction, experimental results, and finally, we have conducted some experiments of SWCC and obtained some valuable data which could affect urea concentration. By using linear fitting, an exponential function between water content and suction and urea concentration is established.

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Human Performance Evaluation of a Metaphor Graphic Display for Respiratory Data

Methods of Information in Medicine ◽

10.1055/s-0038-1635042 ◽

1994 ◽

Vol 33 (04) ◽

pp. 390-396 ◽

Cited By ~ 30

Author(s):

J. G. Stewart ◽

W. G. Cole

Keyword(s):

Performance Evaluation ◽

Human Performance ◽

Pattern Detection ◽

Data Sets ◽

Complex Task ◽

Graphic Display ◽

Literal Sense ◽

Single Number ◽

The Impact ◽

Human Problem

Abstract:Metaphor graphics are data displays designed to look like corresponding variables in the real world, but in a non-literal sense of “look like”. Evaluation of the impact of these graphics on human problem solving has twice been carried out, but with conflicting results. The present experiment attempted to clarify the discrepancies between these findings by using a complex task in which expert subjects interpreted respiratory data. The metaphor graphic display led to interpretations twice as fast as a tabular (flowsheet) format, suggesting that conflict between earlier studies is due either to differences in training or to differences in goodness of metaphor, Findings to date indicate that metaphor graphics work with complex as well as simple data sets, pattern detection as well as single number reporting tasks, and with expert as well as novice subjects.

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