Hybrid mixture theory based moisture transport and stress development in corn kernels during drying: Validation and simulation results

Effect of ultrasound technique to improve quality of Iranian industrial honey by controlling crystallization process

This experiment aimed to assess the effects of ultrasound techniques on the quality of Iranian industrial honey. Honey samples were subjected to ultrasound waves at different frequencies and various parameters. The results showed that both ultrasound treatments (30 or 42 kHz) changed the physical, biochemical, antioxidant, and antibacterial characteristics of honey. Ultrasound treatments at 20 or 45°C for 1, 5, or 10 min reduced moisture, acidity, sugars, ABTS levels, 5-hydroxymethylfurfural content, clostridium, aerobic mesophilic bacteria count, and osmophile count while increasing diastase, phenol, and proline levels. Ultrasound treatment of honey samples at 30 and 42 kHz and different temperatures for varying durations led to a decrease in acidity after 90 and 180 days. Treating honey samples with 42 kHz ultrasound at 45°C for 10 min led to a significant reduction in the amount of reducing sugar. Ultrasonication at different frequencies and temperatures led to higher levels of phenol, ABTS, and proline production, along with a considerable decrease in the total count of aerobic mesophilic bacteria. Our study unveils the potential of ultrasonication to enhance honey quality through multifaceted improvements. Treatment significantly augmented phenolic content and antioxidant capacity, opening avenues for novel honey preservation and quality enhancement strategies. Additionally, ultrasonication effectively controlled honey crystallization while simultaneously improving biochemical, antioxidant, and antibacterial properties. This demonstrates its potential as a comprehensive strategy for honey quality improvement.

A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure

In order to optimize the convective drying process parameters of peanuts and to provide a theoretical basis for the scientific use of energy in the drying process, this study took single-particle peanuts as the research object and analyzed the heat and mass transfer process during convective drying. In addition, a 3D two-component moisture heat transfer model for peanuts was constructed based on the mass balance and heat balance theorem. Moreover, the changes in the internal temperature and concentration fields of peanut pods during the whole drying process were investigated by simulations using COMSOL Multiphysics. The model was validated by thin-layer drying experiments, compared with the one-component model, and combined with low-field NMR technology to further analyze the internal moisture distribution state of peanut kernel drying process. The results show that both models can effectively simulate the peanut thin-layer drying process, and consistency is found between the experimental and simulated values, with the maximum errors of 10.25%, 9.10%, and 7.60% between the simulated moisture content and the experimental values for the two-component model, peanut shell, and peanut kernel models, respectively. Free water and part of the weakly bound water was the main water lost by peanuts during the drying process, the change in oil content was small, and the bound water content was basically unchanged. The results of the study provide a theoretical basis to accurately predict the moisture content within different components of peanuts and reveal the mechanism of moisture and heat migration during the drying process of peanut pods.

Genome-wide association analysis for grain moisture content and dehydration rate on maize hybrids

For mechanized maize production, a low grain water content (GWC) at harvest is necessary. However, as a complex quantitative trait, understand the genetic mechanism of GWC remains a large gap, especially in hybrids. In this study, a hybrid population through two environments including 442 F1 was used for genome-wide association analysis of GWC and the grain dehydration rate (GDR), using the area under the dry down curve (AUDDC) as the index. Then, we identified 19 and 17 associated SNPs for GWC and AUDDC, including 10 co-localized SNPs, along with 64 and 77 pairs of epistatic SNPs for GWC and AUDDC, respectively. These loci could explain 11.39-68.2% of the total phenotypic variation for GWC and 41.07-67.02% for AUDDC at different stages, whose major effect was the additive and epistatic effect. By exploring the candidate genes around the significant sites, a total of 398 and 457 possible protein-coding genes were screened, including autophagy pathway and auxin regulation-related genes, and five inbred lines with the potential to reduce GWC in the combined F1 hybrid were identified. Our research not only provides a certain reference for the genetic mechanism analysis of GWC in hybrids but also provides an added reference for breeding low-GWC materials.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01349-x.

In Silico Prediction of Food Properties: A Multiscale Perspective

Several open software packages have popularized modeling and simulation strategies at the food product scale. Food processing and key digestion steps can be described in 3D using the principles of continuum mechanics. However, compared to other branches of engineering, the necessary transport, mechanical, chemical, and thermodynamic properties have been insufficiently tabulated and documented. Natural variability, accented by food evolution during processing and deconstruction, requires considering composition and structure-dependent properties. This review presents practical approaches where the premises for modeling and simulation start at a so-called “microscopic” scale where constituents or phase properties are known. The concept of microscopic or ground scale is shown to be very flexible from atoms to cellular structures. Zooming in on spatial details tends to increase the overall cost of simulations and the integration over food regions or time scales. The independence of scales facilitates the reuse of calculations and makes multiscale modeling capable of meeting food manufacturing needs. On one hand, new image-modeling strategies without equations or meshes are emerging. On the other hand, complex notions such as compositional effects, multiphase organization, and non-equilibrium thermodynamics are naturally incorporated in models without linearization or simplifications. Multiscale method’s applicability to hierarchically predict food properties is discussed with comprehensive examples relevant to food science, engineering and packaging. Entropy-driven properties such as transport and sorption are emphasized to illustrate how microscopic details bring new degrees of freedom to explore food-specific concepts such as safety, bioavailability, shelf-life and food formulation. Routes for performing spatial and temporal homogenization with and without chemical details are developed. Creating a community sharing computational codes, force fields, and generic food structures is the next step and should be encouraged. This paper provides a framework for the transfer of results from other fields and the development of methods specific to the food domain.

Modelling Volume Change and Deformation in Food Products/Processes: An Overview

Volume change and large deformation occur in different solid and semi-solid foods during processing, e.g., shrinkage of fruits and vegetables during drying and of meat during cooking, swelling of grains during hydration, and expansion of dough during baking and of snacks during extrusion and puffing. In addition, food is broken down during oral processing. Such phenomena are the result of complex and dynamic relationships between composition and structure of foods, and driving forces established by processes and operating conditions. In particular, water plays a key role as plasticizer, strongly influencing the state of amorphous materials via the glass transition and, thus, their mechanical properties. Therefore, it is important to improve the understanding about these complex phenomena and to develop useful prediction tools. For this aim, different modelling approaches have been applied in the food engineering field. The objective of this article is to provide a general (non-systematic) review of recent (2005-2021) and relevant works regarding the modelling and simulation of volume change and large deformation in various food products/processes. Empirical- and physics-based models are considered, as well as different driving forces for deformation, in order to identify common bottlenecks and challenges in food engineering applications.

Study on drying characteristics of corn based on 3D model

In this study, the moisture diffusion process and mass transfer resistances for the drying process of corn were studied numerically. A 3D mathematical model for the heat and mass transfer of the hot air drying of corn was established. The heterogeneity of the corn kernels' physical structure was designed by multi-component modeling of the corn geometry. The distributions of the temperature and moisture inside the kernel during the drying process were simulated by COMSOL Multi physics software. The effects of drying air temperature, relative humidity, and wind velocity on the mass transfer process of drying corn were analyzed. The pericarp resistance comprised the majority of the mass transfer resistance in the drying process. The drying air temperature significantly reduced pericarp resistance. The higher the wind velocity was, the lower the boundary layer resistance.

Genetic dissection of grain water content and dehydration rate related to mechanical harvest in maize

BACKGROUND

The low grain water content (GWC) at harvest is a prerequisite to mechanical harvesting in maize, or otherwise would cause massive broken kernels and increase drying costs. The GWC at harvest in turn depends on GWC at the physiological maturity (PM) stage and grain dehydration rate (GDR). Both GWC and GDR are very complex traits, governed by multiple quantitative trait loci (QTL) and easily influenced by environmental conditions. So far, a number of experiments have been conducted to reveal numbers of GWC and GDR QTL, however, very few QTL have been confirmed, and no QTL has been fine-mapped or even been cloned.

RESULTS

We demonstrated that GWCs after PM were positively correlated with GWC at PM, whereas negatively with GDRs after PM. With a recombinant inbred line (RIL) population, we identified totally 31 QTL related to GWC and 17 QTL related to GDR in three field trials. Seven GWC QTL were consistently detected in at least two of the three field trials, each of which could explain 6.92-24.78% of the total GWC variation. Similarly, one GDR QTL was consistently detected, accounting for 9.44-14.46% of the total GDR variation. Three major GWC QTL were found to overlap with three GDR QTL in bins 1.05/06, 2.06/07, and 3.05, respectively. One of the consistent GWC QTL, namely qGwc1.1, was fine-mapped from a 27.22 Mb to a 2.05 Mb region by using recombinant-derived progeny test. The qGwc1.1 acted in a semi-dominant manner to reduce GWC by 1.49-3.31%.

CONCLUSIONS

A number of consistent GWC and GDR QTL have been identified, and one of them, QTL-qGwc1.1, was successfully refined into a 2.05 Mb region. Hence, it is realistic to clone the genes underlying the GWC and GDR QTL and to make use of them in breeding of maize varieties with low GWC at harvest.

X-ray computed tomography for quality inspection of agricultural products: A review

The quality of agricultural products relates to the internal structure, which has long been a matter of interest in agricultural scientists. However, inspection methods of the opaque nature of internal information on agricultural products are usually destructive and require sample separation or preparation. X-ray computed tomography (X-ray CT) technology is one of the important nondestructive testing (NDT) technologies without sample separation and preparation. In this study, X-ray CT technology is used to obtain two-dimensional slice images and three-dimensional tomographic images of samples. The purpose of the review was to provide an overview of the working principle of X-ray CT technology, image processing, and analysis. This review aims to focus on the development of the agricultural products (e.g., wheat, maize, rice, apple, beef) and its applications (e.g., internal quality evaluation, microstructure observation, mechanical property measurement, and others) using CT scanner. This paper covers the aspects regarding the advantages and disadvantages of NDT technology, especially the unique advantages and limitations of X-ray CT technology on the quality inspection of agricultural products. Future prospects of X-ray CT technology are also put forward to become indispensable to the quality evaluation and product development on agricultural products.

Transport Mechanisms and Quality Changes During Frying of Chicken Nuggets--Hybrid Mixture Theory Based Modeling and Experimental Verification

Hybrid mixture theory (HMT) based 2-scale fluid transport relations of Takhar coupled with a multiphase heat transfer equation were solved to model water, oil and gas movement during frying of chicken nuggets. A chicken nugget was treated as a heterogeneous material consisting of meat core with wheat-based coating. The coupled heat and fluid transfer equations were solved using the finite element method. Numerical simulations resulted in data on spatial and temporal profiles for moisture, rate of evaporation, temperature, oil, pore pressure, pressure in various phases, and coefficient of elasticity. Results showed that most of the oil stayed in the outer 1.5 mm of the coating region. Temperature values greater than 100 °C were observed in the coating after 30 s of frying. Negative gage-pore pressure (p(w) < p(g)) magnitudes were observed in simulations, which is in agreement with experimental observations of Sandhu and others. It is hypothesized that high water-phase capillary pressure (p(c) > p(g)) in the hydrophilic matrix causes p(w) < p(g), which further results in negative pore pressure. The coefficient of elasticity was the highest at the surface (2.5 × 10(5) Pa) for coating and the interface of coating and core (6 × 10(5) Pa). Kinetics equation for color change obtained from experiments was coupled with the HMT based model to predict the color (L, a, and b) as a function of frying time.

Development of drying-induced stresses in pharmaceutical granules prepared in continuous production line

The phenomenon of development of drying-induced stresses has been given a through consideration in the literature on drying of many products. At the same time, to the best of our knowledge, the open published sources contain no information on drying stresses in pharmaceutical granules prepared by continuous manufacturing methods. To study the appearance and evolution of drying-induced stresses in pharmaceutical granules during their production, in this work a theoretical model of drying of single wet pharmaceutical granule has been developed and successively validated by published experimental data obtained on ConsiGma™ continuous from-powder-to-tablet production line (GEA Pharma Systems). The results demonstrate that elevated temperatures of drying air result in faster drying process (which reduces the specific cost of the final product), but, on the other hand, quick drying leads to substantial drying-induced stresses which may damage the granule microstructure, resulting in cracking or even breakage of granules. The drying-induced stresses increase with drying temperature, porosity and size of dense non-hollow granules. The negative effects promoted by the drying-induced stresses should be taken into consideration when choosing operating conditions of continuous production lines including drying of pharmaceutical granules.

Analysis of maize ( Zea mays ) kernel density and volume using microcomputed tomography and single-kernel near-infrared spectroscopy

Maize kernel density affects milling quality of the grain. Kernel density of bulk samples can be predicted by near-infrared reflectance (NIR) spectroscopy, but no accurate method to measure individual kernel density has been reported. This study demonstrates that individual kernel density and volume are accurately measured using X-ray microcomputed tomography (μCT). Kernel density was significantly correlated with kernel volume, air space within the kernel, and protein content. Embryo density and volume did not influence overall kernel density. Partial least-squares (PLS) regression of μCT traits with single-kernel NIR spectra gave stable predictive models for kernel density (R(2) = 0.78, SEP = 0.034 g/cm(3)) and volume (R(2) = 0.86, SEP = 2.88 cm(3)). Density and volume predictions were accurate for data collected over 10 months based on kernel weights calculated from predicted density and volume (R(2) = 0.83, SEP = 24.78 mg). Kernel density was significantly correlated with bulk test weight (r = 0.80), suggesting that selection of dense kernels can translate to improved agronomic performance.