scholarly journals Sloughing in potatoes induced by tuber density and affected by variety

2008 ◽  
Vol 26 (No. 1) ◽  
pp. 48-57 ◽  
Author(s):  
A. Hejlová ◽  
J. Blahovec
Keyword(s):  
Effective Mass ◽  
Linear Models ◽  
Close Association ◽  
Cooking Time ◽  
Time Sensitivity ◽  
Starting Point ◽  
Effective Mass Method

Two cultivars (Nicola and Saturna) largely distinguishing from each other in cooking behaviour and one cultivar (Agria) grown in six different cultivation regimes were tested by the CPEM (cooked potato effective mass) method for the potato sloughing assessment. The sloughing process is characterised by two cooking and disintegration stages, from which two basic CPEM parameters are derived: cooking time as the starting point of disintegration and the rate of the disintegration. Both parameters are analysed as functions of the tuber density in linear models of both stages. Significant differences in CPEM parameters and in the linear models were observed between different varieties. The data from two-year measurements were in basic agreement with our previous concept of the limited contribution of starch in the first cooking stage and of its more important role in the second disintegration stage of sloughing. The results indicated a close association between the mechanisms controlling sloughing and the tuber density in the cultivars Agria and Saturna. A different cooking behaviour was observed in the case of the typical salad cultivar Nicola with a considerably lower cooking time sensitivity to the tuber density.

scholarly journals Role of cultivation conditions in potato sloughing as indicated by CPEM method

2008 ◽  
Vol 53 (No. 9) ◽  
pp. 403-412 ◽  
Author(s):  
A. Hejlová ◽  
J. Blahovec
Keyword(s):  
Potato Variety ◽  
Linear Models ◽  
Cooking Time ◽  
Cultivation Conditions ◽  
Stable Variety ◽  
Starting Point ◽  
Growing Conditions ◽  
Different Levels ◽  
Effective Mass Method

The new CPEM (cooked potato effective mass) method was used to study the sloughing of a potato variety grown in two successive years in six regimes given by different levels and forms of fertilisation and irrigation. The sloughing process is characterized by the cooking time, i.e. the starting point of disintegration, and by the speed of disintegration. Both parameters are also evaluated in dependence on tuber density in linear models of cooking and disintegration stages. Effects of different cultivation regimes were observed in both stages. The sloughing sensitivity to tuber density expressed via the cooking time seemed to be a relatively stable variety parameter independent of growing conditions. The fertilisation reduced the level of sloughing, i.e. higher cooking time values (<i>P</i> < 0.0023), and at the same time lower disintegration rates (<i>P</i> < 0.006) were indicated for fertilised tubers. No influence of irrigation was observed in our study.

scholarly journals Influence of process parameters on the color and texture of passion fruit albedo preserved in syrup

2013 ◽  
Vol 33 (1) ◽  
pp. 116-121
Author(s):  
Luisa Pereira Figueiredo ◽  
Marali Vilela Dias ◽  
Wanderson Alexandre Valente ◽  
Soraia Vilela Borges ◽  
Anirene Galvão Tavares Pereira ◽  
...  
Keyword(s):  
Process Parameters ◽  
Linear Models ◽  
Fruit Juice ◽  
Correlation Coefficients ◽  
Cooking Time ◽  
Passion Fruit ◽  
Influence Of Process Parameters ◽  
Yellow Color

The industrialization of passion fruit in the form of juice produces considerable amounts of residue that could be used as food. The objective of the present study was to determine the effects of the volume of passion fruit juice added to the syrup and the cooking time on the color and texture of passion fruit albedo preserved in syrup. Multi-linear models were well fit to describe the value for a* (for the albedo) the values for b* (for the albedo and syrup), which exhibited high correlation coefficients of 98%, 84%, and 88%, respectively. The volume of passion fruit juice added and the cooking time of the albedos in the syrup, involved in the processing of passion fruit albedo preserves in syrup, significantly affected color analyses. The texture was not affected by the parameters studied. Therefore, the use of larger volumes of passion fruit juice and longer cooking time is recommended for the production of passion fruit albedo preserves in syrup to achieve the characteristic yellow color of the fruit.

The effective mass method for surface states

1983 ◽  
Vol 16 (5) ◽  
pp. 985-997 ◽  
Author(s):  
A Fasolino ◽  
G Santoro ◽  
E Tosatti
Keyword(s):  
Effective Mass ◽  
Surface States ◽  
Effective Mass Method

Valley mixing in GaAs/AlAs multilayer structures in the effective-mass method

1993 ◽  
Vol 47 (20) ◽  
pp. 13498-13507 ◽  
Author(s):  
Y. Fu ◽  
M. Willander ◽  
E. L. Ivchenko ◽  
A. A. Kiselev
Keyword(s):  
Effective Mass ◽  
Multilayer Structures ◽  
Effective Mass Method

scholarly journals On modeling and analyzing barley malt data in different years

2019 ◽  
Vol 56 (1) ◽  
pp. 45-57
Author(s):  
Iwona Mejza ◽  
Katarzyna Ambroży-Deręgowska ◽  
Jan Bocianowski ◽  
Józef Błażewicz ◽  
Marek Liszewski ◽  
...  
Keyword(s):  
Linear Model ◽  
Random Effects ◽  
Fixed Effects ◽  
Linear Models ◽  
Model Fitting ◽  
Mixed Linear Model ◽  
Barley Grain ◽  
Barley Malt ◽  
Starting Point ◽  
Quality Coefficient

SummaryThe main purpose of this study was the model fitting of data deriving from a three-year experiment with barley malt. Two linear models were considered: a fixed linear model with fixed effects of years and other factors, and a mixed linear model with random effects of years and fixed effects of other factors. Two cultivars of brewing barley, Sebastian and Mauritia, six methods of nitrogen fertilization and four germination times were analyzed. Three quantitative traits were observed: practical extractivity of the malt, malting productivity, and a quality coefficient Q. The starting point for the statistical analyses was the available experimental material, which consisted of barley grain samples destined for malting. The analyses were performed over a series of years with respect to fixed or random effects of years. Due to the strong differentiation of the years of the study and some significant interactions of factors with years, annual analyses were also carried out.

Effect of Potential Correction on the Ground States of P and S+ Impurities in Silicon: Application of the Cavity Model

1965 ◽  
Vol 20 (11) ◽  
pp. 1476-1490
Author(s):  
A. M. K. Müller
Keyword(s):  
Effective Mass ◽  
Free Electron ◽  
Energy Levels ◽  
Correction Method ◽  
Host Lattice ◽  
Electron Mass ◽  
Cavity Model ◽  
Cavity Radius ◽  
Donor Nucleus ◽  
Starting Point

The discrepancies between the observed and the calculated ground state energies of P and S+ impurities in silicon are discussed on the basis of a cavity model which roughly accounts for the spatial dependence of the inverse dielectric function in the vicinity of the impurity. Applying simple effective mass theory (without reference to the KOHN—LUTTINGER semi-empirical correction method), it is shown that the model yields energy levels (and also the wave function at the P donor nucleus) in fair agreement with the experiments, if the effective cavity radius r0 is assumed to resemble the WIGNER-SEITZ radius rs rather than the nearest neighbour distance rd of the Si host lattice.The result depends critically on the assumption that the effective mass m* related to the bottom of the conduction band, may be used even for levels as deep as S+. Application of the cavity model in connection with the free electron mass m0 , gives rise to an almost zero cavity radius which appears to be inconsistent with various estimates yielding rs ≲ r0 ≲ rd. It is concluded that the effective mass theory rather than a free electron mass equation will be the appropriate starting point for a more refined treatment of the S+ spectrum and that of related defects.The paper contains a discussion of various relevant aspects of the problem as well as a review of some different attempts to account for the discrepancies.

Cross-Talk Induces Bifurcations in Nonlinear Models of Synaptic Plasticity

2012 ◽  
Vol 24 (2) ◽  
pp. 455-522 ◽  
Author(s):  
Terry Elliott
Keyword(s):  
Synaptic Plasticity ◽  
Cross Talk ◽  
Neuronal Development ◽  
Linear Models ◽  
Critical Level ◽  
Nonlinear Dynamical Systems ◽  
Nonlinear Models ◽  
Nonlinear Dynamical ◽  
Starting Point ◽  
Biological Realism

Linear models of synaptic plasticity provide a useful starting-point for examining the dynamics of neuronal development and learning, but their inherent problems are well known. Models of synaptic plasticity that embrace the demands of biological realism are therefore typically nonlinear. Viewed from a more abstract perspective, nonlinear models of synaptic plasticity are a subset of nonlinear dynamical systems. As such, they may therefore exhibit bifurcations under the variation of control parameters, including noise and errors in synaptic updates. One source of noise or error is the cross-talk that occurs during otherwise Hebbian plasticity. Under cross-talk, stimulation of a set of synapses can induce or modify plasticity in adjacent, unstimulated synapses. Here, we analyze two nonlinear models of developmental synaptic plasticity and a model of independent component analysis in the presence of a simple model of cross-talk. We show that cross-talk does indeed induce bifurcations in these models, entirely destroying their ability to acquire either developmentally or learning-related patterns of fixed points. Importantly, the critical level of cross-talk required to induce bifurcations in these models is very sensitive to the statistics of the afferents’ activities and the number of afferents synapsing on a postsynaptic cell. In particular, the critical level can be made arbitrarily small. Because bifurcations are inevitable in nonlinear models, our results likely apply to many nonlinear models of synaptic plasticity, although the precise details vary by model. Hence, many nonlinear models of synaptic plasticity are potentially fatally compromised by the toxic influence of cross-talk and other sources of noise and errors more generally. We conclude by arguing that biologically realistic models of synaptic plasticity must be robust against noise-induced bifurcations and that biological systems may have evolved strategies to circumvent their possible dangers.

scholarly journals Screening for early-stage Alzheimer’s disease using optimized feature sets and machine learning

2020 ◽  
Author(s):  
Michael J. Kleiman ◽  
Elan Barenholtz ◽  
James E. Galvin ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Linear Models ◽  
Early Stage ◽  
High Rate ◽  
Cognitive Assessments ◽  
High Detection Rate ◽  
Starting Point ◽  
Assessment Time ◽  
Mild Impairment

ABSTRACTBackgroundDetecting early-stage Alzheimer’s disease in clinical practice is difficult due to a lack of efficient and easily administered cognitive assessments that are sensitive to very mild impairment, a likely contributor to the high rate of undetected dementia.ObjectiveHere, we aim to identify groups of cognitive assessment features optimized for detecting mild impairment that can be used in routine screening. We also compare the efficacy of classifying impairment using either a two-class (impaired vs non-impaired) or three-class approach.MethodsSupervised feature selection methods generated groups of cognitive measurements targeting impairment defined at CDR 0.5 and above. Random forest classifiers then generated predictions of impairment for each group using highly stochastic cross-validation, with group outputs examined using general linear models.ResultsThe strategy of combining impairment levels for two-class classification resulted in significantly higher sensitivities and NPVs, two metrics useful in clinical screening, compared to the three-class approach. Just four neuropsychological features (delayed WAIS Logical Memory, trail-making, patient and informant memory questions), able to be administered in approximately 15 active minutes (∼30 minutes with delay), enabled classification sensitivity of 94.53% (88.43% PPV) with the addition of four more features significantly increasing sensitivity to 95.18% (88.77% PPV) when added to the model as a second classifier.ConclusionThe high detection rate paired with the minimal assessment time of the four identified features may act as an effective starting point when screening for cognitive impairment defined at CDR 0.5 and above.

Sign in / Sign up

Export Citation Format

Share Document