Quality of soybeans stored under controlled temperature and relative humidity conditions with heat pump technology: A comparison with conventional bag storage

Qualidade de grãos de soja armazenados sob condições controladas de temperatura e umidade relativa com tecnologia de bomba de calor: Uma comparação com o armazenamento convencional em bag

ABSTRACT

Soybeans are among the most important agricultural commodities in the global scenario, with Brazil standing out in recent years. Storage is a critical stage in the agricultural production chain. During this phase, the product is exposed to external agents and pests for a longer period. Damage during storage, caused by the lack of adequate techniques for temperature and humidity control, results in significant quantitative and qualitative losses. The adoption of storage practices that regulate these parameters is essential for loss reduction. In this context, the objective of this investigation was to compare the quality parameters of soybeans (lipid acidity, physiological quality, and sanitary condition) stored in silos with temperature/humidity control via a heat pump-based automated psychrometric system versus conventional bag storage. All evaluated parameters were better preserved in soybeans stored in the cooled silo. Soybeans stored in the cooled silo exhibited 15% lower lipid acidity and 40% higher germination rates compared to bag storage after8 months. A significant inverse correlation was observed between germination rates and fungal presence, with contamination levels in the bag storage consistently higher than those in the silo throughout the entire experiment. The heat pump is a sustainable solution that contributes as a practical subsidy for the stability of grains stored in tropical regions.

Index terms:
Cooling; Glycine max L.; psychrometric conditions; incidence of fungi

RESUMO

A soja está entre as commodities agrícolas mais importantes no cenário global, com o Brasil se destacando nos últimos anos. O armazenamento é uma etapa crítica na cadeia de produção agrícola. Durante essa fase, o produto é exposto a agentes externos e pragas por um período mais longo. Os danos durante o armazenamento, causados pela falta de técnicas adequadas de controle de temperatura e umidade, resultam em perdas quantitativas e qualitativas significativas. A adoção de práticas de armazenamento que regulem esses parâmetros é essencial para a redução de prejuízos. Nesse contexto, o objetivo desta investigação foi comparar os parâmetros de qualidade da soja (acidez lipídica, qualidade fisiológica e condição sanitária) armazenada em silos com controle de temperatura/umidade por meio de um sistema psicrométrico automatizado baseado em bomba de calor versus o armazenamento convencional em bags. Todos os parâmetros avaliados foram melhor preservados na soja armazenada no silo resfriado. A soja armazenada no silo resfriado apresentou 15% menos acidez lipídica e 40% mais germinação em comparação ao armazenamento em sacos após 8 meses. Houve correlação significativa e inversamente proporcional entre os percentuais de germinação e a presença de fungos, sendo que as médias de contaminação do bag mantiveram-se superiores às do silo durante todo o experimento. A bomba de calor é uma solução sustentável que contribui como subsídio prático para a estabilidade de grãos armazenados em regiões tropicais.

Termos para indexação:
Resfriamento; Glycine max L.; condições psicrométricas; incidência de fungos

Introduction

Soybeans (Glycine max L.) are among the most relevant agricultural commodities in the world, used for both human and animal consumption, they represent the main cultivated oilseed crop (Ayala et al., 2025; Debiasi et al., 2025). According to (Companhia Nacional de Abastecimento - Conab, 2025), Brazil reached the highest production level in history during the 2022/2023 season, amounting to 154.6 million tons. Despite a 4.5% decrease in the 2023/2024 season, productivity achieved the second-highest value in seven years.

Grain storage is an excellent alternative to support the logistics of food production and marketing, helping to maintain quality. However, according to Pasqualone (2025), it is one of the most critical stages in the production chain, where susceptibility to damage is quite high. Post-harvest quality loss in grains mainly occurs due to pest infestations and fungal degradation (Ouaarous et al., 2025).

These challenges are not exclusive to Brazil but are also documented in other major soybean-producing countries located in tropical and subtropical regions, including Argentina, Paraguay, India, and parts of Southeast Asia. In such climates, grain deterioration is intensified by changes in respiration rates, microbial growth, and lipid oxidation (Oyagbohun, 2025), reinforcing the global demand for more energy-efficient storage technologies. According to the FAO (Food and Agriculture Organization - FAO, 2022), about one-third of the food produced is wasted during the post-harvest stages.

Zhang et al. (2021) classify soybean technological quality into quantitative aspects-related to moisture content and, especially, protein and lipid content, which are important for producing derivatives (oil and meal)-and qualitative aspects-related to lipid and protein fractions (globulins, glutelins, albumins, and prolamins), which are important for characterization and processing line destination. Grain quality is a highly relevant parameter for marketing and processing, affecting the product’s value (Freitas et al., 2024; Vicentin et al., 2024; Lopes 2023; Xiao et al., 2025).

Another indicator of quality is physiological potential, which consists of a combination of physical, genetic, and sanitary attributes, all of which are easily influenced by events occurring throughout the production chain, from the beginning to the end of the storage period (Reis et al., 2023; Shafat et al., 2025). According to Rakhnamokhon et al. (2021), grains continue to respire after harvest, and the rate of deterioration of the grain mass can be measured by the degree of respiratory intensity. Labrot-Rhodes, Campo and Poujaud (2025) point out that the temperature rise in the grain mass during the storage period is undoubtedly the result of the respiratory process.

During storage stages, grain quality can also be affected by external agents such as fungi and insect pests. The most commonly found fungi in soybeans during storage are Penicillium and Aspergillus flavus (Maciel et al., 2025). Insect pests, especially Lasioderma serricorne, Oryzaephilus surinamensis, Cryptolestes ferrugineus, and moths such as Ephestia kuehniella and E. elutella, are largely responsible for physical deterioration (Kadyrov et al., 2024; Ranabhat et al., 2025).

Among the external factors, those that most affect the grain mass ecosystem are the temperature and the relative humidity of the intergranular air (Leal et al., 2023). Thus, the use of low temperatures emerges as a promising technique in grain storage, inhibiting insect proliferation and contributing to the maintenance of quality (Chen et al., 2023). The rate of chemical and enzymatic reactions in the drying process decreases logarithmically with temperature (Çulluk, Demiray & Çalışkan Koç, 2025). Therefore, cooling allows the control of grain quality loss over time, preserving their characteristics and protecting them from external agents such as microorganisms and insects.

Refrigerated aeration reduces the metabolic rate of the grains and, consequently, the deterioration related to their respiration, influencing the CO₂ concentration in the storage environment (Müller et al., 2022). Under adverse climatic conditions, such as those found in tropical and subtropical climate regions, this practice is the most recommended (Mafra & Christian, 2024).

Dürks et al. (2019) evaluated the quality of soybean grains under two aeration conditions-one conventional and the other with artificial cooling-and found that the grains subjected to cooling exhibited less pronounced qualitative losses compared to soybean grains maintained with conventional aeration. Zhao et al. (2024) concluded that grain storage under high temperature and humidity promotes changes in metabolic processes, resulting in quality degradation.

Grain coolers have been used to maintain appropriate product temperatures during storage to minimize biological activity and microorganism growth (Sousa et al., 2023). However, these devices are limited by their inability to control the relative humidity of the air, which is a critical factor in preventing pathogen-related deterioration (Liang, Chen & Orooji, 2022; Liu et al., 2024).

Heat pumps present themselves as an interesting option. These are highly efficient and environmentally friendly devices, as they use high-quality energy, and they offer a significant advantage: the ability to control both temperature and relative humidity levels with various operational modes (Jordan et al., 2020; Liu et al., 2025; Salazar-Hincapié et al., 2020).

In this context, the present study aimed to evaluate and compare quality indicators of soybean grains stored in a silo under controlled temperature and relative humidity conditions, using heat pump technology in conventional storage and in bags. Specifically, the study sought to quantify changes in lipid acidity during storage, monitored variations in seed physiological quality through the germination rate, identified the impact of psychrometric control technology on the incidence of phytopathogenic fungi, analyzed the stability of lipid, protein, and moisture contents on a dry basis, and verified the correlation between physiological deterioration and the presence of microorganisms.

This experimental approach aimed to demonstrate that the heat pump is a viable and sustainable alternative that promotes greater biochemical and sanitary stability of grains during prolonged storage, especially for regions with tropical and subtropical climates, such as Brazil.

Material and Methods

Experimental area location

The research was conducted on a rural property located in the municipality of Lindoeste, state of Paraná, Brazil, at 25° 17’ 00.8” South Latitude and 53° 32’ 29.7” West Longitude, with an orthometric altitude of 590 m (Figure 1). The climate is classified as Cfa (humid temperate with hot summer) according to the Köppen climate classification (Aparecido et al., 2016).

Figure 1:
Geographical location of the experimental area. Source: The Authors.

Experiment setup and conduction

The soybeans, harvested on February 15, 2024, with a moisture content of 13%, were stored for a period of 26 days in a silo without temperature control after undergoing a pre-cleaning stage. On March 12, 2024, the grain was allocated for the experiment: 700 kg for bag storage under ambient conditions and 3,000 kg for silo storage (full capacity) with artificial cooling and controlled temperature. Figure 2 presents the flowchart of the stages with the respective dates.

Figure 2:
Representation of the experimental period stages. Source: The Authors.

The silo (Figure 3) was connected to a prototype cooler based on heat pump technology, equipped with a system for controlling the psychrometric conditions of the air, named SIARCOMPAG-Autonomous System for Cooling and Psychrometric Control of Grain Storage Conditions (Freitas, V. et al., 2024).

Figure 3:
Silo for storage (A) connected to the cooling prototype (B) and bag storage (C). Source: The Authors.

SIARCOMPAG can operate in fully automatic, semi-automatic, or manual mode, depending on the programming of the functions in the PLC (Programmable Logic Controller) through the human-machine interface (HMI) (Figure 4). In automatic mode, the parameters (product, temperature, and moisture content on a wet basis) are entered into the HMI (Figure 4B), and the control of operating conditions is carried out entirely by the PLC through moisture equilibrium equations. The equipment includes equations for the following products: soybean, corn, wheat, rice, beans, and coffee.

Figure 4:
HMI screens: A) operation mode selection; B) parameter selection in automatic mode; C) compressor speed selection in manual mode. Source: The Authors.

Aiming to optimize environmental data collection, as recommended by Santana et al. (2024) and Santos et al. (2024), this study adopted methodological strategies that propose the use of remote sensors for real-time data collection, minimizing operational uncertainties.

To monitor the temperatures inside the silo, four RHT-type sensors (RHT1, RHT2, RHT3, and RHT4) and eight PT100 sensors (T5, T6, T7, T8, T9, T10, T11, and T12) were used (Figure 5). Temperature monitoring in the bag storage was performed using nine PT100 sensors (Figure 6). All sensors were previously calibrated with INMETRO certification and connected to Novus brand Field Logger acquisition modules, which were linked to a computer, enabling continuous data recording and monitoring.

Figure 5:
Layout of the temperature sensors placement installed in the silo. Source: The Authors.

Figure 6:
Layout of the temperature sensors placement installed in the bag. Source: The Authors.

Due to technical issues in the field, it was not possible to establish communication between the silo data acquisition system and the SIARCOMPAG PLC. Thus, the equipment had to be manually turned on and off. The equipment was activated when the temperature inside the silo reached 18°C and turned off when it dropped to 13°C. For this purpose, a digital temperature indicator was installed in the silo as schematized in Figure 5, where the sensor (Tsilo) was positioned at the center of the grain mass.

Despite the need for manual activation of SIARCOMPAG, thermal control performance was maintained within the established range (13 °C to 18 °C), with temperature variations of less than ±1 °C. This fluctuation is consistent with the expected behavior for systems based on intermittent control by thermal regulation, as observed by Hordov et al. (2023), who reported thermal stability in storage environments with cyclic cooler operation. Thus, manual operation did not compromise the system’s efficiency nor the results compared to conventional bag storage.

SIARCOMPAG was then programmed to cool soybeans, with an operating temperature of 13 °C and a moisture content of 13% on a wet basis. Due to sensor reading fluctuations and the PLC response time for adjusting the operating conditions, there is a variation of ±1°C in temperature and ±1% in moisture content.

The storage period lasted approximately 8 months, ending on October 12, 2024. During this period, with the aid of a grain probe, soybean samples were collected from the silo and the bag at 60, 136, and 244 days of storage, referred to in the analysis as collections 1, 2, and 3. In both the silo and the bag, samples were taken from five points. In the silo, sampling was performed from the top, through the hatch access. The samples, weighing 800 grams, were packed on-site in sealed, waterproof plastic bags to prevent moisture exchange with the air.

In the laboratory, the samples were divided into two equal parts: one designated for physiological and sanitary analyses (germination and fungi) and the other for chemical composition analyses (free fatty acid content, total protein, lipids, and moisture).

Laboratory analysis of the samples

The free fatty acid content was determined using the flour method, as described in AOAC 939.05 (Association of Official Agricultural Chemists, AOAC, 2010). The lipid fraction was extracted from the sample using an organic solvent (ether), followed by titration of the extract with a standardized alcoholic solution of potassium hydroxide (KOH), using phenolphthalein as an indicator. The free fatty acid content was expressed as a percentage (%FFA), calculated based on the volume of KOH consumed (V), the normality of the solution (N), the reference molar mass (M), and the sample mass (m), according to Equation 1:

$$\%FFA=\frac{V\cdot N\cdot M\cdot 100}{m\cdot 1000}$$ (1)

where:

V = volume of KOH (mL),

N = normality of KOH,

M = molar mass of the reference fatty acid (g/mol), and

m = sample mass (g).

The determination of total protein, lipid, and moisture contents in the soybean samples was performed using near-infrared reflectance spectroscopy (NIRS), employing the CropScan 2000B NIR Analyzer (NIR Technology Systems). The instrument was calibrated for whole soybeans and operated according to the manufacturer’s guidelines. For each sample, five replicates were analyzed using subsamples of approximately 75 grams of clean, whole soybean grains. The samples were scanned in reflectance mode, and the spectral data obtained were processed by the device’s internal calibration models to quantify the concentrations of protein, lipids, and moisture. The results were expressed as a percentage of total mass (wet basis) and subsequently converted to a dry basis to eliminate the influence of water content, allowing for a more accurate comparison of the parameters comprising the samples.

The physiological quality of the seeds was evaluated through the paper germination test (Figure 7), following the methodology established by RAS (Brasil, 2009). Four replicates of 50 seeds each were uniformly distributed between moistened germitest paper sheets, hydrated with distilled water at a ratio of 2.5 times the dry paper mass. The paper rolls containing the seeds were placed in a germinator at a controlled temperature of 25 °C under a controlled photoperiod.

Figure 7:
Soybean samples subjected to the paper germination test. Source: The Authors.

Germination counts were performed on the fourth day (first count) and eighth day (final count), with seeds considered germinated only if both root and shoot systems were normally developed, according to RAS criteria. Results were expressed as germination percentage.

The sanitary quality of the seeds was evaluated using the Blotter Test, following established protocols for the detection of seed-borne pathogens. For each treatment, a total of 100 seeds were analyzed, distributed across eight gerboxes, with 25 seeds per gerbox. Each gerbox contained two sheets of sterilized filter paper moistened with a solution composed of sterile distilled water supplemented with 0.01% of the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D), which inhibits seed germination and facilitates fungal development. The seeds were evenly spaced on the moistened paper without overlapping and incubated under controlled conditions in a BOD (Biochemical Oxygen Demand) growth chamber at 25 °C for a period of seven days, under a 12-hour light/dark photoperiod to stimulate sporulation. After incubation, the seeds were examined for the quantification of fungal contamination (Peng et al., 2025; Ramdan et al., 2021). The results were expressed as the percentage of seeds infected.

Statistical analysis

The data were subjected to analysis of variance (ANOVA) using a split-plot design, following the methodology recommended by Santos et al. (2020) and Jesus et al. (2021), in order to ensure consistent interpretation of main effects and their interactions. For soybean temperature data, monthly means were evaluated, with storage methods (silo and bag) considered as the main treatment and the months (8 months) as the secondary treatment.

For data on free fatty acid content, total protein, lipids, moisture, germination percentage, and pathogen incidence, the storage methods (silo and bag) were considered the main treatment and the sampling times (three collections) as the secondary treatment. The analysis was performed using R software (Ferreira, Cavalcanti & Nogueira, 2014). The assumptions of data normality and homogeneity of variances were verified using the Shapiro-Wilk and Levene tests, respectively. In addition, Pearson’s linear correlation analysis was conducted between pathogen incidence and the grain germination percentage.

Results and Discussion

Free fatty acid values showed no significant variation over the storage period. However, a significant difference was observed between the storage methods. Soybeans stored in bags presented higher acidity levels compared to those stored in the silo under controlled psychrometric conditions, as shown in Tables 1 and 2.

Table 1:
F values calculated by analysis of variance (ANOVA) for the free fatty acid content (%) of soybeans stored in bag and silo at three sampling times.

Source of Variation	DF	Free fatty acid
Storage (A)	1	52.505**
Sampling (C)	2	1.34ns
A x C	2	0.09ns
CV - A (%)	4.96
CV - C (%)	10.00

• DF: Degrees of Freedom; **: significant (P ≤ 0.01) by the F test; ns: not significant; CV: Coefficient of Variation.

Table 2:
Results of the mean comparison test for the free fatty acid content (%) of soybeans stored in silo and bag at three sampling times.

Storage	Free fatty acids
Bag	28.33 a
Silo	24.67 b
Sampling
1	25.30 a
2	26.80 a
3	27.10 a

• Means followed by the same letter do not differ significantly by Tukey’s test (p ≤ 0.05).

The results in Table 2 indicate that the free fatty acid content of grains stored in bags was significantly higher than that of grains stored in silos with psychrometric control (p ≤ 0.05). This increase is associated with greater lipid oxidation by microorganisms, favored by higher temperatures and humidity levels (Ludwig et al., 2021). Ajayi-Banji et al. (2024) reported lower free fatty acid content in grains stored under cooler and drier conditions, supporting the findings of this study. Therefore, the use of systems that control temperature and humidity, such as heat pumps, proves to be effective in preserving the lipid quality of soybeans during storage.

The impact of storage conditions became apparent from the early months, with the most significant increase in acidity occurring within the first two months for both storage conditions. However, the increase in the bag was greater than in the silo, as shown in Figure 8.

Figure 8:
Distribution of free fatty acid (%) data between silo and bag according to sampling times. Source: The Authors.

According to Kumar et al. (2021), the increase in free fatty acid content results from the activity of the lipase enzyme, which is produced through the metabolic processes of microorganisms. Guo et al. (2025) emphasize that this process can be mitigated by lowering the temperature, which is explained by the reduced activity of microorganisms at lower temperatures, as observed in the experiment and illustrated in Figure 9.

Figure 9:
(A) Boxplots of the daily average temperatures of the silo and bag for each month. (B) Boxplots of the average soybean temperature values during the storage period for the treatments. Source: The Authors.

Mendonça et al. (2024) concluded that temperature is the main factor in preserving lipid acidity, based on comparisons of storage at different temperatures and moisture contents. Faroni et al. (2009) observed significant variations in free fatty acid profiles under different temperature and humidity scenarios, with the best results occurring under milder conditions (20°C and 11.2%).

Table 3 presents a summary of the analysis of variance for soybean temperature data stored in bag and silo over the eight-month sampling period. There were highly significant differences between storage methods, sampling periods, and the interaction between both factors. The variability of the experiment, indicated by the coefficient of variation (CV), can be considered low for the storage factor and moderate for the sampling factor, according to criteria proposed by Rosenman (2025).

Table 3:
F values calculated by analysis of variance (ANOVA) for soybean temperature (^oC) stored in bag and silo across eight sampling periods.

Source of variation	DF	Temperature
Storage (A)	1	597.13**
Sampling (C)	7	17.14**
A x C	7	18.09**
CV - A (%)		9.23
CV - C (%)		12.48

• DF: Degrees of Freedom; **: significant (P ≤ 0.01) by F test; CV: Coefficient of Variation.

The results of the interaction breakdown, using the mean comparison test (Tukey, P < 0.05), are presented in Table 4. Soybean temperatures were higher when stored in bags, differing significantly from storage in silos, except in July, when there was no significant difference between the storage methods. Regarding the sampling months, greater variability was observed in the temperatures of soybeans stored in bags, with more pronounced fluctuations over the storage period. In contrast, temperature stability was higher when storage was carried out in silos, where significant temperature differences were observed only between March and October.

Table 4:
Results of the mean comparison test for soybean temperature stored in silo and bag over eight sampling periods (breakdown of significant interactions).

Month	Temperature (oC)
	Bag	Silo
3	25.34 aA	15.19 bB
4	23.74 abA	16.08 abB
5	22.09 bA	16.77 abB
6	19.38 cA	16.68 abB
7	16.11 dA	15.83 abA
8	19.4 cA	16.10 abB
9	21.28 bcA	17.7 abB
10	24.76 aA	18.34 aB

• Means followed by the same lowercase letter in columns and uppercase letter in rows do not differ significantly by Tukey’s test (P < 0.05).

The results in Table 4 indicate that silo storage provides greater thermal stability, which was confirmed by Rocha et al. (2025), who pointed out that controlled temperature conditions prevent pronounced fluctuations in the physiology of stored grains. On the other hand, storage in bags, with greater thermal variability, favors deterioration, as indicated by Murmu et al. (2025), who associated temperature fluctuations with more significant qualitative losses. Therefore, continuous temperature control in silos contributes to preserving grain quality.

Figure 10 shows the boxplots of the values of total protein, lipids, and moisture content of soybeans on a dry basis according to sampling. The protein (A), lipid (B), and moisture (C) contents of soybeans on a dry basis are compared for the treatments (bag and silo) across the three sampling points.

Figure 10:
Boxplots of dry basis values of protein (A), lipids (B), and moisture (C) content (%) in soybeans for the treatments (bag and silo) in samplings 1, 2, and 3. Source: The Authors.

In Figure 10A, we observed that total protein content remained relatively stable between treatments, ranging from 47.6% to 48.5%, in agreement with Toni et al. (2024), who reported averages between 47.5% and 48.2% for grains stored under different environmental conditions. As for lipids, Figure 10B indicates a slight reduction in values over time in bag storage and greater stability in silo treatments, indicating lower oxidative degradation, which is consistent with Ludwig et al. (2021), who linked lipid preservation to maintaining lower temperatures. In Figure 10C, we observed a progressive decline in moisture content in both storage systems, with lower values recorded in the silo during the third sampling.

The behaviors observed in Figure 10 may be related to the lower relative air humidity during the period, associated with greater thermal control efficiency. According to Mamede et al. (2009) and Oliveira et al. (2025), environments with low humidity and stable temperatures tend to accelerate water loss in grains.

Tables 5, 6, and 7 present the results of the statistical analysis for lipid, total protein, and moisture data. The interaction between storage method and storage time (sampling) was significant for lipid and moisture contents. No significant difference was observed for total protein values concerning the evaluated factors. The experimental variability, given by the coefficient of variation, was quite low, which ensures reliability in the evaluated data.

Table 5:
F values calculated by analysis of variance (ANOVA) for chemical attributes (%) of soybeans stored in bag and silo across three sampling periods.

Source of variation	DF	Lipids	Proteins	Moisture
Storage (A)	1	0.341ns	0.259ns	10.021*
Sampling (C)	2	1.047ns	1.497ns	47.558**
A x C	2	6.924**	0.643ns	6.073*
CV - A (%)		0.84	0.74	2.97
CV - C (%)		0.77	0.71	2.48

• DF: Degrees of Freedom; **, *: significant (P < 0.01 and P < 0.05, respectively); ns: not significant by F test; CV: Coefficient of Variation.

Table 6:
Results of the mean comparison test for lipid and moisture content of soybeans stored in silo and bag over three sampling periods (breakdown of significant interactions).

Sampling	Lipids (%)		Moisture (%)
	Bag	Silo	Bag	Silo
1	25.88 aA	25.55 aB	13.37 aA	13.50 aA
2	25.46 bB	25.75 aA	13.42 aA	12.77 bB
3	25.51 bA	25.69 aA	12.49 bA	11.69 cB

• Means followed by the same lowercase letter in columns and uppercase letter in rows do not differ significantly by Tukey’s test (P < 0.05).

Table 7:
Results of the mean comparison test for protein content of soybeans stored in silo and bag across three sampling periods.

Storage	Proteins (%)
Bag	47.97 a
Silo	48.04 a
Sampling
1	48.14 a
2	47.87 a
3	48.01 a

• Means followed by the same letter do not differ significantly by Tukey’s test (P ≤ 0.05).

The breakdown of interactions (Table 6) shows that storage in bag led to a decrease in lipid content over time, while lipid levels remained stable under silo storage. Regarding moisture content, we observed a downward trend throughout the storage period, culminating during the driest time of year, with the reduction being more pronounced in the soybeans stored in the silo. This result occurred due to the burnout of the electrode in the vaporization system of the SIARCOMPAG , which was responsible for increasing the relative humidity of the air. As a result, the system became unable to prevent moisture loss in the product.

Tables 5, 6, and 7 show that the interaction between storage type and storage time was statistically significant (p < 0.05) for both lipid and moisture contents, with smaller variation in grains stored in the silo, indicating greater biochemical stability over time. This stability is associated with the psychrometric control of the storage environment, as demonstrated by Ziegler, Paraginski and Ferreira (2021), who reported reduced oxidative degradation in systems with controlled temperature and humidity. The lack of a significant effect on protein content reinforces the lower sensitivity of this parameter to environmental variation during storage (Kibar & Soydemir, 2025).

The physiological quality of the grains was significantly affected by both storage method and storage time (Table 8), with a drastic reduction in germination percentages for both conditions at the end of the experiment (8 months of storage). However, we observed a smaller impact on grains stored under controlled temperature and humidity.

Table 8:
Results of the mean comparison test for soybean germination stored in silo and bag across three sampling periods (breakdown of significant interactions).

Sampling	Germination (%)
	Bag	Silo
1	64.36 aB	84.75 aA
2	6.48 bB	47.25 bA
3	2.68 cB	43.26 cA

• Means followed by the same lowercase letter in columns and uppercase letter in rows do not differ significantly by Tukey’s test (P < 0.05).

In general, the results in Table 8 are consistent with Selvarani et al. (2024), who stated that soybeans stored for 8 months tend to show a drop in germination. Similarly, Muhamad et al. (2024) reported substantial reductions in germination percentage after 6 months of storage under ambient conditions.

Although deterioration in grain quality is inevitable, it can be mitigated by controlling temperature and relative humidity during storage (Leal et al., 2023). Toni et al. (2024) observed greater loss of physiological potential in seeds stored under ambient air compared to those kept in a dry chamber (20 °C and 50% RH) and a cold chamber (10 °C and 90% RH). Mitchener et al. (2025) also found smaller reductions in germination in a qualitatively ideal environment (20 °C and low RH) compared to a silo with conventional storage.

The data in Table 8 confirm that prolonged exposure to unfavorable conditions significantly increased physiological deterioration in grains, with germination dropping to 2.68% in bag storage after eight months, compared to 43.26% in the silo. This substantial difference highlights the impact of high temperature and humidity on cellular membrane degradation, as described by Sousa et al. (2025), directly affecting seed vigor and viability.

The analysis of variance indicated a significant effect of the storage method on the incidence of all pathogens evaluated (Tables 9 and 10), with lower incidence observed in the silo across all cases. However, time did not significantly affect all microorganisms, as observed for Fusarium and Macrophomina. The high coefficients of variation, especially for Alternaria and Macrophomina, were due to the presence of null data in several replicates, which increased relative dispersion and compromised statistical homogeneity for these factors. These results are consistent with Alizadeh et al. (2025), who reported significant variation in the incidence of Macrophomina phaseolina in soybean seeds influenced by different storage conditions, emphasizing the importance of environmental control in preserving seed sanitary quality.

Table 9:
F values calculated by analysis of variance (ANOVA) for pathogen incidence (%) in soybeans stored in bag and silo across three sampling periods.

Source of variation	DF	Alternaria	Aspergillus	Cercospora	Fusarium
Storage (A)	1	8.96**	446.88**	108.73**	200.66**
Sampling (C)	2	8.25**	14.90**	6.35**	0.49ns
A x C	2	8.25**	3.86*	0.27ns	0.85ns
CV - A (%)		231.41	10.68	20.01	13.24
CV - C (%)		197.86	5.46	18.96	13.90

• DF: Degrees of Freedom; **, *: significant (P < 0.01 and P < 0.05, respectively); ns: not significant by F test; CV: Coefficient of variation.

Table 10:
F values calculated by analysis of variance (ANOVA) for pathogen incidence (%) in soybeans stored in bag and silo across three sampling periods.

Source of variation	DF	Macrophina	Penicillium	Trichoderma
Storage (A)	1	7.95*	835.04**	223.57**
Sampling (C)	2	1.42ns	3.66*	6.19**
A x C	2	1.42ns	0.00ns	0.37ns
CV - A (%)		245.93	8.61	15.52
CV - C (%)		327.32	7.71	11.95

• DF: Degrees of Freedom; **, *: significant (P < 0.01 and P < 0.05, respectively); ns: not significant by F test; CV: Coefficient of variation.

Contamination levels in bag storage remained higher than those in silo storage throughout the experiment, with no incidence of Alternaria and Macrophomina observed in the silo across all three samplings. It is possible to note increases in the incidence of all other pathogens over time, though at a lower intensity in the silo (Tables 11 and 12).

Table 11:
Results of the mean comparison test for Alternaria and Aspergillus incidence in soybeans stored in silo and bag across three sampling periods (values expressed in percentages) (breakdown of significant interactions).

Sampling	Alternaria		Aspergillus
	Bag	Silo	Bag	Silo
1	0.05 bA	0.00 aA	84.25 cA	43.88 aB
2	3.50 aA	0.00 aB	90.13 bA	45.75 aB
3	0.00 bA	0.00 aA	95.00 aA	47.38 aB

• Means followed by the same lowercase letter in columns and uppercase letter in rows do not differ significantly by Tukey’s test (P < 0.05).

Table 12:
Results of the mean comparison test for Cercospora, Fusarium, Macrophina, Penicillium, and Trichoderma incidence in soybeans stored in silo and bag across three sampling periods (values expressed in percentages).

Storage	Cercospora	Fusarium	Macrophina	Penicillium	Trichoderma
Bag	60.04 a	71.38 a	0.83 a	89.29 a	71.67 a
Silo	32.25 b	40.96 b	0.00 b	42.13 b	35.71 b
Sampling
1	41.06 b	56.63 a	0.81 a	63.81 b	50.13 b
2	45.38 ab	54.63 a	0.00 a	64.88 ab	52.94 ab
3	52.00 a	57.25 a	0.44 a	68.44 a	58.00 a

• Means followed by the same letter do not differ significantly by Tukey’s test (P ≤ 0.05).

The results in Tables 11 and 12 indicate statistically significant reductions (p < 0.05) in pathogen incidence in grains stored in silos with psychrometric control, particularly for Aspergillus and Penicillium, whose mean values were lower than those observed under bag storage. This trend confirms that environments with ideal temperatures and controlled humidity suppress fungal activity, as reported by Yu (2025), who described inhibition of storage fungi growth under stabilized thermal conditions. Thus, maintaining stable psychrometric parameters represents an effective strategy for mitigating microbiological risks during storage.

The linear correlation coefficients between germination percentages and fungal incidence were significant (Figure 11), all being inversely proportional. Only for fungi with lower incidence (Macrophomina phaseolina and Alternaria) was no significant correlation with germination found.

Figure 11:
Pearson linear correlation diagram between germination and fungal incidence. Source: The Authors.

The Pearson correlation coefficients shown in Figure 11 reveal strong negative and statistically significant relationships between germination and the incidence of fungi such as Aspergillus (r = -0.66), Penicillium (r = -0.61), and Trichoderma (r = -0.61), indicating that increased fungal colonization severely compromises the physiological potential of the grains. Furthermore, the high positive correlations among the pathogens themselves, mostly ranging between r = 0.80 and r = 1.00, suggest synergistic competition under favorable environmental conditions, particularly in non-refrigerated environments. These results reinforce the role of psychrometric control as a key factor in preserving seed viability, as supported by Padia et al. (2023).

Figure 12 indicates the deterioration of soybean grains stored in bag, with a greater presence of mycelium and fungal sporulation compared to the grains stored in silo, which maintained a better appearance and lower visible colonization.

Figure 12:
Soybean grains from bag and silo storage after the first (4 months) and last (8 months) sanitary evaluation. Source: The Authors.

As reported by Souza, Souza and Ramser (2024), the high incidence of field fungi such as Fusarium is associated with delayed harvest and prolonged exposure to field moisture-both factors present in this study due to the waiting period for grains to reach 13% moisture content. This delay increased initial colonization by saprophytic fungi still in the field, as described by Lindemann et al. (2021) and Batzer et al. (2024), who found that a harvest delay of up to 15 days intensifies fungal infestation. Nonetheless, the progression of storage fungi such as Aspergillus and Penicillium was more pronounced in bag-stored grains, as explained by Medeiros et al. (2012) and Olszewski et al. (2025), who attributed this proliferation to deficiencies in humidity and temperature control during storage.

Tavares et al. (2025) observed loss of viability in field fungi spores over the storage period, reflected by the decline in their incidence due to moisture loss. Carvalho et al. (2021) reported similar behavior, where field fungi incidence decreased over time, but storage fungi (Aspergillus) showed an increase with prolonged storage. Thus, in this study, a reduction in field fungi levels over time was not observed; however, consistent with the literature, we noted a loss in spore viability, as the spores observed in the final sanitary tests were predominantly smaller than those observed initially (Figure 12).

Figure 12 indicates that the cooling system performed better in almost all evaluated parameters, being able to mitigate fungal development, with lower percentages of growth and infection for all microorganisms, as the average temperatures in the silo remained below 18.5°C (Table 4). According to Shango et al. (2024), storage at lower temperatures contributed to reduced damage caused by microorganisms. Freitas, R. et al. (2024) described that the flow of warm air through the grain mass accelerates the grain’s respiratory process, favoring the development of insects and fungi in stored mass. Finally, Cortese, De Oliveira and Fernandes (2025) found that temperatures below 15°C are capable of reducing insect and microorganism attacks on grains, as observed in this investigation.

The physiological results resulting from this system, such as the reduction of lipid acidity and the increase in germination rates in soybeans stored under controlled temperature and humidity conditions, highlight the superiority of SIARCOMPAG compared to conventional storage. However, the adoption of this technology does not rely solely on its effectiveness in preserving grain quality but also on its economic feasibility and energy performance.

Studies such as those by Lopes and Steidle Neto (2021) demonstrated that the use of grain coolers in Brazil presents technical feasibility and positive financial returns, especially when associated with the reduction of qualitative losses and the preservation of seed physiological integrity. The authors reported an average payback time of less than three harvests, considering the reduction of fungal damage and maintenance of germination potential in different crops.

Furthermore, Liu et al. (2025) assessed the operational performance of systems with heat pumps and humidity control in agricultural environments, recording a coefficient of performance (COP) above 3.0, even under variations in relative humidity. Since SIARCOMPAG operates on similar principles, with simultaneous temperature and humidity control via PLC automation, its results indicate compatibility with the energy efficiency standards documented in international literature.

Conclusions

Storage under controlled temperature and humidity using a heat pump was more effective in preserving grain quality than conventional bag storage. Grains stored in silos maintained stable lipid levels, higher germination, and lower microbial contamination, while bag-stored grains showed increased free fatty acids and higher fungal incidence from the second month onward. The heat pump system offers a sustainable solution for tropical regions, and redundant humidity control is recommended to ensure storage stability.

Acknowledgements

The authors thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), the Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul (FUNDECT), the Federal University of Grande Dourados (UFGD), and the State University of Western Paraná (UNIOESTE) for their financial and structural support for the research.

Data Availability Statement

Data available upon request to authors.

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• Editor de seção:
  Renato Paiva

Publication Dates

• Publication in this collection
  17 Oct 2025
• Date of issue
  2025

History

• Received
  27 May 2025
• Accepted
  15 July 2025