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Wild edible mushrooms are an important food source globally and have a crucial role in forest ecosystems. However, there is limited research on the growth characteristics and the contribution of agronomic traits to biomass, and the environmental factors affecting mushroom growth are limited. This study was conducted in the Qilian Mountains, China, and focused on investigating the growth patterns and agronomic traits of Lyophyllum decastes and Coprinus comatus. The results revealed that the growth of these mushrooms followed a logical growth curve. By calculating the model parameters, we obtained the maximum daily growth of height (PH), pileus diameter (PD), and cluster perimeter (CP) of L. decastes on the 5th, 7th, and 7th days, respectively, with values of 0.55 cm d−1, 0.54 cm d−1, and 4.54 cm d−1, respectively. However, the maximum daily growth of PH, pileus length (PL), and PD of the C. comatus appeared on the 3rd day, 2nd day, and 2nd day of the observation, respectively. This study identified near-surface relative humidity, air relative humidity, and rainfall as the primary factors influencing mushroom growth, as indicated by Pearson's correlation analysis, redundancy analysis (RDA), and multiple linear and stepwise regression. Additionally, land surface temperature and air temperature were also identified as important factors affecting mushroom growth. By utilizing random forest and stepwise regression analysis, this study identified PH and stipe diameter (SD) as the most crucial agronomic traits affecting mushroom biomass. Overall, this study offers insights for industrial mushroom cultivation and basic fungal research. [ABSTRACT FROM AUTHOR]

Background: The aim of the present study was to provide ocular biometry percentile values for Indian children between the ages of 6 and 12 and to validate the usefulness of centiles in predicting myopia development. Methods: The study was part of a longitudinal study—the Sankara Nethralaya Tamil Nadu Essilor Myopia Study (STEM), where objective refraction and ocular biometry were measured for children studying in grades 1, 4, and 6 at baseline (2019–2020). These data were used to generate ocular biometry percentile curves (both for axial length (AL) and AL/corneal curvature (AL/CR) ratios). The usefulness of percentile values in predicting myopia development was estimated from follow-up data (2022). Results: The total number of children in the three grades at baseline was 4514 (age range 6 to 12). Boys represented 54% (n = 2442) of the overall sample. The prevalence of myopia at baseline was 11.7% (95% CI from 10.8 to 12.7%) in these three grades. Both the AL and AL/CR ratio centiles showed a linear trend with an increase in AL and AL/CR with increasing grades (p < 0.001) for all percentiles (2, 5, 10, 25, 50, 75, 90, 95, 98, and 99) when stratified by sex. In the follow-up data (n = 377), the 75th and 50th percentiles of the AL/CR ratio had an area under the curve (AUC) of 0.79 and 0.72 to predict myopia onset for grade 4 and 6 children at baseline. Combining baseline AL with the centile shift in follow-up as a predictor increased the AUC to 0.83. Conclusions: The present study has provided centile values specific for Indian children between the ages of 6 and 12 to monitor and intervene where children are at a higher risk of myopia development. [ABSTRACT FROM AUTHOR]

Evaluating the behavior of fruit width and length characters throughout the pepper crop cycle is essential for researchers in decision-making aimed at developing appropriate management techniques and harvesting fruits at proper growth stages. The Nonlinear Mixed-Effect Models (NLME) method is recommended to jointly model the residuals and the entire database, including group effects, to describe growth curves. This work compared four nonlinear equations (Gompertz, Logistic, Richards, and von Bertalanffy) by including groups (pepper and bell pepper) to describe the pepper genotypes' length and width growth. Of the eight genotypes used, three were bell pepper, and five were pepper. For each, fruit length and width were measured in 10 periods. According to the fit-quality measures studied, the best model for adjusting the length of the fruit was the Richards ( R a d j. 2 = 0.9960 ), while for the width, it was the Logistic ( R a d j. 2 = 0.9957 ). The estimated random effects showed that for asymptotic length and time to the inflection point presented a correlation of 0.75, indicating a positive association between these traits. For width, however, this result was different: −0.02. NLME adjustment allowed efficient prediction of values and efficient characterization of the studied genotypes, proving to be an efficient method for longitudinal data. [ABSTRACT FROM AUTHOR]

In this article, we compare two ways of modelling measures of fetal growth. The goal is to impute the missing information for certain ultrasound measurements that are observed at different times and with different numbers of observations. To analyze the effect that other variables have, such as environmental exposure to certain substances or diet, on fetal growth based on these data, we need to handle the information measured at the same instant of time for all the individuals under study, preferably in three time windows of pregnancy (first trimester, week 12; second trimester, week 20; third trimester, week 34). For this, data at these chosen times, in case they are not available, must be imputed from the available information using an appropriate statistical model. One option is to use a linear model, specifically a generalized least squares model that is fitted to the features shown in the data. The other option is to use diffusion processes, estimating their parameters based on the available information. In both options, missing data can be estimated with the unconditional fitted model, conditional on the previous available measurement, or conditional to the closest measurement. [ABSTRACT FROM AUTHOR]

Simple Summary: Following the growth of a fattening animal is an important aspect since farmers aim to maximize their profits by improving their slaughter weight. Growth models can fit the age–weight data into biologically interpretable parameters that provide a growth curve for monitoring animal growth, thus identifying the growth declining point during the fattening period. In this study, we aimed to define the best fitting growth model for describing Kivircik lamb growth. While the Gompertz model was identified as the best fitting growth model, it was determined that male lambs, twin lambs, and winter-born lambs had a higher mature weight. Even though they may be lighter at birth, the proportion of their prospective weight gain was found to be higher compared to female, single-born, and spring-born lambs. Our results showed that the estimation error of the Gompertz model ranged between −0.43 kg to 0.60 kg. In conclusion, according to the Gompertz model's estimation, Kivircik lambs reached 40.7% of their slaughter weight at weaning and had a 66.3% degree of maturity at the slaughter age, which indicated inappropriate management. The Kivircik is an indigenous sheep breed from Turkey, and it has superior meat quality compared to other indigenous breeds. Therefore, farmers prioritize Kivircik lamb fattening instead of milk production. Here, we aimed to determine the best nonlinear growth model, i.e., Gompertz, Logistic, Von Bertalanffy, and Brody, to describe the growth curve of Kivircik lambs. The body weight data from birth until 150 days of age belonging to 612 lambs were used as the material of this study. The best fitting model was selected by considering the adjusted coefficient of determination (R2adj), residual mean square, and Akaike's (AIC) and Bayesian information criteria (BIC). Even though the Brody model had a better statistical fit, considering its biological interpretation, the Gompertz model was identified as an appropriate model for describing Kivircik lamb growth. Male lambs, twin lambs, and lambs born in winter had higher mature live weights (44.2 kg, 71.2 kg, and 38.5 kg, respectively) and rate of weight gain (2.1, 2.6, and 2.0, respectively). However, our subgroups revealed a similar rate of maturity (0.01). Growth models are important tools for deciding the optimal slaughter age and they provide valuable information on the management practices of both sexes, birth types, and birth seasons. These results can be applied to breeding programs for early selection, enabling intervention strategies when needed. [ABSTRACT FROM AUTHOR]

Opuntia joconostle is a semi-wild cactus cultivated for its fruit. However, the cladodes are often discarded, wasting the potentially useful mucilage in them. The mucilage is composed primarily of heteropolysaccharides, characterized by their molar mass distribution, monosaccharide composition, structural features (by vibrational spectroscopy, FT IR, and atomic force microscopy, AFM), and fermentability by known saccharolytic commensal members of the gut microbiota. After fractionation with ion exchange chromatography, four polysaccharides were found: one neutral (composed mainly of galactose, arabinose, and xylose) and three acidic, with a galacturonic acid content from 10 to 35%mol. Their average molar masses ranged from 1.8 × 105 to 2.8 × 105 g·mol−1. Distinct structural features such as galactan, arabinan, xylan, and galacturonan motifs were present in the FT IR spectra. The intra- and intermolecular interactions of the polysaccharides, and their effect on the aggregation behavior, were shown by AFM. The composition and structural features of these polysaccharides were reflected in their prebiotic potential. Lactobacilli and Bifidobacteria were not able to utilize them, whereas members of Bacteroidetes showed utilization capacity. The obtained data suggest a high economic potential for this Opuntia species, with potential uses such as animal feed in arid areas, precise prebiotic, and symbiotic formulations, or as the carbon skeleton source in a green refinery. Our methodology can be used to evaluate the saccharides as the phenotype of interest, helping to guide the breeding strategy. [ABSTRACT FROM AUTHOR]

Featured Application: A better understanding of mold growth on wood and the parameters on which this growth depends will lead to improved calculation models for predicting mold occurrence in buildings and building components. The possible influence of anatomical sections of wood on mold growth was investigated by means of a laboratory experiment. The selected fungi, Aspergillus sp., Penicillium sp., and Alternaria sp. were inoculated by spraying on the surface of wood specimens prepared from pine (Pinus sylvestris) and spruce (Picea abies). The incubation was carried out under stable environmental conditions (temperature of 22 °C, relative humidity of 75, 87, and 95%) over three months. Mold growth was evaluated based on regular microscopic and macroscopic observations. The recorded mold coverage fractions and the qualitative indicators of mold development were later expressed by a dimensionless mold index. The differences in mold growth in the anatomical sections of wood were found to be relatively insignificant. In contrast, comparison of measured data with other experimental studies showed large differences, especially in the initial growth phase. The discrepancy is probably related to differences among the experimental protocols. It is concluded that laboratory mold growth studies would be improved if a common standardized methodology was developed and followed. [ABSTRACT FROM AUTHOR]

Information on age and growth is essential to modern stock assessment and the development of management plans for fish resources. To provide quality otolith-based estimates of growth parameters, this study performed five types of analyses on the two important croakers that were under high fishing pressure in southwestern Taiwan: Pennahia macrocephalus (big-head pennah croaker) and Atrobucca nibe (blackmouth croaker): (1) Estimation of length–weight relationships (LWR) with discussion on the differences with previous studies; (2) validation of the periodicity of ring formation using edge analysis; (3) examination of three age determination methods (integral, quartile and back-calculation methods) and selection of the most appropriate one using a k-fold cross-validation simulation; (4) determination of the representative growth models from four candidate models using a multimodel inference approach; and, (5) compilation of growth parameters for all Pennahia and Atrobucca species published globally for reviewing the clusters of estimates using auximetric plots of logged growth parameters. The study observed that features of samples affected the LWR estimates. Edge analysis supported the growth rings were formed annually, and the cross-validation study supported the quartile method (age was determined as the number of opaque bands on otolith plus the quartile of the width of the marginal translucent band) provided more appropriate estimates of age. The multimodel inference approach suggested the von Bertalanffy growth model as the optimal model for P. macrocephalus and logistic growth model for A. nibe, with asymptotic lengths and relative growth rates of 18.0 cm TL and 0.789 year−1 and 55.21 cm, 0.374 year−1, respectively. Auximetric plots of global estimates showed a downward trend with clusters by species. Growth rates of the two species were higher than in previous studies using the same aging structure (otolith) and from similar locations conducted a decade ago, suggesting a possible effect of increased fishing pressure and the need to establish a management framework. This study adds updated information to the global literature and provides an overview of growth parameters for the two important croakers. [ABSTRACT FROM AUTHOR]

Objective: To provide new information about androgen insensitivity syndrome (AIS), we studied growth patterns in Chinese children with AIS. Subjects: Data are from 118 untreated AIS patients who were admitted to eight pediatric endocrine centers from January 2010 to December 2019. Methods: In this retrospective cohort study, clinical data were collected from a multicenter database. We compared physical assessment data among AIS patients and standard growth charts for Chinese pediatric population. Results: 1. Children with AIS grew slightly less than the mean before 6 months of age, and then, height gradually increased before 12 years of age, from the median to +1 standard deviation (SD), according to the standard reference for Chinese pediatric population. After 12 years of age, height showed differently in profiles: The mean height in AIS patients gradually decreased from the mean to −1 SD, according to the standard for Chinese boys, and increased from the mean to +2 SD, according to the standard for Chinese girls. 2. The weights of children with AIS were greater than the mean standards of Chinese pediatric population from newborn to 11 years of age. From 12–16 years of age, the mean weight of children with AIS showed different profiles, from the mean to −1 SD, according to the standard for Chinese boys and from the mean to +1.5 SD, according to the standard for Chinese girls. 3. Weight standard deviation (WtSDS) and target height (THt) in northern Chinese AIS patients were significantly higher than those from the southern region (p = 0.035, 0.005, respectively). Age in northern Chinese AIS patients was significantly younger than those from the southern region (p = 0.034). No difference was found among birth weight (BW), birth length (BL), height standard deviation (HtSDS) and body mass index (BMI) in AIS patients from different regions (p > 0.05). 4. HtSDS and WtSDS in complete AIS (CAIS) patients were higher than those in partial AIS (PAIS) patients without significant difference (p > 0.05). Conclusions: Growth of children with AIS varied to different degrees. AIS patients seemed not to experience a puberty growth spurt. CAIS and PAIS patients show little difference in their growth. Regional differences have no effect on the height but influence the weight of AIS patients. [ABSTRACT FROM AUTHOR]

Height-for-age Z-score (HAZ) curves are widely used for detecting children with stunting. The aim of this study was to provide smoothed HAZ growth reference values and their curves for Pakistani children and adolescents aged 2-18 years. The prevalence of stunting in Pakistani children was determined. A total of 10,668 healthy Pakistani participants were included. Information related to age, sex, city of residence and height (cm) was used. Age- and sex-specific smoothed HAZ growth reference values and associated graphs were obtained using the lambda-mu-sigma (LMS) method. The prevalence of stunting was calculated by applying WHO 2007 and USCDC 2000 height-for-age references and local reference of the study population. In both sexes, the smoothed HAZ curves increased with age. For 2 and 3 years of age, the height values of the girls were greater than those of the boys. The boys were then taller than the girls. Comparing our median height (z = 0) growth reference data from WHO, USCDC and corresponding data from other countries, Pakistani children and adolescents have significantly different reference values than their counterparts in the reference group. A marked overestimation of the prevalence of stunting was observed (10.8% and 17.9% according to WHO and USCDC, respectively) compared to the local reference (3.0%). It is recommended that the prevalence of stunting in children and adolescents is determined by applying local height growth references to plan health strategies and treatments in the local population.

Simple Summary: The present review evaluates twenty years (2001 to 2021) of the study of growth and performance in local chicken breeds worldwide. The assessment of methodological approaches and their constraints when intending to fit for data derived from often endangered autochthonous populations was performed. The evaluation of conditioning factors on the impact that publications reporting on research progresses in the field have on the scientific community and how such advances are valued suggests the need to seek new methodological alternatives or statistical strategies. Such strategies must meet the requirements of local populations which are characterized by reduced censuses, a lack of data structure, highly skewed sex ratios, and a large interbreed and variety variability. The sustainable conservation of these populations cannot be approached if scientific knowledge on their productive behaviour is not reinforced in a manner that allows distinctive products to be put on the market and be competitive. A review of the scientific advances in the study of the growth and performance in native chicken breeds and varieties over the past 20 years was performed. Understanding the growth patterns of native breeds can only be achieved if the constraints characterizing these populations are considered and treated accordingly. Contextually, the determination of researchers to use the same research methods and study designs applied in international commercial poultry populations conditions the accuracy of the model, variability capturing ability, and the observational or predictive performance when the data of the local population are fitted. Highly skewed sex ratios favouring females, an inappropriate census imbalance compensation and a lack of population structure render models that are regularly deemed effective as invalid to issue solid and sound conclusions. The wider the breed diversity is in a country, the higher the scientific attention paid to these populations. A detailed discussion of the most appropriate models and underlying reasons for their suitability and the reasons preventing the use of others in these populations is provided. Furthermore, the factors conditioning the scientific reception and impact of related publications used to transfer these results to the broad scientific public were evaluated to serve as guidance for the maximization of the success and dissemination of local breed information. [ABSTRACT FROM AUTHOR]

The main objective of this work is to introduce a stochastic model associated with the one described by the T-growth curve, which is in turn a modification of the logistic curve. By conveniently reformulating the T curve, it may be obtained as a solution to a linear differential equation. This greatly simplifies the mathematical treatment of the model and allows a diffusion process to be defined, which is derived from the non-homogeneous lognormal diffusion process, whose mean function is a T curve. This allows the phenomenon under study to be viewed in a dynamic way. In these pages, the distribution of the process is obtained, as are its main characteristics. The maximum likelihood estimation procedure is carried out by optimization via metaheuristic algorithms. Thanks to an exhaustive study of the curve, a strategy is obtained to bound the parametric space, which is a requirement for the application of various swarm-based metaheuristic algorithms. A simulation study is presented to show the validity of the bounding procedure and an example based on real data is provided. [ABSTRACT FROM AUTHOR]

The modeling of karst water level fluctuations is a crucial task in the water resource management of vulnerable karstic areas. In the Transdanubian Range (East Central Europe, Hungary), from 1950 to 1990, coal and bauxite mining were carried out, with large amounts of karst water being extracted, thus lowering the water table by amounts ranging between 10 and 100 m. Since the cessation of mining activities in the early 1990s, the volume of natural recharge has exceeded the amount of dewatering, and the system has begun to return to its original undisturbed state. This apparently welcome development does, however, bring economic and technical engineering problems. The estimation and prediction of such water level changes is often tackled via the use of deterministic approaches, however, in the present case, it is also addressed with an alternative approach using trend estimation to monthly water level data from 107 karst water wells over the period 1990–2017. To approximate the change in karst water levels, (i) growth curve models were fitted to the monthly data, allowing the estimation of karst water levels, at least as far as 2030. Similarly, this was also done with (ii) deterministic modelling in order to describe the recovery process up to 2030. Specifically, measured and predicted values for karst water level were used to derive interpolated (kriged) maps to compare the forecasting power of the two approaches. Comparing the results of the trend analysis with those of the traditional deterministic modelling results, it is apparent that the two approaches predict similar spatial distribution of water levels, but slightly different future water level values. [ABSTRACT FROM AUTHOR]

Preterm infant growth is a major health indicator and needs to be monitored with an appropriate growth curve to achieve the best developmental and growth potential while avoiding excessive caloric intake that is linked to metabolic syndrome and hypertension later in life. New international standards for size at birth and postnatal growth for preterm infants are available and need implementation in clinical practice. A prospective, single center observational study was conducted to evaluate the in-hospital and long-term growth of 80 preterm infants with a mean gestational age of 33.3 ± 2.2 weeks, 57% males. Size at birth and at discharge were assessed using the INTERGROWTH-21ST standards, at preschool age with World Health Organization (WHO) child growth standards. The employment of INTERGROWTH-21ST Preterm Postnatal longitudinal standards during the in-hospital follow-up significantly reduced the diagnosis of short term extrauterine growth restriction when compared to commonly used cross sectional neonatal charts, with significant lower loss of percentiles between birth and term corrected age (p < 0.0001). The implementation of a package of standards at birth, preterm postnatal growth standards and WHO child growth standards proved to be consistent, with correlation between centile at birth and at follow-up, and therefore effective in monitoring growth in a moderate and late preterm infant cohort without chronic or major morbidities. Infants identified as small for gestational age at birth showed significantly more frequently a need for auxological referral. [ABSTRACT FROM AUTHOR]

Pasture-based livestock production is impacted by management and weather. In pastures, there is conflict between leaf retention for plant growth and leaf harvest for animal nutrition. Defoliated pastures with low light interception (LI) may have a low forage growth rate (FGR), while excessive growth shades leaves, reducing FGR and resulting in an S-shaped regrowth curve. To optimize production, it is best to keep FGR linear. Three studies were conducted to evaluate the impact of management and weather on FGR. Replicated pastures were used to measure FGR when grazed from 25 to 10 cm and allowed to regrow. The impact of alternative defoliation timings and intensities on FGR were studied using clipped treatments at three recovery intervals and two stubble heights. Variability in FGR was studied using a field validated plant growth model. Of the 24 growth periods studied, two displayed exponential, 12 linear and 10 linear-plateau growth. There was no effect of FM on growth curve form. In May and June, LI increased with canopy height, up to 0.93. Stubble height and days of growth impacted FGR with an interaction. There was no treatment impact on root density. Weather caused variation in FGR. A low FGR risk occurs at high elevations; greater risk occurs east of the plateau. [ABSTRACT FROM AUTHOR]

This paper aims to assess important forest parameters, including tree density, diameter at breast height (DBH), and age distribution, investigate the dynamic growth of miombo tree species, and employ this information to design a management framework in miombo forests. The delineation of the management zones was based on unsupervised land cover classification that began with three zones where ground data was collected and increased to five zones. Eighteen circular plots (25.2 m radius) were randomly distributed over the study areas to assess the current situation and potential growth patterns for each species. The patterns of the six most representative tree species of miombo in Angola were described and we used KORFiT 2.4 software to fit data and develop growth curves for at least three miombo species. Growth function fitness was evaluated by root mean squared error (RMSE), coefficient of determination (R2), significance of the parameters (p < 0.05), and Akaike’s information criterion (AIC). The diameter distribution of miombo tree species resembled a typical distribution of uneven-aged forest stands; higher DBH classes had lower abundances of tree species. Logistic and Gompertz growth functions were the best fits for miombo tree species. Brachystegia spiciformis Benth., is suggested as a potential species for timber management in the region because they displayed high growth potential to more quickly reach an assumed minimum DBH of 20 cm. This study concluded that miombo forest stands present an irregular structure in which DBH distribution illustrated only two patterns: many small stems and a bimodal forest structure. [ABSTRACT FROM AUTHOR]

Different versions of the lognormal diffusion process with exogenous factors have been used in recent years to model and study the behavior of phenomena following a given growth curve. In each case considered, the estimation of the model has been addressed, generally by maximum likelihood (ML), as has been the study of several characteristics associated with the type of curve considered. For this process, a unified version of the ML estimation problem is presented, including how to obtain estimation errors and asymptotic confidence intervals for parametric functions when no explicit expression is available for the estimators of the parameters of the model. The Gompertz-type diffusion process is used here to illustrate the application of the methodology. [ABSTRACT FROM AUTHOR]