scholarly journals Nonlinear Model Selection for Fruit and Kernel Development as a Function of Heat in Pistachio

HortScience ◽  
2021 ◽  
pp. 1-11
Author(s):  
Lu Zhang ◽  
Emilio Laca ◽  
Cara J. Allan ◽  
Narges M. Mahvelati ◽  
Louise Ferguson
Keyword(s):  
Goodness Of Fit ◽  
Management Practices ◽  
Growth Traits ◽  
Gompertz Model ◽  
Nonlinear Dependence ◽  
Cultivar Differences ◽  
Coefficient Of Determination ◽  
Residual Distribution ◽  
Heat Accumulation ◽  
Shell Size

Knowing a tree crop’s seasonal growth and development as a function of heat accumulation can facilitate scheduling of irrigation, pesticide applications, and harvest. Our objective was to compare the goodness of fit of applied models and determine which provides the best description of pistachio nut growth as a function of thermal unit accumulation. Three fruit growth traits of pistachio—pericarp (hull) + endocarp (shell) size, endocarp thickening and hardening, and embryo (kernel) size—exhibited clear nonlinear dependence on heat accumulation. We tested three nonlinear models—Michaelis–Menten, three-parameter logistic, and Gompertz—fitted to fruit development data to create a tool to forecast pest susceptibility and harvest timing. Observation of development began at full bloom and ended at harvest. Data were collected from six pistachio cultivars in one experimental and eight commercial orchards over 3 years. Analyses of residual distribution, parameter standard errors, coefficient of determination (R2) and the Akaike information criterion (AIC) all demonstrated the Gompertz function was the best model. Cultivars differed significantly in all the three parameters (Asym, b, and c) for all three traits with the Gompertz model, demonstrating the Gompertz model can adjust to incorporate cultivar differences. The growth curve of the three traits together provided integrated information on nut biomass accumulation that facilitates predicting the critical timing for multiple orchard management practices.

scholarly journals Evaluation of NASA POWER Reanalysis Products to Estimate Daily Weather Variables in a Hot Summer Mediterranean Climate

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1207
Author(s):  
Gonçalo C. Rodrigues ◽  
Ricardo P. Braga
Keyword(s):  
Wind Speed ◽  
Bias Correction ◽  
Goodness Of Fit ◽  
Mediterranean Climate ◽  
Weather Data ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Weather Variables ◽  
Weather Stations

This study aims to evaluate NASA POWER reanalysis products for daily surface maximum (Tmax) and minimum (Tmin) temperatures, solar radiation (Rs), relative humidity (RH) and wind speed (Ws) when compared with observed data from 14 distributed weather stations across Alentejo Region, Southern Portugal, with a hot summer Mediterranean climate. Results showed that there is good agreement between NASA POWER reanalysis and observed data for all parameters, except for wind speed, with coefficient of determination (R2) higher than 0.82, with normalized root mean square error (NRMSE) varying, from 8 to 20%, and a normalized mean bias error (NMBE) ranging from –9 to 26%, for those variables. Based on these results, and in order to improve the accuracy of the NASA POWER dataset, two bias corrections were performed to all weather variables: one for the Alentejo Region as a whole; another, for each location individually. Results improved significantly, especially when a local bias correction is performed, with Tmax and Tmin presenting an improvement of the mean NRMSE of 6.6 °C (from 8.0 °C) and 16.1 °C (from 20.5 °C), respectively, while a mean NMBE decreased from 10.65 to 0.2%. Rs results also show a very high goodness of fit with a mean NRMSE of 11.2% and mean NMBE equal to 0.1%. Additionally, bias corrected RH data performed acceptably with an NRMSE lower than 12.1% and an NMBE below 2.1%. However, even when a bias correction is performed, Ws lacks the performance showed by the remaining weather variables, with an NRMSE never lower than 19.6%. Results show that NASA POWER can be useful for the generation of weather data sets where ground weather stations data is of missing or unavailable.

scholarly journals A generalized Gompertz growth model with applications and related birth-death processes

2020 ◽  
Author(s):  
Majid Asadi ◽  
Antonio Di Crescenzo ◽  
Farkhondeh A. Sajadi ◽  
Serena Spina
Keyword(s):  
Growth Model ◽  
Growth Curve ◽  
Goodness Of Fit ◽  
Gompertz Model ◽  
Death Process ◽  
Birth Process ◽  
Failure Data ◽  
First Case ◽  
Gompertz Growth Model ◽  
Birth Death

AbstractIn this paper, we propose a flexible growth model that constitutes a suitable generalization of the well-known Gompertz model. We perform an analysis of various features of interest, including a sensitivity analysis of the initial value and the three parameters of the model. We show that the considered model provides a good fit to some real datasets concerning the growth of the number of individuals infected during the COVID-19 outbreak, and software failure data. The goodness of fit is established on the ground of the ISRP metric and the $$d_2$$ d 2 -distance. We also analyze two time-inhomogeneous stochastic processes, namely a birth-death process and a birth process, whose means are equal to the proposed growth curve. In the first case we obtain the probability of ultimate extinction, being 0 an absorbing endpoint. We also deal with a threshold crossing problem both for the proposed growth curve and the corresponding birth process. A simulation procedure for the latter process is also exploited.

scholarly journals Drying kinetics of ‘babassu’ mesocarp

2017 ◽  
Vol 21 (10) ◽  
pp. 709-714 ◽  
Author(s):  
Jhonatas C. Rosa ◽  
Andreza P. Mendonça ◽  
Angélica dos S. Oliveira ◽  
Sylviane B. Ribeiro ◽  
Andréia do R. Batista ◽  
...  
Keyword(s):  
Experimental Data ◽  
Water Content ◽  
Animal Feed ◽  
Coefficient Of Determination ◽  
Residual Distribution ◽  
Solar Dryer ◽  
Error Standard Deviation ◽  
Forced Air ◽  
Final Water Content ◽  
Best Fit

ABSTRACT ‘Babassu’ mesocarp flour has been used by the pharmaceutical, human food and animal feed industries. However, there is lack of standardization in the production, as well as absence of information on the management of the product’s quality. Thus, the objective of this study was to dry the ‘babassu’ mesocarp in forced-air oven and solar dryer, adjust different mathematical models to the experimental data, as well as to quantify the levels of proteins and crude fiber of the produced flour. The criteria for the adjustment were the coefficient of determination, magnitude of the mean relative error, standard deviation of estimate and the residual distribution trend. Drying in the shortest time occurred in oven at 60 °C (370 min), leading to water content of 4.62%, while in the solar dryer the final water content was 8.07% in 6 days. The mathematical model Two Terms showed the best fit to the experimental data for oven drying and the Midilli model showed the best fit in solar dryer. There was an increase in protein content with the drying in solar dryer and oven at 40, 50 and 60 °C (1.36, 1.33, 1.15 and 1.37%, respectively) in relation to fresh mesocarp (0.88%). Drying in both oven and solar dryer promoted increase of protein in the flour.

scholarly journals BIDIRECTIONAL REFLECTANCE MODELING OF THE GEOSTATIONARY SENSOR HIMAWARI-8/AHI USING A KERNEL-DRIVEN BRDF MODEL

2016 ◽  
Vol III-7 ◽  
pp. 3-8 ◽  
Author(s):  
M. Matsuoka ◽  
M. Takagi ◽  
S. Akatsuka ◽  
R. Honda ◽  
A. Nonomura ◽  
...  
Keyword(s):  
Surface Properties ◽  
Land Surface ◽  
Goodness Of Fit ◽  
Near Infrared ◽  
Temporal Frequency ◽  
Atmospheric Correction ◽  
Time Of Day ◽  
Coefficient Of Determination ◽  
Near Infrared Reflectance ◽  
Bidirectional Reflectance

Himawari-8/AHI is a new geostationary sensor that can observe the land surface with high temporal frequency. Bidirectional reflectance derived by the Advanced Himawari Imager (AHI) includes information regarding land surface properties such as albedo, vegetation condition, and forest structure. This information can be extracted by modeling bidirectional reflectance using a bidirectional reflectance distribution function (BRDF). In this study, a kernel-driven BRDF model was applied to the red and near infrared reflectance observed over 8 hours during daytime to express intraday changes in reflectance. We compared the goodness of fit for six combinations of model kernels. The Ross-Thin and Ross-Thick kernels were selected as the best volume kernels for the red and near infrared bands, respectively. For the geometric kernel, the Li-sparse-Reciprocal and Li-Dense kernels displayed similar goodness of fit. The coefficient of determination and regression residuals showed a strong dependency on the azimuth angle of land surface slopes and the time of day that observations were made. Atmospheric correction and model adjustment of the terrain were the main issues encountered. These results will help to improve the BRDF model and to extract surface properties from bidirectional reflectance.

scholarly journals Effect of food matrix type on growth characteristics and hemolysin production of Vibrio alginolyticus

2020 ◽  
Author(s):  
Xiaojun Hu ◽  
Rundong Wang ◽  
Yijia Deng ◽  
Qi Deng ◽  
Zhijia Fang ◽  
...  
Keyword(s):  
Freshwater Fish ◽  
Goodness Of Fit ◽  
Gompertz Model ◽  
Food Matrix ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Primary Model ◽  
Thermostable Direct Hemolysin ◽  
Effect Of Food ◽  
Modified Gompertz Model

Abstract Background: The growth and hemolysin production of V. alginolyticus at 30 °C in briny Tilapia , shrimp, scallop, oyster, pork, chicken, freshwater fish and egg fried rice were investigated. Bacterial counts were enumerated by plate counting. Hemolysin production was evaluated by blood agar and hemolytic titer tests. Results: Based on the goodness of fit primary model statistics (R 2 , MSE, BF, AF), the modified Gompertz model was a better fit to V. alginolyticus growth in foods than the logistic model. Growth kinetic parameters of V. alginolyticus displayed a higher μ max and shorter λ in briny Tilapia > shrimp > freshwater fish > egg fried rice > scallop > oyster > chicken > pork. It was notable that the V. alginolyticus counts were similar at the stationary phase, with no significant growth behavior difference between raw and cooked foods. However, higher thermostable direct hemolysin activity and hemolytic titer were observed in briny Tilapia > egg fried rice > shrimp > freshwater fish > chicken > scallop > oyster > pork. Conclusion: V. alginolyticus growth was good in all food matrix types tested. Contrary to current belief, V. alginolyticus displayed a higher hemolytic activity in some non-seafoods (freshwater fish, egg fried rice and chicken) than in scallop or oyster. This is the first report of growth and toxicity of V. alginolyticus in non-seafood. This finding will significantly improve the accuracy of microbial risk assessment of V. alginolyticus in different food matrices especially during warmer climatic periods when it is most prevalent.

scholarly journals Longitudinal Pattern of Aerenchyma Formation Using the Ti-Gompertz Model in Rice Adventitious Roots

2021 ◽  
Vol 12 ◽  
Author(s):  
Yun Chen ◽  
Guoming Li ◽  
Buhong Zhao ◽  
Yajun Zhang ◽  
Kun Liu ◽  
...  
Keyword(s):  
Adventitious Roots ◽  
Goodness Of Fit ◽  
Gompertz Model ◽  
Root Apex ◽  
Information Criterion ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Aerenchyma Formation ◽  
Root Aerenchyma ◽  
Longitudinal Pattern

The longitudinal pattern of root aerenchyma formation of its relationship with the function of adventitious roots in rice remains unclear. In this study, the percentage of the aerenchyma area to the cross-sectional area (i.e., aerenchyma percentage) was fit with four non-linear models, namely, W0-Gompertz, Ti-Gompertz, logistic, and von Bertalanffy. Goodness-of-fit criteria such as the R2, the Akaike information criterion (AIC), and the Bayesian information criterion (BIC) were used to select the model. The bias of the parameters was evaluated using the difference between the ordinary least squares-based parameter estimates and the mean of 1,000 bootstrap-based parameter estimates and the symmetry of the distributions of these parameters. The results showed that the Ti-Gompertz model, which had a high goodness-of-fit with an R2 close to 1, lower AIC and BIC values, parameter estimates close to being unbiased, and good linear approximation, provided the best fit for the longitude pattern of rice aerenchyma formation with different root lengths among the competing models. Using the second- and third-order derivatives according to the distance from the root apex, the critical points of Ti-Gompertz were calculated. The rapid stage for aerenchyma formation was from the maximum acceleration point (1.38–1.76 cm from the root apex) to the maximum deceleration point (3.13–4.19 cm from the root apex). In this stage, the aerenchyma percentage increased by 5.3–15.7% per cm, suggesting that the cortical cells tended to die rapidly for the aerenchyma formation rather than for the respiration cost during this stage. Meanwhile, the volume of the aerenchyma of the entire roots could be computed using the integral function of the Ti-Gompertz model. We proposed that the longitudinal pattern of root aerenchyma formation modeled by the Ti-Gompertz model helped to deeply understand the relationship between the anatomical traits and physiological function in rice adventitious roots.

scholarly journals Mathematical Models for Tumor Growth and the Reduction of Overtreatment

2018 ◽  
Vol 80 (01) ◽  
pp. 072-078 ◽  
Author(s):  
Berdine Heesterman ◽  
John-Melle Bokhorst ◽  
Lisa de Pont ◽  
Berit Verbist ◽  
Jean-Pierre Bayley ◽  
...  
Keyword(s):  
Tumor Growth ◽  
Mathematical Models ◽  
Goodness Of Fit ◽  
Mean Squared Error ◽  
Age At Onset ◽  
Growth Curves ◽  
Magnetic Resonance Images ◽  
Coefficient Of Determination ◽  
Growth Data ◽  
Significant Difference

Background To improve our understanding of the natural course of head and neck paragangliomas (HNPGL) and ultimately differentiate between cases that benefit from early treatment and those that are best left untreated, we studied the growth dynamics of 77 HNPGL managed with primary observation. Methods Using digitally available magnetic resonance images, tumor volume was estimated at three time points. Subsequently, nonlinear least squares regression was used to fit seven mathematical models to the observed growth data. Goodness of fit was assessed with the coefficient of determination (R 2) and root-mean-squared error. The models were compared with Kruskal–Wallis one-way analysis of variance and subsequent post-hoc tests. In addition, the credibility of predictions (age at onset of neoplastic growth and estimated volume at age 90) was evaluated. Results Equations generating sigmoidal-shaped growth curves (Gompertz, logistic, Spratt and Bertalanffy) provided a good fit (median R 2: 0.996–1.00) and better described the observed data compared with the linear, exponential, and Mendelsohn equations (p < 0.001). Although there was no statistically significant difference between the sigmoidal-shaped growth curves regarding the goodness of fit, a realistic age at onset and estimated volume at age 90 were most often predicted by the Bertalanffy model. Conclusions Growth of HNPGL is best described by decelerating tumor growth laws, with a preference for the Bertalanffy model. To the best of our knowledge, this is the first time that this often-neglected model has been successfully fitted to clinically obtained growth data.

scholarly journals Abdominal subcutaneous fat quantification in obese patients from limited field-of-view MRI data

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Sophia Michel ◽  
Nicolas Linder ◽  
Tobias Eggebrecht ◽  
Alexander Schaudinn ◽  
Matthias Blüher ◽  
...  
Keyword(s):  
Gender Differences ◽  
Adipose Tissue ◽  
Goodness Of Fit ◽  
Imaging Techniques ◽  
Subcutaneous Fat ◽  
Field Of View ◽  
Coefficient Of Determination ◽  
Obese Patients ◽  
Obese Subjects ◽  
Surrogate Measures

Abstract Different types of adipose tissue can be accurately localized and quantified by tomographic imaging techniques (MRI or CT). One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities. Clinical (gender, age, anthropometry) and MRI data (1.5 T, two-point Dixon sequence) of 193 overweight and obese patients (116 female, 77 male) from a single research center for obesity were analyzed retrospectively. Six surrogate measures of fully segmented ASAT volume (VASAT) were considered: two simple ASAT lengths, two partial areas (Ap-FH, Ap-ASIS) and two partial volumes (Vp-FH, Vp-ASIS) limited by either the femoral heads (FH) or the anterior superior iliac spine (ASIS). Least-squares regression between each measure and VASAT provided slope and intercept for the computation of estimated ASAT volumes (V~ASAT). Goodness of fit was evaluated by coefficient of determination (R2) and standard deviation of percent differences (sd%) between V~ASAT and VASAT. Best agreement was observed for partial volume Vp-FH (sd% = 14.4% and R2 = 0.78), followed by Vp-ASIS (sd% = 18.1% and R2 = 0.69) and AWFASIS (sd% = 23.9% and R2 = 0.54), with minor gender differences only. Other estimates from simple lengths and partial areas were moderate only (sd% > 23.0% and R2 < 0.50). Gender differences in R2 generally ranged between 0.02 (dven) and 0.29 (Ap-FH). The common FOV restriction for MRI volumetry of ASAT in obese subjects can best be overcome by estimating VASAT from Vp-FH using the equation derived here. The very simple AWFASIS can be used with reservation.

scholarly journals Relationship between positive clinical VTO and post-treatment soft tissue profile following phase l growth modification therapy

2018 ◽  
Vol 8 (2) ◽  
pp. 45-49 ◽  
Author(s):  
Shabbir Hussain ◽  
Muhammad Azeem ◽  
Waheed Ul Hamid ◽  
Faiz Rasool
Keyword(s):  
Soft Tissue ◽  
Goodness Of Fit ◽  
Linear Regression Analysis ◽  
Post Treatment ◽  
Coefficient Of Determination ◽  
Facial Profile ◽  
Soft Tissue Profile ◽  
Growth Modification ◽  
Treatment Profile

Introduction: Facial profile improvement is goal of cotemporary orthodontics and a reason to seek orthodontic therapy. The soft tissue profile plays a important role on orthodontic diagnosis and treatment planning. The objective of this study is to investigate the relationship between positive clinical VTO and actual post-treatment soft tissue profile after phase l therapy of growth modification in Class II. Materials & Method: Pretreatment simulation of post-treatment and actual post-treatment profile photographs of 30 class ll div l patients treated with twin block appliance were compared. Three profile photographs of each subject; pretreatment, positive clinical VTO and post-treatment were taken and on each photograph four angles; Nasofacial (NF), Nasomental (NM), Mentocervical (MC) and Nasolabial (NL) were drawn and measured. Mean, standard deviation, success and coefficient of determination of each angle was measured and linear regressions analysis was applied to find out the correlation. Result: Nasolabial and nasomental angles showed greater success i.e. 81.4% and 68.1% respectively showing greater correlation, while nasofacial and mentocervical angles showed less success i.e. 48.1% and 48.3% respectively showing less correlation. Linear regression analysis revealed that positive clinical VTO significantly predicted post-treatment profile whereas coefficient of determination for nasomental and mentocervical angles was 76.5% and 60% representing a better goodness of fit while nasolabial and nasofacial angles was 53.6% and 51.6% demonstrating poor fit of regression lines. Conclusion: Even though there is improved facial profile obtained by protracting the mandible into class l relation in a chair side maneuver in class ll div l malocclusions, yet the orthodontist should be tentative when predicting the outcome of growth modification to get benefit of this therapy.

scholarly journals The ConCom Safety Management Scale: developing and testing a measurement instrument for control-based and commitment-based safety management approaches in hospitals

2018 ◽  
Vol 27 (10) ◽  
pp. 807-817 ◽  
Author(s):  
Carien W Alingh ◽  
Mathilde M H Strating ◽  
Jeroen D H van Wijngaarden ◽  
Jaap Paauwe ◽  
Robbert Huijsman
Keyword(s):  
Patient Safety ◽  
Construct Validity ◽  
Goodness Of Fit ◽  
Management Practices ◽  
Nurse Managers ◽  
Safety Management ◽  
Measurement Instrument ◽  
Managerial Control ◽  
Clinical Hospital ◽  
Management Approaches

BackgroundNursing management is considered important for patient safety. Prior research has predominantly focused on charismatic leadership styles, although it is questionable whether these best characterise the role of nurse managers. Managerial control is also relevant. Therefore, we aimed to develop and test a measurement instrument for control-based and commitment-based safety management of nurse managers in clinical hospital departments.MethodsA cross-sectional survey design was used to test the newly developed questionnaire in a sample of 2378 nurses working in clinical departments. The nurses were asked about their perceptions of the leadership behaviour and management practices of their direct supervisors. Psychometric properties were evaluated using confirmatory factor analysis and reliability estimates.ResultsThe final 33-item questionnaire showed acceptable goodness-of-fit indices and internal consistency (Cronbach’s α of the subscales range: 0.59–0.90). The factor structure revealed three subdimensions for control-based safety management: (1) stressing the importance of safety rules and regulations; (2) monitoring compliance; and (3) providing employees with feedback. Commitment-based management consisted of four subdimensions: (1) showing role modelling behaviour; (2) creating safety awareness; (3) showing safety commitment; and (4) encouraging participation. Construct validity of the scale was supported by high factor loadings and provided preliminary evidence that control-based and commitment-based safety management are two distinct yet related constructs. The findings were reconfirmed in a cross-validation procedure.ConclusionThe results provide initial support for the construct validity and reliability of our ConCom Safety Management Scale. Both management approaches were found to be relevant for managing patient safety in clinical hospital departments. The scale can be used to deepen our understanding of the influence of patient safety management on healthcare professionals’ safety behaviour as well as patient safety outcomes.

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