The grain storage ecosystem comprises of biotic and abiotic factors that interact during grain storage, and their interaction affects the quality of the stored grains over time. The understanding and management of the complex interaction of the biotic and abiotic factors in the stored grain ecosystem is crucial to decision-making and in the development of management strategies for grain farmers and elevators. Mathematical modelling has emerged as an essential approach in tackling complex systems such as the stored grain ecosystem. This review explores the application of mathematical modelling in the grain storage ecosystem and synthesizes the existing literature, highlighting the various mathematical models and approaches to solving issues relating to the grain storage ecosystem. The review will be helpful to researchers and stored grain experts in the grain industry on the various mathematical modelling approaches and equations that can be employed to solve problems associated with grain storage in order to better manage the quality of stored grain.

The aim of this review paper is to document the role of post-harvest rice cooling in ensuring the safe storage of rice, given the ongoing increase in rice production. The United States exports substantial quantities of rice, with milled and rough rice being the primary exports. The industry has experienced growth, propelled by rising demand, a diverse population, and international trade. Effective storage of harvested rice is essential for year-round utilization, and the USA utilizes both on-farm and off-farm in-bin storage methods equipped with features like moisture control, pest management, and temperature regulation. The adoption of rice cooling technology for storage emerges as a solution to accelerate drying, prolong shelf life, and improve overall quality. Despite challenges such as upfront costs and energy requirements, cooling technology offers benefits for both short-term and long-term storage. Integrating cooling models into mathematical simulations becomes crucial for optimizing storage conditions. Research opportunities in post-harvest rice cooling focus on energy-efficient technologies, smart sensors, modern storage structures, microbial control methods, and economic evaluations. Future trends encompass automation, intelligent monitoring, climate-controlled storage, sustainability measures, and technological integration to enhance the efficiency and security of rice storage facilities in the USA.

The process of preliminary cleaning is a determining factor affecting the standard qualities of the seeds. The grain mass that undergoes primary processing contains significant amounts of impurities, the amount of which is strictly regulated by standards. Sieves with rectangular and round openings are the most widely used for separating maize seeds. In this study, the feasibility and efficiency of using sieves with openings in the Cassini oval shape were proposed and substantiated. Three factors subject to variation during the experiments were selected, each having a crucial influence on the process parameters: rotational speed (n, rpm), specific material feed (Q, kg), and angle of sieve inclination (α, deg.). A regression equation was developed, and the response surfaces of the dependencies of defining characteristics of the process of separation of maize seeds on sieves with openings in the Cassini oval shape were compiled and analyzed. The study showed that the rotational speed has a less significant influence on the mass of the undersize of sieved maize than the inclination angle and feeding rate. A maximum grain passage (2.9 kg) into the openings in the Cassini oval shape is obtained at a rotational speed of 290.35 min^-1 and a grain feed rate of 3.06 kg min^-1.

Improperly balanced diets not only impact the quality of animal production but also the profits of a livestock operation. Typically, the nutrient and chemical content of feed ingredients and forages are determined using well-established wet chemistry tests. However, these tests can be expensive and time-consuming. Moreover, the increasing use of various by-products which are known to have large variations in chemical and nutrient content warrants a real-time on-site feed and forage testing system. Near infrared (NIR) spectroscopy systems are quick and effective on-site testing tools. While NIR systems are being adopted for on-farm or at feed mill ingredient and forage testing, little is known about the economic impacts of such an investment for a livestock or feed mill operator. This study developed a baseline model and an Excel based spreadsheet application for performing Return on Investment (ROI) analysis to determine the feasibility of using an on-farm or at feed mill NIR testing system. ROI was calculated based on the nutrient cost saved or spent determined from the difference of estimated nutrient content and actual calculated value. The findings from this study will promote low-cost alternatives for onfarm or at feed mill ingredient testing, positively impacting quality of animal products and minimizing costs.

The fisheries and aquaculture industries are vital components of global food production, yet they also contribute to release of microplastics into marine environments, posing risks to ecosystem health and seafood safety. Among the contributing factors, the erosion of feeding pipes during the pneumatic conveyance of fish feed pellets stands out as a significant source of microplastic pollution. This study focuses on optimizing feed pellet conveying systems in fish farms to minimize microplastic emissions while maximizing pipeline lifespan and pellet integrity. Using high-density polyethylene (HDPE) pipes commonly found in aquaculture facilities, the impact of air velocity and pipeline configuration on pipe wall erosion and pellet breakage was investigated. Through pneumatic conveying tests, the effects of varying air flow rates and bend radii were assessed on pipeline wear and feed pellet integrity. The findings of the study underscored the importance of optimizing operating parameters to bring a balance between preventing pipe blockages and minimizing abrasive impacts on pellets and pipeline surfaces. Furthermore, a simulationbased approach to optimize feeding system performance is presented, integrating the experimental results into a computational model. This model allows for the evaluation of different operating conditions and pipeline configurations, offering insights into costeffective strategies for reducing microplastic emissions while maintaining efficient feed delivery to fish populations. Ultimately, this research provided practical recommendations and best practices for the aquaculture industry to mitigate microplastic pollution from feeding pipes. By optimizing feed pellet conveying systems, environmental sustainability can be enhanced, seafood quality be preserved, and bolster consumer confidence in aquaculture products.

Kulfi was frozen from concentrated milk as well as from reconstituted dry mix with solids content of 60%. The convective heat transfer coefficients during freezing of kulfi by deep freeze and cryogenic methods were determined using one-dimensional transient heat conduction equation. The heat transfer coefficient for cryogenic freezing of kulfi from milk and dry mix concentrates was 210.57 W m^-2K^-1 and 216.84 W m^-2K^-1, respectively when compared to 8.33 W m^-2K^-1 for conventional deep-frozen kulfi. Freezing was achieved in 267 min in deep freeze method, while it reduced to just 185-190 s under cryogenic conditions. The freezing time was predicted using empirical equations, and the prediction accuracies were compared. Cryogenic freezing was nearly 87.66 times faster than deep freezing, and Pham’s model best-predicted the freezing time. Organoleptic evaluation using fuzzy-logic revealed that the order of ranking of quality attributes of kulfi was body and texture (highly important) > melting characteristics (highly important) > flavour and taste (highly important) > colour and appearance (important), and cryogenically frozen kulfi was statistically (p<0.05) superior to conventionally frozen kulfi.

Traditional methods of extracting oil with organic solvents raise issues related to health, safety, and the environment. Microwave-assisted enzymatic green solvent extraction (MAEGSE) technology is environment friendly because it involves less hazardous chemical synthesis, utilizes renewable feedstock, and decreases the chemical load and emissions produced by organic solvents. The solvents methanol, ethanol, and various cell wall degrading enzymes such as hemicellulose, viscozyme L, pectinase, xylanase, and cellulase were used in this study. The MAEGSE process of sesame oil was conducted, and the results indicated that, unlike the controlled group, no enzymes were used during the process. Among all the combinations a higher oil extraction efficiency was obtained with combination of pectinase and ethanol (37.27%) followed by the xylanase with ethanol (36.75%) from sesame seed without compromising the quality of oil. Among the enzymes tested, pectinase resulted in the highest oil extraction efficiency, followed by xylanase. Use of pectinase improved the oil extraction efficiency in both ethanol and methanol mediums. The outcomes suggested that the application of pectinase enzymes plays a significant role in increasing the oil yield in comparison with the control without compromising quality of oil. Oil extracted without the use of enzyme (control) had a lower free fatty acid (FFA) concentration than the oils extracted with MAEGSE. Even though the specific gravity (SG) and refractive index (RI) of extracted oils were not significantly different in the solvents, the saponification value (SV), peroxide value (PV), iodine value (IV), and free fatty acid (FFA) were found to have minor differences among the extraction techniques.

Agriculture feedstock materials have low bulk density and are difficult to handle and transport. Compaction can enhance the agricultural feedstock density and could be an effective solution for handling problems. To develop a better compaction process, mathematical modelling can help understand the compaction mechanism and can help predict the mechanical behaviour of feedstock materials. This paper presents a review on the energy consumption, applied pressure, as well as rheological models to predict their compaction behaviour and thus help improve compacts’ mechanical strength and reduce densification costs. In summary, energy requirement for densification of biomass depends primarily upon the pressure applied, holding on time and properties of the material. From the published literature, it could be found that the Cooper-Eaton and the Kawakita-Ludde models that considers particle rearrangement and deformation mechanism can fit pressure and density of feedstock materials during compaction. The parameters in the rheological models were correlated to the properties of the feedstock materials and can be used for optimization of machine and operational parameters.

The imbalance in nutrient release from conventional fertilizers and plant nutrient uptake leads to a surplus accumulation of nutrients in the soil. A key approach to tackle this issue involves the engineering of nano-enabled fertilizers for the controlled release of nutrients to crops. In this context, it is important to understand the strategies for designing and utilizing nano-enabled fertilizers that can effectively regulate nutrient release and enhance nutrient use efficiency (NUE). This review focuses on nano-structured materials that serve as nutrient carriers: nano-clays, hydroxyapatite (HA) nanoparticles, mesoporous silica, carbon-based nanomaterials, polymeric nanoparticles, and other nanomaterials. In addition, the nutrient release mechanisms in controlled release fertilizers (CRFs)/slow-release fertilizers (SRFs) are discussed. The discussion and perspectives presented emphasizes the need for standardized and comprehensive fertilizer evaluation systems, design of multifunctional nanomaterials, and the creation of stimuli-responsive nanocarriers to improve NUE.