There is increasing interest in Ontario about the impact of grain dryer sound emissions on neighbours as rural populations increase. Predicting the sound levels at particular distances from a dryer is complicated because different types of dryers produce different amounts of sound, and grain dryers are partially or fully surrounded by other structures, most commonly large steel grain storage bins. Prior studies by the research team measured sound levels in the areas around multiple Ontario grain dryers. However, since actual sites are complex, it is difficult to use measured data at one site to accurately predict sound conditions at a different site. Acoustic modelling software provides an opportunity to simulate specific sites as well as general configurations of dryers and structures to get insights needed to provide general guidelines for sound propagation at grain dryers and to model how different mitigations (like barriers or operational changes) would impact sound levels at neighbouring locations. This study used SoundPLAN software to trial three different sound propagation models (ISO 9613-2, CnossosEU and Nord 2000) to predict sound level distribution around actual grain dryers. Simulation accuracy was quantified using the degree of agreement with measured sound levels collected by the research team at four different grain drying sites in southern Ontario. It was found that error levels of less than 5 dB(A) could be consistently achieved using the more accurate CnossosEU model. Specific recommendations for simulating sound propagation from grain dryers and similar agricultural facilities will be reviewed.

New approaches to energy supply for low temperature grain drying have the potential to reduce energy costs, improve grain quality and yield climate benefits. Current options for drying grain using alternative energy sources are few, necessitating the development of new dryers optimized for this type of drying. This research project is studying a full-scale prototype of an electrically-powered air source heat pump, horizontal flow, low temperature batch dryer. Initial drying experiments have been completed in the prototype dryer with corn. The initial tests quantified the energy intensity and energy consumption of corn drying in the prototype dryer. Further analysis of the efficiency of the dryer will be included in future research and used to inform refinement of the prototype dryer design. Supporting lab-scale experiments have also been conducted to replicate drying processes to predict likely drying efficiency with other grains in a range of operating conditions. These lab tests provide supplemental data under controlled conditions to analyze how different variables impact the drying process. Tests of multiple drying iterations were conducted with cycles of rehydrated and dried grain. The low temperature drying cycles were shown to have negligible impact on grain germination rates. This ongoing research using full-scale field studies and laboratory experiments has already provided insights into the potential benefits of low temperature drying at a larger scale, which may include reduced greenhouse gas emissions, and lower and less variable energy costs than conventional high temperature drying with fossil fuels.

The main objective of this research was to develop a numerical model to simulate the transport phenomena involved in grain drying processes in mixed-flow grain dryers by coupling the discrete element method (DEM) and computational fluid dynamics (CFD), and utilize the proposed model for the design assessment and optimization of mixed-low grain dryers. The proposed model was validated against experimental literature data in terms of grain temperature and moisture content distribution, as well as grain movement and airflow pattern. Close agreements were achieved between simulated results of the coupled CFD-DEM model and published experimental data, with an average difference of 4.3% for grain temperature and 2.5% for grain moisture content. Using empirical models in the literature, risks of germination reduction and fissure (stress cracking) of grain kernels during drying was predicted based on the grain conditions simulated by the coupled CFD-DEM model. The proposed model provides a versatile numerical tool to assess the performance of mixed-flow grain dryers by quantify the uniformness of grain moisture content and temperature, as well as the risk of germination reduction and stress cracking of grain kernels. The model was applied to assessment of different duct designs and layouts in mixed-flow grain dryers. It was found that the air ducts with 60-degree angles resulted in the best drying performance among the five layouts that were simulated. The best layout had the ratio of vertical distance to duct height of 1.35 and the ratio of horizontal distance to duct width of 1.5.

Drying is essential for grain corn production to preserve harvested goods in high humidity. Current processes rely on fossil fueled heat sources, greatly contributing to their global warming potential (GWP) through greenhouse gas (GHG) emissions. A proposed solution for improving grain drying is the use of electric air source heat pumps (HPs) which are proven to increase efficiency while decreasing GHG emissions. This study uses a life cycle assessment to justify the environmental feasibility of transitioning from fossil fuels to HPs. The project boundaries included the manufacturing of heating units to sufficiently dry corn. Different electricity sources were assessed. For Ontario, a GWP reduction of more than 22.5 times was achieved by using HPs over fossil fuel heaters. For other provinces, 100% natural gas, and 100% coal sourced electricity, reductions in GWP over fossil fuel dryers were shown. The effect of the coefficient of performance (COP) on the GWP was studied. Assuming higher COP resulted in lower GWP: a COP of 9.5 had 2.4 times smaller GWP than a COP of 3.5. However, the COP of 3.5 still achieved 15.4 and 13.0 times less GWP than using natural gas and propane heaters respectively. The HP construction contributed significantly to its overall GWP (13.8%). The working fluid (R134a) was a major contributor to GWP (15.0%) but could be mitigated by choosing a cleaner working fluid (e.g. R1234z(E)). In summary, using electric HPs in Ontario grain drying appears to be an environmentally feasible substitute for propane and natural gas heaters.

Drying stands as a pivotal process in manufacturing, essential for removing moisture from materials. However, its energy-intensive nature leads to substantial energy consumption, accounting for more than 12% of total industry energy usage. Moreover, conventional thermal drying systems exhibit low energetic performance, contributing to environmental harm. The study aimed to introduce and compare three novel exergy-based real-time control schemes for manipulating and adjusting the recycle ratio of outflow air in dryers to enhance energetic and exergetic performance. The control schemes developed in the study include Scheme I, based on the thermophysical exergy efficiency, Scheme II, which considers the outflow wet exergy rate below a constant threshold value and Scheme III, which incorporates a varying threshold value for the outflow wet exergy rate. The drying process for poplar wood chips involved examining two drying air temperatures (55-70 ºC) and two air volume flow rates (360‒450 m3/h). Additionally, the total exergy of air exhaust from the drying chamber was also fractionated into thermophysical and wet exergies for further assessing the effect of the recycle fraction. The study found that the universal exergetic efficiency of the drying chamber varied from 30.2% to 95.5%, and the overall functional exergetic efficiency of the drying system suggested that implementing developed control schemes could enhance the functional exergetic efficiency of the dryers. This study revealed that control scheme III, demonstrating the highest improvement of up to 75%, could be implemented on industrial dryers to improve the energetic performance and environmental sustainability by recovering exergy from outflow air.

Atmospheric Freeze Drying (AFD) has emerged as a promising alternative to the conventional freeze-drying method (VFD). This technology is characterized by its ability to operate under atmospheric conditions, offers lower energy consumption, continuous processing, and cost-effectiveness, especially in cold climates where natural cooling can be exploited. Despite its advantages, AFD faces challenges such as prolonged drying times and potential product shrinkage, which are addressed through innovative hybrid techniques, incorporating thermal or mechanical energy inputs to enhance drying efficiency. This literature review presented a comprehensive analysis of recent advancements in AFD technology by examining both the fundamental principles underlying the process and innovative approaches designed to improve its efficiency. The investigation of AFD fundamentals demonstrated the importance of vapor partial pressure gradients and external factors such as boundary layer effects in enhancing the drying process. Hybrid approaches, such as heat pumps, vortex tubes, expanders, ultrasonic and microwave assistance, adsorbent usage, and fluidization, have shown significant savings in energy consumption and improvements in product quality. Additionally, this review examined the influence of process parameters such as drying temperature, air velocity, and sample characteristics on drying kinetics and product attributes, offering insights into optimal process conditions. Finally, the review explored modeling approaches, including diffusion models and the Uniformly Retreating Ice Front (URIF) model to provide a comprehensive understanding of drying kinetics, facilitating the optimization of drying processes. Despite the promising advancements, this review emphasized the need for ongoing research to and extend the applicability of advanced AFD technologies across various industrial sectors.

With rising concerns on sustainability, fuel sourcing for continuous dryers is shifting towards natural gas and propane, however, carbon dioxide (CO2) emission is inevitable, subject to levies. The continuous drying process, reliant on electrical energy along with fuel, results in a total emission of 0.209 tonnes (t) of CO2 equivalent/Gigajoule. The levy is expected to increase at $15/year until 2030 capping at $170/tCO2e on the top of the actual fuel cost. To address these issues, a three-year (2021-2023) on-farm study was conducted with 5 different dryers in Alberta. The initial grain moisture of 15 to 23% wet basis (wb) was dried at 49-93.3℃ with discharge rates of 10,402-51,709 kg/h (385-1800 bu/h). Actual energy was calculated with weather-normalized fuel and electricity consumption. Results showed that levies were 47% (average) higher than fuel costs for any dryer. Double-flow dryer emitted the lowest emission with the lowest cost due to its air-recirculation system. Approximately 20% cost increment was observed per point of initial moisture decrease from 23 to 18% wb. However, a 32% cost increase was observed from 17 to 15% wb. This showed that grain moisture below 17% wb should not be dried in high-temperature dryers unless waste heat is reused for operations to promote drying sustainability.

Drying and storage at sub-zero temperatures affects the quality of stored grains and oilseeds. This review explored the efficacy of sub-zero temperatures in prolonging the viability of food grains and oilseeds. Seed survival mechanisms, particularly the formation of intracellular glasses, play a crucial role in preserving biological structures in seeds. The focus was primarily on orthodox seeds, which are characteristic of most agricultural crops and known for their desiccation tolerance at sub-zero temperature conditions. Drying at these low temperatures along with a high airflow inhibits ice crystal formation and slows down metabolic processes. This property eventually helps in prolonging the seed survival. The review also discussed the varying moisture content thresholds for different seeds and the risk of spoilage and maintaining nutritional quality. Additionally, the review highlighted the environmental benefits of this approach, aligning with the objectives of sustainable agriculture by minimizing emissions and maximizing resource efficiency.

A particularly wicked problem faced by modern farmers is the safe storage and preservation of cereal grains. A common approach to find the bulk moisture content of grain uses the electrical permittivity. Permittivity is a complex quantity, consisting of both real and imaginary parts. Most common capacitive moisture sensors operate by measuring the real part only and use the permittivity of water to make inference to volumetric moisture content of grain. However, valuable information is stored in both real and imaginary parts of the permittivity. Due to the close relationship with density, temperature and moisture content, a true understanding of the electrical permittivity of grain is vital for high-accuracy physical measurements.

We have obtained the full complex electrical permittivity of cereal grains using a coaxial transmission-line device (the ``permittivity cell'', or PC) in the frequency range 400 kHz to 1.3 GHz. Analysis is performed using a combination of numerical and analytical methods, including HFSS. We calibrate the device using fluids described by the Debye model. With non-parametric numerical inversion we recover the both components of the complex permittivity from the scattering matrix elements. We perform simultaneous inversion of both open and short cap measurements, ensuring the physicality of recovered solutions. Using the Kramers-Kronig approach, we find that non-parametric cereal grain permittivity results can be represented by an analogous parallel RC circuit. The implications of these findings and the possibility of utilizing this approach for advanced sensing applications will be discussed.

Grain storage is the process of holding back entropy; outside of removing waste, there is no known way to improve the quality of grain post-harvested. As a result, the farmer is faced with the difficult issue of storing grain, risking spoilage, or selling it at a lower price. Current grain management technologies are reactive and can only identify spoilage after it has occurred. In contrast, the challenge of a more predictive approach is that it requires a detailed understanding of the grain. One essential feature that needs to be understood to represent a grain bin is the pressure that the grain experiences, which affects grain compaction, aeration efficiency, and overall storage management.

An innovative approach to radial pressure distribution analysis in grain bins, utilizing a novel triaxial pressure sensor, is introduced in this study. Such sensors can be placed anywhere in a bin while filling to measure the x, y, and z pressures experienced by the grain in that specific region. Our objective involves using these sensors to refine and validate new mathematical models, specifically addressing the unknown variability of the vertical-to-lateral pressure ratio (k) throughout a bin. These sensors are deployed at strategic locations within a grain bin to generate a detailed pressure distribution map. This research aims to develop a comprehensive framework that improves our understanding of grain pressure fields and serves as a cornerstone for future predictive grain management approaches, including the application of digital twins to grain storage.

Ensuring a seamless and consistent flow of bulk grain is vital for efficient handling, processing, and storage, particularly with wheat, where impurities can significantly affect handling dynamics and storage properties. This study examined the impact of three dockage sizes (smaller than 1.1 mm, 1.1 to 2 mm, and larger than 3.3 mm) at four dockage percentages (from 0 to 10%) on the repose angle of dry wheat with 7.5% moisture content (wet basis). Employing an exponential growth model with two parameters as a regression framework, the study revealed complex relationships between dockage attributes and wheat's repose angle, assessed using both filling and emptying methods. The findings indicated variations between predicted and measured repose angles, with differences ranging from 0.01 to 1.62o for filling angles and from 0.56 to 4.56o for emptying angles. By illuminating the intricate interplay between dockage attributes and wheat behavior, especially in controlled silo environments, this research could enhance our understanding of storage condition optimization. These insights might offer valuable guidance for improving grain flow efficiency and ensuring optimal storage practices in agriculture.

Deoxynivalenol (DON) contamination from Fusarium graminearum colonization poses a significant challenge in Canadian wheat production. Both high atmospheric and interstitial CO2 concentration in field and storage, respectively, have been associated with fungal growth and mycotoxin production in grains. This study aimed to investigate DON production under different airtight conditions during the storage of wheat. Wheat samples with different moisture contents (17, 20 and 23%) were treated by: 1) natural infestation, 2) supplemental Fusarium inoculation, and 3) disinfestation followed by inoculation with Fusarium. The prepared samples were stored in sealed flasks at room temperature. The flasks were opened at intervals of 1, 3, 7, or 12 days. Prior to each opening, the concentrations of oxygen and carbon dioxide were measured using gas chromatography. Differences in CO2 and DON production under different storage condition were observed. The preliminary results will be presented.

Harvested grain is stored until the harvested grain is processed and delivered to customers for consumption. Insect infestation in stored grain not only causes nutrient degradation and dry matter loss, but also initiates mold growth inside the stored grain bulks. Detecting insect activities and monitoring insect populations is critical during storage as it helps in taking immediate corrective action to prevent further damage. Traditional sampling methods, although cheap, require skilled labor and are incapable of continuously monitoring insect activities and their population dynamics. Timely and in situ insect monitoring is needed. This study reviewed the application of in situ insect detection techniques combined with machine learning. Machine learning has been emerging for insect detection because it can classify various types of stored product insects. Technologies including image processing, acoustic measurements, mass spectroscopy, polymeric chain reaction (PCR) and electronic nose have been studied in literatures to produce real time detection of different species and different life stages of an insect in stored grain bulks. While suitable models including artificial neural networks, YOLO models, multivariate curve fittings are trained to classify or quantify the infestation level. These artificial intelligent-support techniques providing the next level of sensing and handling huge data at any point of time during the insect monitoring. The role of these new techniques in Integrated Pest Management of the stored grain products is also reviewed.

Plant breeding and genetic engineering have been used to establish high-yielding, drought-tolerant, disease-resistant, short-maturity corn varieties. However, there is no certainty that these varieties conform to the established thermal property values in literature, and the existing moisture content-based and proximate composition-based predictive models. This study evaluated the thermal properties of ten (10) corn varieties at five different moisture content levels, ranging from 13 to 21%. The aim was to examine the potential application of moisture content- and proximate composition models in predicting the thermal properties of corn varieties. Thermal properties were evaluated using existing reference scientific methods. The Moisture content – variety interaction significantly affected most of the thermal properties. The thermal conductivity, diffusivity, and specific heat ranged between 0.11 – 0.55 W m-1 K-1, 0.09-0.21 mm2 s-1, and 1.44 – 4.24 kJ kg-1 K-1, respectively. The predictive strength of both moisture content and proximate composition-based models varied greatly among corn varieties for thermal properties. The corn thermal properties were largely described by the Gaussian Process Regression (GPR) models compared to Linear Regression machine learning models. The existing moisture content and proximate composition-based predictive models are more suited for descriptive than predictive application with corn varieties in U.S.

PAMI is performing research aimed at exploring the variables that impact agricultural productivity and the overall economic advantages and disadvantages of wetland drainage scenarios. The availability of yield data and field path data obtained over multiple years provides the opportunity for an observational study of the yield response in distinct field zones including the upland acres, the buffer zone around a wetland, and the wetland itself.

A financial model was created based on yield response in each zone to drive scenarios of no wetland drainage, partial drainage, and full drainage. Crop values and agronomic assumptions were applied based the Saskatchewan Crop Planning Guide. Consistently, the models showed an economic incentive to the producer for draining wetlands of $18 to $33 per cultivated acre.

The findings reveal that drained and farmed wetlands produce slightly lower yields then field average with substantial variability due to crop type, soil zone and precipitation. Furthermore, it is found that the effects of wetlands on crop yields extend well beyond the wetland where noticeably higher yields are found in the surrounding 50 m buffer zones of drained versus undrained wetlands. The results demonstrate the importance of considering wetland and buffer zone yield effects in wetland drainage decisions and improve our understanding of the costs and potentially required incentives for wetland conservation. Ongoing work explores the relationships of percent wetland area to overlap of farming inputs and to nuisance cost and the validation of the buffer yield effect using pre- and post-drainage yield data.

Food loss and waste (FLW) is a major sustainability challenge at all levels from local to global. FLW in industrial, commercial, and institutional (IC&I) sectors is large in quantity, wide in scope, and complex in source. Information regarding the scale, patterns, and environmental impacts of food waste in IC&I sectors is particularly fragmented. The goal of this research, therefore, is to better characterize the quantity, distribution, and impact of FLW in the IC&I sectors and recommend better strategies for managing FLW. Using Montreal as a case study, a geospatial model will be developed of patterns and the carbon emissions of food waste from the IC&I sectors. First, fragmented data from various IC&I sector stakeholders will be gathered within a common framework to build a systematized database of FLW across different sources and actors. Second, spatial analysis and systems modeling will be used to show the spatial distribution and identify spatial factors of FLW on a city scale. Third, life cycle assessment (LCA) will be used to estimate the carbon emissions related to FLW management. Finally, strategies will be investigated to reduce carbon emissions from FLW flow paths. This study will improve data, decision-making tools, and policy strategies for FLW management at all levels of government.

The management of municipal solid waste (MSW) poses a significant global environmental challenge. Landfills are important sources of greenhouse gas (GHG) emissions, particularly methane. However, accurate estimation of methane emissions from landfills in Canada remains challenging due to the lack of primary data and accurate models. The goal in this research is to improve estimates of methane emissions from Canadian landfills by using the one at Complexe Environ Connexions, Terrebonne, Quebec, as a case study. Several techniques are being used to measure methane fluxes, including eddy covariance, automated flux chambers, and smart survey flux chambers. Together, these techniques capture high-quality methane emission data, including quantification of any diurnal and seasonal variations. These data are being used together with published information to calibrate and validate computational models such as LandGEM. This research will inform the development of sustainable engineering solutions for the mitigation of methane emissions from Canadian landfills. The research is aligned with Canada's climate objectives and global agreements, thereby reinforcing the nation's commitment to reducing GHG emissions and promoting sustainable waste management practices.

The depletion of nutrients in the soil and the accumulation of nutrients in the water bodies are two major contradicting environmental issues. Hence, it is imperative to recover these nutrients from the water bodies and introduce them into the soil with slow-release properties to prevent further accumulation in the water bodies. Therefore, in this study, a nanocellulose based nanocomposite was fabricated to recover and release the nutrients. The synthesized nanocomposite was characterized through different techniques such as X-ray Diffraction Spectroscopy, Fourier Transform Infrared spectroscopy, Energy Dispersive X-ray Fluorescence spectroscopy, and Differential Scanning Calorimetry to decipher its structural properties, chemical composition, and thermal properties. The specific surface area and the pore distribution were determined through Brunauer-Emmett-Teller analysis. The surface charge and the stability of the nanocomposite was evaluated using Zeta sizer and the morphology was evaluated through Scanning Electron Microscopy. Further, the adsorption of the nutrients by the nanocomposites from wastewater were examined. Subsequently, the effect of different parameters influencing the adsorption including the pH, temperature, and concentration of the adsorbents and adsorbate were evaluated. The influence of the commonly present ions in the water and the organic matter were also evaluated. In addition, the reusability of the adsorbent was examined. Finally, the nutrient release studies were performed to understand its potential application of the nanocellulose nanocomposite as a slow-release organic fertilizer.

In response to the challenge of reducing GHG emissions and achieving carbon neutrality in livestock production, we propose a holistic systems approach tailored to integrated swine and corn/soybean systems. Our strategy encompasses integrated changes to cropping systems, feed production, and manure management, focusing on producing high-moisture corn and integrating anaerobic co-digestion systems to mitigate emissions.

Fundamental changes include harvesting high-moisture corn to eliminate grain drying and extend the growing season for cover crops, thus reducing carbon emissions and enhancing cover crop production opportunities. Our proposed approach incorporates co-digestion of swine manure, corn stover silage, and winter cover crops, alongside techniques to mitigate CH4, NH3, and N2O emissions from animal housing, manure management, and crop production.

Implementation of these changes requires adjustments throughout the production system. Row crop producers must transition to earlier corn harvests and cover crop planting, while farmers and feed processors must adapt storage and handling practices for high-moisture grain. Additionally, the feed production industry must effectively process high-moisture corn into swine feed, and the pork industry must adopt feeds derived from high-moisture grains. Furthermore, developing co-digestion systems supports these changes and facilitates biomass processing. Successful implementation hinges on the cooperation and adaptation of all stakeholders within this circular system.

This paper presents a comprehensive system plan detailing proposed technology changes and addressing obstacles to implementation. We aim to establish a more sustainable and environmentally friendly approach to swine and corn/soybean production through these integrated solutions while significantly reducing GHG emissions.

There has been a surge of interest in sustainable diets due to the growing climate crisis across the globe. In response, several attempts to estimate sustainable dietary intake scenarios have emerged for many countries including Canada. Yet, the influence of age, gender, and spatial distribution details have not been adequately incorporated into the existing proposed dietary scenarios. These factors vary the type, quantity, and nutrient quality requirements of dietary intake and in turn may impact the associated environmental implications. Therefore, this study examines the variations induced by age, gender, and spatial distribution in the environmental, nutritional, and economic implications of dietary intake among Canadians. Dietary intake data from the Canadian Community Health Survey, CCHS 2015, are examined with the SPSS Statistical software as well as Microsoft Excel models. Environmental impact data from dataFIELD and Our World in Data were sourced for environmental calculations. Also, food price data from the Food Price Hub of Statistics Canada were employed to compute the dietary cost. The expected impacts associated with the dietary intake across the life stages, gender, and provincial locations are highlighted as well as spatial hotspots. The application of these models is useful for outlining easy-to-adopt targeted sustainable dietary patterns for Canadians in the global bid to build sustainable and resilient food systems. Moreover, these findings will also form the basis for further work focused on designing sustainable dietary transition scenarios for all consumers in Canada.

This study presents the results of preparing a charcoal briquette derived from a combination of pine wood sawdust and pine cone biomass without any binders. The investigation focuses on the effects of hydrothermal heat pretreatments (HT) at temperatures of 280, 320, and 360 °C, alongside ozonation pretreatment (OZ) at durations of 60, 75, and 90 minutes. For each experiment, the pretreated samples were densified to prepare biomass briquette and then carbonized at 430 °C to prepare charcoal briquette without any binders. All experiments maintained consistent conditions regarding compressive force, initial humidity, particle size, and biomass material composition. Thermal and physical properties of the charcoal briquettes were measured for each experiment, with results subjected to statistical analysis. The findings showed that charcoal briquettes subjected to HT pretreatment and ozonation exhibit higher combustion character index and lower ash yields than those without pretreatment.

Furthermore, the pretreated samples demonstrated superior physical properties, including mass density and compressive strength, compared to untreated samples. Based on the research outcomes, optimal conditions for charcoal briquette production from pine wood waste and sawdust pretreated by HT method at 280 °C, and an OZ method duration of 75 minutes. It was found that the charcoal briquette prepared by pine wood sawdust and pine cone biomass pretreated by an OZ duration of 75 minutes and an HT pretreatment at 280 °C showed the best combustion and physical characteristics.

Microwave ovens are popular for their convenience, but uneven heating can affect the quality and safety of cooked food. A modified microwave oven with a fibre optic system was developed to investigate the effect of packaging on temperature distribution. The oven had a frequency of 2450 MHz and a rated output power of 1000 W. To evaluate the package geometry effect, baby potatoes (3-5 cm diameter; about 450 g) were arranged in layers within airtight polypropylene containers equipped with a steam vent hole and cooked at maximal power for 6 min. Potatoes were stacked in 3, 2, and 1 layer in the cylindrical (5.2 cm radius, 14.7 cm depth), cuboidal (14.5 L x 14.5 W x 8.5 H cm), and rectangular (19.5 L x 12.5 W x 4 H cm) containers, respectively. The results showed that package geometry and potato arrangement did not significantly affect the temperature profile in headspace and potatoes positioned at the container periphery in all the packages tested. Steam vent hole of 4 mm diameter had no significant effect on the time taken for the potatoes and headspace to reach the maximal temperature (100oC). However, the time taken to reach 100oC for the potatoes located at the centre was considerably longer for the cylindrical container (6 min) than the rectangular container (2 min). This study showed that minimizing the potato stack layer within a package would improve product temperature uniformity during microwave cooking.

Potato (Solanum tuberosum L.) is an important food crop and ranks fourth in the world after wheat, rice, and maize. Potato is usually consumed after processing with or without its peel where most of the phenolic compounds and glycoalkaloids are concentrated. Glycoalkaloids, a group of nitrogen-containing compounds are toxic to humans if consumed in high concentrations. Plant glycoalkaloids are toxic steroidal glycosides and the common types found in potatoes are α-solanine and α-chaconine. Canadian consumers are rarely exposed to toxic levels of glycoalkaloids that cause serious health effects. However, there are occasional reports of short-term adverse symptoms, usually from eating potatoes that contain elevated concentrations of glycoalkaloids like burning sensation in the mouth, nausea, vomiting, stomach and abdominal cramps, and diarrhea. Therefore, Health Canada has set the level of total glycoalkaloids (TGA ) concentrations to not exceed 200 mg/kg (2,00,000 ppb) fresh weight, in any of the potato variety before marketing. Thus, the current study seeks to estimate the level of TGA using analytical high-performance liquid chromatography (HPLC) technique in various potato varieties. Samples were placed under LED light, continuously for a period of twenty days after which the tubers were assessed for their TGA content at 0, 3-, 5-, 7- and 20-day intervals of light exposure and assessed for TGA content. The levels of TGA found in the analyzed potato samples were below maximum residue level, rendering them safe for human consumption.

Unripe plantain slices were pretreated, deep-fried, then their quality and shelf life were evaluated in this work. Pretreatment techniques were; an ultrasound probe; 20KHz frequency at 600W maximum power, dipping in honey, and soaking in sugar solution. Plantain slices, with average weight, thickness, and diameter of 3g, 3mm, and 30mm respectively were fried using sunflower oil at a temperature of 170 o C for 2, 4, 6, 8, and 10 minutes. The Moisture content (MC), oil uptake (OU), moisture diffusivity (MD), and carotenoid content (CC) of fried plantain chips were evaluated. The honey and sugar pretreatments caused the samples to have lower MC before frying compared with ultrasound and control (samples with no treatment). The lowest OU was seen with ultrasound and sugar samples. Moisture transfer rate correlation coefficient (R2) ranged from 0.90 to 0.99 demonstrating a good fit for the experimental data with the sugar sample having the highest MD. Statistically, the honey sample with the lowest k-value and highest CC retention was the best in taste, aroma, crispiness, greasiness, and overall acceptability when fried for 10 minutes using 30 semi-panelists. The pretreated sample fried for 2 minutes was best in color with a mean and S.D value of 9.18±0.94^e at P<0.05. Microbial analysis of samples pretreated with ultrasound had minimal coliform and other pathogenic bacteria as compared with other samples after 28 days in aluminum foil stored in 27o C condition. However, the various pretreatments were found to have some advantages in improving the quality of plantain chips.

The optimization of drying techniques for preserving the structural integrity and quality of dehydrated food products is critical in the food industry. This study examines the microstructural changes in potato samples subjected to freeze drying (FD), infrared drying (ID), and hot air drying (HD). The 3D X-ray micro-computed tomography was used to quantify morphological alterations across various drying intervals 4, 8, 12, and 16 hours. An Artificial Neural Network (ANN) was used to predict the quality changes across drying time. The study revealed that FD samples consistently demonstrated minimal shrinkage, with a notable increase in total porosity, predominantly open porosity, as drying time increased. Conversely, ID and HD samples exhibited considerable shrinkage and density changes, although ID samples experienced a significant porosity increase over time. The findings from this study indicated FD’s superiority in preserving microstructural integrity, enhancing porosity, minimizing density changes, and optimizing color retention, thereby underscoring its potential to improve product quality and shelf life but at the cost of increased energy consumption. ID and HD presented a more favorable energy consumption profile but compromised the sample structure. This study provided valuable insights for the food processing industry, guiding the selection of optimal drying techniques that balance energy efficiency to achieve desired product quality.

This research focused on the structural and allergenic characteristics of cod proteins, which pose challenges for seafood product development. The objective was to explore the impact of high-intensity ultrasound (HIU) on cod, particularly regarding protein structural changes and allergenicity reduction. Ultrasound was applied for various periods (0-60 minutes) to assess its effect on protein attributes. Significant findings include the decrease in total soluble protein and the transition of protein secondary structures from α-helices to β-sheets and disordered formations, as validated by FTIR and CD spectroscopy (p < 0.05). UV spectroscopy and scanning electron microscopy corroborated these alterations, showing protein denaturation and potential Maillard reactions. Analysis through SDS-PAGE revealed protein degradation and aggregation, and ELISA tests indicated a reduction in allergenic potential by up to 31.82%, especially after prolonged exposure (60 minutes). These changes demonstrate that ultrasound treatment can effectively modify protein configurations and diminish allergenicity. The findings suggest that HIU could be a valuable method for enhancing the safety and quality of seafood, paving the way for innovation within the food sector.

This research investigated the influence of a pulsing microwave pretreatment, on the osmotic dehydration of waxy skin highbush blueberries. Initially, fresh blueberries were subjected to 20% microwave power for one and a half minutes before undergoing osmotic dehydration for 8 hours in a 60 °Brix sucrose solution. The study evaluated the mass transfer and the reduction of total soluble solid content during osmotic dehydration, alongside assessments of texture and color, across four temperature levels (room temperature, 60 °C, 65 °C, and 70 °C). Results revealed that the most substantial decrease in total soluble solid content within the osmotic solution occurred during the initial phase of the process (0-4 hours), with a negligible and gradual decline thereafter (4-8 hours). Microwave pretreatment showed no impact on the chromatic characteristics of blueberries color, particularly in parameters a, b, and L parameters. Although microwave pretreatment did not significantly alter texture compared to untreated blueberry samples, it notably boosted the efficiency of osmotic dehydration at higher temperatures. Optimizing microwave pretreatment parameters hold promise for reducing both processing time and temperature requirements in osmotic dehydration processes, especially beneficial for large-scale processing of waxy skinned berries.

The aim of this study was to develop a synbiotic legume-based beverage powder using spray drying with maximum probiotic viability, enhanced shelf life, and consumer acceptability via response surface methodology. The synbiotic beverage was made using green mung beans (Vigna radiata L.) and red kidney beans (Phaseolus vulgaris L.) as prebiotic sources and Lacticaseibacillus casei as the probiotic. The optimization was done using Box-Behnken design with independent variables viz., inlet temperature of spray dryer (130-150 ℃), feed flow rate (20-30 mL/min), and gum acacia (GA) concentration (1-3%). The responses were total viable probiotic count (log CFU/mL), powder yield (%), and moisture content (%). The results showed that the optimized spray-dried power could be obtained at 130 ℃ inlet temperature, 20 mL/min feed rate and 2.32% GA concentration with maximum probiotic count (8.80 ± 0.06 log CFU/mL), yield (50.92 % ± 0.12) and desirable moisture content (50.92 % ± 0.12). The obtained synbiotic powder at optimized conditions also showed good powder characteristics (bulk, tapped & particle density, porosity, flowability, cohesiveness, dissolution, color, and encapsulation efficiency), desirable probiotic growth (>7 log CFU/mL) under simulated gut conditions (acidic and bile juices), and higher shelf life (> 55 days). The particle morphology and thermal properties were also desirable in comparison to the commercial control sample. Thus, the developed synbiotic legume-based beverage powder can be used as a novel dairy alternative and vegan product in the functional food industry by serving as a ready-to-reconstitute instant mix and a dairy alternative with added health benefits.