Grain storage loss is a major contributor to post-harvest losses and is one of the main causes of food insecurity for smallholder farmers in developing countries. Thus, the objective of this review is to assess the conventional and emerging grain storage practices for smallholder farmers in developing countries and highlight their most promising features and drawbacks. Smallholder farmers in developing countries use conventional grain storage structures and handling systems such as woven bags or cribs to store grain. However, they are ineffective against mold and insects already present in the grain before storage. Different chemicals are also mixed with grain to improve grain storability. Hermetic storage systems are effective alternatives for grain storage as they have minimal storage losses without using any chemicals. However, hermetic bags are prone to damage and hermetic metal silos are cost-prohibitive to most smallholder farmers in developing countries. Thus, an ideal grain storage system for smallholder farmers should be hermetically sealable, mechanically durable, and cost-effective compared to the conventional storage options. Such a storage system will help reduce grain storage losses, maintain grain quality and contribute to reducing food insecurity for smallholder farmers in developing countries.

Lactic acid is an important chemical with numerous commercial applications that can be fermentatively produced from biological feedstocks. Producing lactic acid from corn grain could complement the use of already existing infrastructure for corn grain-based ethanol production with a higher value product. The objective of this study was to evaluate the techno-economic feasibility of producing 100,000 metric tons (t) of lactic acid annually from corn grain in a biorefinery. The study estimated the resources (equipment, raw materials, energy, and labor) requirements and costs to produce lactic acid from bacteria, fungi and yeast-based fermentation pathways. Lactic acid production costs were $1181, $1251 and $844, for bacteria, fungi and yeast, respectively. Genetically engineered yeast strains capable of producing lactic acid at low pH support significantly cheaper processes because they do not require simultaneous neutralization and recovery of lactic acid, resulting in lower requirements for chemical, equipment, and utilities. Lactic acid production costs were highly sensitive to sugar-to-lactic-acid conversion rates, grain price, plant size, annual operation hours, and potential use of gypsum. Improvements in process efficiencies and lower equipment and chemical costs would further reduce the cost of lactic acid production from corn grain.

This study reports the results of an evaluation of the techno-economic feasibility of a biorefinery with an annual lactic acid production capacity of 100,000 metric tons using lignocellulosic biomass. Corn stover and miscanthus were considered as model feedstocks, and three different fermentation pathways involving bacteria, fungi, and yeast were compared with respect to their ability to convert biomass feedstocks to lactic acid. Equipment, raw materials, utilities and labor requirements, and lactic acid production costs were estimated. The minimum selling price (at a 10% internal rate of return) per metric ton of lactic acid produced from different feedstocks for lactic acid bacteria, fungi, and yeast-based pathways were in the range of USD 1243–1390, USD 1250–1392, and USD 993–1123, respectively, with lower costs for miscanthus. Lactic acid production using genetically engineered yeast strains can eliminate the need for the simultaneous neutralization and recovery of lactic acid, resulting in lower equipment, chemical, and utility requirements and lower lactic acid production costs. Lactic acid production costs were highly sensitive to the conversion rates of sugars into lactic acid, feedstock cost, production plant size, operation hours, and acid hydrolysis reactor costs. Improvements in process conditions and efficiencies and lower costs of equipment and consumables are necessary to utilize lignocellulosic biomass for lactic acid production at lower costs while remaining cost-competitive with respect to first-generation and petroleum-based feedstocks.

Accurate stockpile volume estimation is essential for industries that manage bulk materials across various stages of production. Conventional ground-based methods such as walking wheels, total stations, Global Navigation Satellite Systems (GNSSs), and Terrestrial Laser Scanners (TLSs) have been widely used, but often involve significant safety risks, particularly when accessing hard-to-reach or hazardous areas. Unmanned Aerial Systems (UASs) provide a safer and more efficient alternative for surveying irregularly shaped stockpiles. This study evaluates UAS-based methods for estimating the volume of coal stockpiles at a storage facility near Cadiz, Ohio. Two sensor platforms were deployed: a Freefly Alta X quadcopter equipped with a Real-Time Kinematic (RTK) Light Detection and Ranging (LiDAR, active sensor) and a WingtraOne UAS with Post-Processed Kinematic (PPK) multispectral imaging (optical, passive sensor). Three approaches were compared: (1) LiDAR; (2) Structure-from-Motion (SfM) photogrammetry with a Digital Surface Model (DSM) and Digital Terrain Model (DTM) (SfM–DTM); and (3) an SfM-derived DSM combined with a kriging-interpolated DTM (SfM–intDTM). An automated boundary detection workflow was developed, integrating slope thresholding, Near-Infrared (NIR) spectral filtering, and Canny edge detection. Volume estimates from SfM–DTM and SfM–intDTM closely matched LiDAR-based reference estimates, with Root Mean Square Error (RMSE) values of 147.51 m³ and 146.18 m³, respectively. The SfM–intDTM approach achieved a Mean Absolute Percentage Error (MAPE) of ~2%, indicating strong agreement with LiDAR and improved accuracy compared to prior studies. A sensitivity analysis further highlighted the role of spatial resolution in volume estimation. While RMSE values remained consistent (141–162 m³) and the MAPE below 2.5% for resolutions between 0.06 m and 5 m, accuracy declined at coarser resolutions, with the MAPE rising to 11.76% at 10 m. This emphasizes the need to balance the resolution with the study objectives, geographic extent, and computational costs when selecting elevation data for volume estimation. Overall, UAS-based SfM photogrammetry combined with interpolated DTMs and automated boundary extraction offers a scalable, cost-effective, and accurate approach for stockpile volume estimation. The methodology is well-suited for both the high-precision monitoring of individual stockpiles and broader regional-scale assessments and can be readily adapted to other domains such as quarrying, agricultural storage, and forestry operations.

Excess phosphorus (P) in agricultural runoff can cause eutrophication in nearby waterbodies. Therefore, it is crucial to remove P from agricultural runoff before it reaches aquatic environments. This study evaluated the P adsorption potential of adsorbents prepared via co-hydrothermal carbonization of multiple agricultural wastes, including dairy manure (DM), corn stover (CS), and eggshell (ES), followed by thermal activation. The performance of the prepared adsorbents was investigated by both batch and column experiments. The activated hydrochar (AHC) with a DM/CS/ES ratio of 1:0:1 showed the highest P adsorption capacity of 209 ± 0.6 and 65.97 ± 9.04 mg/g in batch and column experiments, respectively. The P adsorption mechanism was well described by the Langmuir isotherm model (R² > 0.8802) and the pseudo-second-order kinetics model (R² > 0.8989). The adsorbent indicated the longest breakthrough and exhaust time of 210 and 540 min, respectively, with an adsorbent dose of 1 g and an initial concentration of 25 mg P/L. The breakthrough curve was well described by the Thomas model (R² > 0.971). Thus, this study indicates that AHC with eggshell has high potential for use as an adsorbent for P removal from agricultural runoff.