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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.

In Mozambique, 80% of the population directly depends on agriculture as a source of food and income. However, some of the most produced food crops, such as maize, rice and peanuts, are easily contaminated by fungi and mycotoxins. The naturally high prevalence of mycotoxins can be aggravated by the high vulnerability and lack of knowledge of the farmers. The aims of this study were to assess the knowledge and perceptions of small-size and medium-size farmers in the provinces of Inhambane and Gaza, southern Mozambique, regarding awareness of fungi and mycotoxin contamination of food crops, losses of production and income, and the causes and consequences of this contamination.MethodsA survey was conducted with 180 farmers in the two provinces. A multiple linear regression model was used to correlate the level of knowledge with the sociodemographic characteristics of the studied population.ResultsThe results showed that 97.8% of the farmers have an insufficient level of knowledge about fungi and mycotoxins contamination of food crops. While 17.8% showed sufficient or good knowledge of the conditions that promote fungal contamination, only 3.9% knew what measures to apply to mitigate their occurrence. The level of knowledge was lower for the Inhambane farmers.DiscussionAccording to the estimated model, province, gender, age (>45years old), primary and secondary (1st cycle) education, another source of income other than agriculture and experience as a farmer (>10years) are statistically significant predictors of the level of knowledge of the Mozambican farmers analyzed. These findings highlight the urgent need of tailored interventions to promote good agricultural and storage practices that allow the mitigation of mycotoxin contamination of food.

This article presents the main problems associated with cereal harvesting in sloping areas. The presented innovative aerodynamic system supporting the separating unit of combine harvester can be one of the ways to counteract the negative effects of harvesting machines work on slopes. The Monte Carlo numerical method, presented in this article, was applied in the optimization of an aerodynamic sieve separation process on an inclined terrain. The given variables are the transverse slope of separator α (of the sieve), longitudinal slope β and the output of the main and side fans. The Monte Carlo method makes it possible to determine an optimized set of parameters ( α  = 10°, β  = 2.8°, δ  = 9°), the output of the main fan (0.67 m 3  s −1 ) and the output of the side fan (1.86 m 3  s −1 ), allowing to obtain the best indicator values of 2.1% grain loss and 97.5% grain purity.

Infestation resistance of hermetic plastic (HB) bags and non-hermetic polypropylene (PP) miniature bags for grain storage was studied against (Fabricius) (Coleoptera: Bostrichidae) under conditions simulating both external and internal infestation. Results showed that successfully penetrated PP bags of 0.02–0.05 mm thickness but failed to perforate HB bags with 0.07 mm thickness. Externally released caused grain weight loss in penetrated PP bags, while surrounding HB bags experienced 100 % mortality. When were released internally, HB bags again caused the highest mortality (97 %) and the least grain weight loss (0.57 %), whereas PP bags caused significantly lower mortality and greater grain damage (1.13–1.32 %). Despite the superior performance of HB bags to protect grains against , overall results indicated that internal infestation caused lower mortality and greater grain losses than external infestation. Phosphine fumigation for internal infestation of these bags showed mortality of 89–94 % in PP bags and 98.67 % in HB bags. However, high mortality in HB bags even without fumigation indicated the inherent contribution of hermeticity to pest suppression. To simulate long-term field storage, bags were artificially damaged with two holes per bag. Fumigation of damaged bags showed 89–100 % mortality of in PP bags and 100 % in HB bags. In the corresponding non-fumigated control treatment, mortality in damaged HB bags was only 14 % and 2–5 % in PP bags. These results highlighted the importance of phosphine fumigation, which becomes essential for internal infestation in PP bags and for HB bags when their hermeticity is compromised.

This article aims to improve the real-time monitoring accuracy of the loss rate for grain combine harvesters by optimizing the sensor-sensitive plate structure, thereby addressing the problem of low detection efficiency in existing equipment. Based on Kirchhoff’s thin plate theory, COMSOL 6.0 software was utilized to conduct modal analysis and single-grain impact tests on rectangular and circular sensing plates fabricated from three materials: stainless steel, aluminum alloy, and cupronickel. The circular stainless steel sensing plate was identified as the optimal structure, whose natural frequency and sensitivity significantly outperform those of traditional rectangular plates. By integrating a signal processing strategy based on FFT (Fast Fourier Transform) spectrum analysis (band-pass filtering: 1.0~3.0 kHz, voltage threshold: 3.5 V) and a high-level duration counting algorithm, the system effectively distinguishes between grains and impurities and resolves the counting errors caused by multi-grain impacts and secondary rebounds. Field experiments demonstrate that the developed sensor exhibits strong anti-interference ability and high measurement accuracy, providing reliable technical support for reducing harvesting losses.

Threshing is the most important function of grain harvester. Grain loss and damage in harvesting are significantly related to threshing theory and technology. There are four kinds of threshing principles including impact, rubbing, combing and grinding. Four types of contact models between grain and threshing components have been constructed correspondently. Grain damage can be regarded as a function of peripheral velocity and contact pattern of impacting. Grain loss can be regarded as a function of contact pattern of rasp bars. Grain loss coming from cleaning and separation in the subsequent process of combing threshing was significantly decreased. Tangential and axial threshing technologies have been applied in grain threshing system widely. It showed that in the combined application, tangential rolls are used to accelerate grain flow, and axial rolls are used to increase threshing quality especially lower loss and damage. Conical concave may take the place of the traditional cylindrical one. With the development of sensor technology and communication technology, intelligent harvesting robot and automatic threshing system will be integrated together to improve grain quality and operation comfort.

Nearly, a quarter of the world's population does not have enough food for normal living and nearly 1 billion people become hungry every year. One of the reasons for undernourishment and hunger is drought, which reduces agricultural production leading to food insecurity situation. In half of the years of the twenty-first century, drought was the main cause of shortage in world grain production compared to its consumption, creating problem with food security. In November 2017, a new generation of NOAA operational satellite, JPSS-1, with VIIRS instrument on board was launched. Regarding land cover monitoring, the system was designed to advance drought detection, and improve prediction of grain loss using the highest resolution vegetation health (VH) method. The VIIRS-based VH will detect drought early, monitor accurately at 0.5 km 2 resolution, provide drought intensity, duration and predict agricultural loss 2 months ahead of crop harvest. Such early estimates will predict food security situation. Examples in this article prove high accuracy of vegetation health assessment, drought-triggered crop stress and the resulting grain production loss. These applications provide 2-4 months of advanced predictions of global food insecurity and early assessments of food assistance for the countries in need.

The determination of equilibrium moisture content, associated with measuring the respiration of the grain mass in real time, is a possible indicator for the indirect prediction of the quality of grains stored in bag silos, ensuring an adequate storage time. Thus, with the aid of an Internet of Things prototype, multiple linear regression models, and artificial neural networks, the present study is aimed at predicting the quality of corn grain stored in a silo bag over time based on real-time monitoring of the equilibrium moisture content and the concentration of carbon dioxide (CO 2 ). For this, an IoT prototype is indexed to monitor the temperature and relative humidity of the air, as well as determine the equilibrium moisture content and the concentration of CO 2 . Monitoring the temperature and relative humidity of the intergranular air and obtaining the equilibrium moisture content of the grains in real time allows for an indication of the storage conditions of the grains in silo bags, as well as, possible deterioration risks. However, the measurement of CO 2 in real time makes it possible to predict the levels of deterioration and the reduction in the quality of the grains during storage. The hermeticity of the silo bag was insufficient to preserve the quality of the stored grains because of the variation in intergranular abiotic factors and changes in grain metabolism. Thus, a combination of equilibrium moisture content and an evaluation of CO 2 allowed a greater assertive effect in predicting the grain quality and estimating a safe storage time. Graphical Abstract

Combine harvesters are evolving from machines equipped with isolated monitoring devices into distributed sensing platforms for process supervision, machine diagnosis, and adaptive control. This review summarizes representative research on six major sensing tasks in combine harvesters: grain loss, grain breakage, cleaning load, feed rate, grain-bin state, and grain quality. The reviewed studies are compared within a unified engineering framework that considers sensing target, installation position, signal path, disturbance source, calibration transferability, field robustness, and control relevance. Rather than evaluating sensors only as individual devices, this review emphasizes the coupled design of transducers, structural anti-interference measures, sampling paths, signal processing, and field-oriented validation under vibration-dominated and dust-laden harvesting conditions. The analysis shows that loss-rate and feed-rate sensing are currently the most mature and control-relevant categories, whereas breakage-rate, grain-bin, and integrated quality sensing remain constrained by representative sampling, disturbance resistance, and cross-condition generalization. Future progress will depend on multi-sensor fusion, realistic benchmark protocols, crop-aware calibration transfer, and tighter integration among onboard sensing, machine control, and digital harvesting systems. By clarifying the engineering value of these sensing routes, the review also supports loss reduction, quality preservation, labor-saving operation, and more reliable adaptive control in commercial grain harvesting.

China has the world's largest planting area of paddy rice, but large quantities of paddy rice fall to the ground and are lost during harvesting with a combine harvester. Reducing grain loss is an effective way to increase production and revenue. In this study, a monitoring system was developed to monitor the grain loss of the paddy rice and this approach was tested on the test bench for verifying the precision. The development of the monitoring system for grain loss included two stages: the first stage was to collect impact signals using a piezoelectric film, extract the four features of Root Mean Square, Peak number, Frequency and Amplitude (fundamental component), and identify the kernel impact signals using the J48 (C4.5) Decision Tree algorithm. In the second stage, the precision of the monitoring system was tested for the paddy rice at three different moisture contents (10.4%, 19.6%, and 30.4%) and five different grain/impurity ratios (1/0.5, 1/1, 1/1.5, 1/2, and 1/2.5). According to the results, the highest monitoring accuracy was 99.3% (moisture content 30.8% and grain/impurity ratio 1/2.5), the average accuracy of the monitoring tests was 92.6%, and monitoring of grain/impurity ratios between 1/1 and 1/1.5 (>95.4%) had higher accuracy than monitoring the other grain/impurity ratios. Monitoring accuracy decreased as impurities increased. The lowest accuracy for grain loss monitoring was obtained when the grain/impurity ratio was 1/2.5, with monitoring accuracies of 88.2%, 75.7% and 78.8% at moisture contents of 10.4%, 19.6% and 30.4%.