Analysis of Heat and Moisture Transfer and Fungi-Induced Hot Spots in Maize Bulk with Different Broken Kernel Contents
, Guixiang Chen 1,2,*, Deqian Zheng 1,2, Jun Yin 3, Chenxing Cui 1,2 and Huankun Lu 1Round 1
Reviewer 1 Report
Comments and Suggestions for Authors
The manuscript presents an investigation of fungal growth and hot spot development in maize bulk with varying broken kernel content (BKC). While the study is relevant and contributes to understanding grain storage dynamics, there are several areas requiring improvement. Language clarity and grammar also need revision to enhance readability and precision.
- Line 36 - It means that the average yield is only 650 kg/ hectares. Too low!
- Line 46 - I suggest to change infestation with "activity" or "damage", because infestation is appropriate for insects, but not for fungi (this are microorganisms, hence produce infections).
- Line 77 - how was the BKC determined? how was the sample conformed to do this determination? there were replicates?
- Line 76 - what is filtration? sieving?
- Line 77 – 80 - Explain better the conformation of both samples.
- Line 82 - How much time? Too little time might not be sufficient for moisture homogenization, too much could result in mold development.
- Line 87 - How were the kernel density and porosity determined? Method?
- Lines 89-91 - check wording - I do not understand the meaning of this sentence. Additionally, explain how the fungal growth was induced, and why it was easy to do it.
- Line 93 - what is a "grain bulk condition detection"? explain.
- Line 100 - What is PMMA? spell it in full.
- Line 131 - provide literature references for the Fungal Spore Number technique.
- Line 141 - The usual terminology is dry matter loss (DML). I suggest to use DML to avoid confusing.
- Line 144 - I think this equation is wrong, since I could not obtain the value of DML with the information provided. Delta CO2 indicates respiration. Delta O2 also indicates respiration. In case that the RQ (RCO2/RO2) = 1, then, according to this equation, both terms will cancel each other. In addition to that, there is no reference to the publication where this equation was derived. I suggest to use a more widespread and accepted equation for computing DML as the one extensively used by several authors:
- Al-Yahaya, S.A., Bern, C.J., Misra, M.K., Bailey, T.B., 1993. Carbon dioxide evolution of fungicide-treated high-moisture corn. Trans. ASAE 36, 1417–1422.
- Bern, C.J., Steele, J.L., Morey, R. V, 2002. Shelled corn CO2 evolution and storage time for 0.5% dry matter loss. Appl. Eng. Agric. 18, 703–706.
- Lacey, J., Hamer, A., Magan, N., 1994. Respiration and losses in stored wheat under different environment conditions, in: Highley, E.; Wright, E.J.; Banks, H.J.; Champ, B.R. (Ed.), Proceedings of the 6th International Working Conference on Stored-Product Protection. 17-23 April 1994, Canberra, Australia, pp. 1007–1013.
- Marcos Valle, F., Gastón, A., Abalone, R., de la Torre, D., Castellari, C., Bartosik, R., 2021. Study and modelling the respiration of corn seeds (Zea mays L.) during hermetic storage. Biosyst. Eng. 8, 45–57. https://doi.org/10.1016/j.biosystemseng.2021.05.009
- Rukunudin, I.H., Bern, C.J., Misra, M.K., Bailey, T.B., 2004. Carbon dioxide evolution from fresh and preserved soybeans. Trans. ASAE 47, 827–834.
- Steele, J.L., Saul, R.A., Hukill, W. V, 1969. Deterioration of shelled corn as measured by carbon dioxide production. Trans. ASAE 12, 685–689.
- Lines 170-173 - This sentence needs a more comprehensive explanation. Why the airflow, in the horizontal plane, would be higher in y=046 than in y=0.08?
- Line 200 - Proportion of what? total amount of grain? Define better this proportion.
- Lines 211-214 - Also, BK increases respiration (and heat release) because the grain has the endosperm directly exposed to the microbial action. Thus, more proportion of BK in the bulk also implies more heat release and, hence, a larger area affected. The authors must also address this issue.
- Lines 217-228 - The authors should offer a more convincing explanation of why the RH and MC (Fig 8) close to the hot wall increases, in apparent contradiction with the hypothesis that water vapor flows towards the cold wall.
- Lines 271-272 - Are this differences statistically significant? Was a statistic test performed?
- Lines 290-305 - The model was not validated with an independent set of data, so I would suggest to address this issue for the reader.
- Line 371 - In fact, corn at 16% MC can hold microbial activity. Most likely, the O2 consumption and CO2 release observed at the early stages was also due to fungal growth, rather than to the seed metabolism. For more information you can review Walters, C., Hill, L.M., Wheeler, L.J., 2005. Dying while dry: Kinetics and mechanisms of deterioration in desiccated organisms. Integr. Comp. Biol. 45, 751–758. https://doi.org/10.1093/icb/45.5.751.
- Lines 381-383 - I disagree with this sentence. What does "inability of organic matter consumption to meet the needs of fungal growth" even mean? It lacks biological relevance and clarity! Additionally, molds can grow with O2 concentrations really low. However, increasing temperatures might affect the development of some fungal species. This would be the more accepted interpretation of why the hotspot dies out (and the reduction in the RH, off course).
Comments for author File: 
Comments.pdf
Author Response
Reply to reviewer: 1
We are grateful to reviewer#1 for his/her effort in reviewing our manuscript and his/her positive feedback. The summary of our work as written by this reviewer is precise. Here below we address the questions and suggestions raised by reviewer#1.
Comment 1: Line 36 - It means that the average yield is only 650 kg/ hectares. Too low!
Response: Thank you very much for your careful reminder and valuable advice. The data on maize planting area and annual maize production are sourced from the "China Statistical Yearbook" [2]. To avoid ambiguity, we only described the production of maize to highlight the importance of this research subject. Thank you again sincerely for your careful suggestions and professional guidance.
Page 1, Lines 36−37:
The annual maize production in China is 288 million tons, accounting for about 41.54% of the total grain production [2].
Comment 2: Line 46 - I suggest to change infestation with "activity" or "damage", because infestation is appropriate for insects, but not for fungi (this are microorganisms, hence produce infections).
Response: Thank you very much for your careful reminder and valuable advice. We have changed “infestation” to "damage" according to your suggestions.
Page 2, Lines 50−52:
The recent studies showing the structure of maize kernels is damaged during mechanical harvesting, transportation, and loading, making them more susceptible to damage from fungi and insect [11, 12].
Comment 3: Line 77 - how was the BKC determined? how was the sample conformed to do this determination? there were replicates?
Response: Thank you very much for your careful reminder and valuable advice. According to GB/T 5494-2019, five maize samples with a mass of approximately 500 g were randomly selected from the screened samples, and the BKC was determined to be 4.26% (BKC4.26) based on the ratio of the BKC to the sample mass.
GB/T 5494-2019; Inspection of Grain and Oils– Determination of Foreign Matter and Unsound Kernels of Grain and Oilseeds. State Administration for Market Regulation: Beijing, China: 2019.
Page 2, Lines 79−82:
Five maize samples with a mass of approximately 500 g were randomly selected from the screened samples, and the BKC was determined to be 4.26% (BKC4.26) based on the ratio of the BKC to the sample mass [18].
Comment 4: Line 76 - What is filtration? sieving?
Response: Thank you very much for your careful reminder and valuable advice. We have changed "filtration" to "sieving" according to your suggestions.
Page 2, Lines 78−79:
Mold maize kernels and other impurities were removed through sieving and sorting before the experiment.
Comment 5: Line 77–80 - Explain better the conformation of both samples.
Response: Thank you very much for your careful reminder and valuable advice. The manuscript focuses on the influence of broken kernel content on the internal heat and moisture transfer and local mold growth in maize bulk. We retrieved approximately 200 kg of maize from the warehouse, screened and removed impurities, and took two samples of approximately 70 kg, one of which was randomly mixed with a portion of broken kernels sorted from the sieved sample. The adjusted content of broken kernels was 6.14% (BKC6.14), while the other sample is not treated. That is, the BKC of the two experimental samples was 4.26% and 6.14%, and there is no difference in other conformation. Thank you again sincerely for your careful suggestions and professional guidance.
Page 2, Lines 82−86:
Take two samples of approximately 70 kg, one of which was randomly mixed with a portion of broken kernels sorted from the sieved sample. The adjusted content of broken kernels was 6.14% (BKC6.14), while the other sample is not treated. That is, the BKC of the two experimental samples was 4.26% and 6.14%, and there is no difference in other conformation.
Comment 6: Line 82 - How much time? Too little time might not be sufficient for moisture homogenization, too much could result in mold development.
Response: Thank you very much for your careful reminder and valuable advice. We have reviewed relevant reports (Sampietro et al, 2009; Suleiman et al., 2018) and combined with the accumulation of previous experiments (Liu et al., 2022; Liu et al., 2023), corn samples were stored at 4 °C for 48 hours before the experiment to maintain moisture balance.
Sampietro, D.A.; Vattuone, M.A.; Presello, D.A.; Fauguel, C.M.; Catalán, C.A.N. The pericarp and its surface wax layer in maize kernels as resistance factors to fumonisin accumulation by Fusarium verticillioides. Crop Prot. 2009, 28, 196−200. https://doi.org/10.1016/j.cropro.2008.09.010.
Suleiman, R.; Bern, C.J.; Brumm, T.J.; Rosentrater, K.A. Impact of moisture content and maize weevils on maize quality during hermetic and non-hermetic storage. J. Stored Prod. Res. 2018, 78, 1−10. https://doi.org/10.1016/j.jspr.2018.05.007.
Liu, C.S.; Chen, G.X.; Zhou, Y.; Yue, L.F.; Liu W.L. Investigation on compression and mildew of mixed and separated maize. Food Sci. Nutr. 2023, 11(5), 2118−2129. https://doi.org/10.1002/fsn3.2985.
Liu, C.S.; Zhou, Y.; Chen, G.X.; Zheng, D.Q.; Yue, L.F.; Compression and fungal heat production in maize bulk considering kernel breakage. Appl. Sci-Basel. 2022, 12(10), 4870. https://doi.org/10.3390/app12104870.
Page 2, Lines 86−88:
Two samples were evenly sprayed with sterile water of the same mass and stored at 4 °C for 48 h to allow moisture equilibrium [10,19].
Comment 7: Line 87 - How were the kernel density and porosity determined? Method?
Response: Thank you very much for your careful reminder and valuable advice. According to GB/T 5518-2008, 10 ml of 20% ethanol is injected into a graduated cylinder at room temperature, and then approximately 5 g of the maize sample (m1, accurate to 0.01 g) is placed in ethanol, shaken slightly to remove bubbles, and once the liquid level stabilizes, the volume of liquid rising (v) is immediately read.
The porosity of the maize bulk is determined based on the grain bulk density (ρ) and the kernel relative density:
where, V is maize bulk volume, m3; m is the mass of experimental maize sample, kg.
GB/T 5494-2008; Inspection of Grain and Oil-Determination of Relatively Density of Grain and Oilseeds. General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China: Beijing, China: 2008.
Page 3, Lines 92−93:
The kernel relatively density is 1293 kg/m3 [21], and the porosity of maize bulk is 0.422 and 0.418 in BKC4.26 and BKC6.14.
Comment 8: Lines 89-91 - check wording - I do not understand the meaning of this sentence. Additionally, explain how the fungal growth was induced, and why it was easy to do it.
Response: Thank you very much for your careful reminder and valuable advice. We apologize for the lack of rigor and clarity in our wording here. During the process of grain storage, the phenomenon of heat and moisture transfer inside the grain bulk happen every day. When the temperature and moisture at certain locations reach conditions suitable for fungal growth, fungi will develop and form hot spots.
Page 3, Lines 95−98:
In the process of grain storage, the phenomenon of heat and moisture transfer inside the grain bulk happen every day due to the changing external environment of the warehouse. When the temperature and moisture at certain locations reach conditions suitable for fungal growth, fungi will develop and form hot spots.
Comment 9: Line 93 - what is a "grain bulk condition detection"? explain.
Response: Thank you very much for your careful reminder and valuable advice. We apologize for the lack of rigor and clarity in our wording here. We want to express the detection of carbon dioxide/oxygen concentration and temperature and humidity changes in the grain bulk during storage using gas detector and Fluke 2638A data acquisition unit. To avoid ambiguity, we have revised the manuscript according to your suggestions. Thank you again sincerely for your careful suggestions and professional guidance.
Page 3, Lines 100−102:
The system included a test bin, temperature control system, gas detection device, temperature and humidity detection device and data acquisition system.
Comment 10: Line 100 - What is PMMA? spell it in full.
Response: Thank you very much for your careful reminder and valuable advice. We have spelt PMMA in full according to your suggestions.
Page 3, Line 108−109:
The front and rear side plates were made of polymethyl methacrylate (PMMA) with a thickness of 0.05 m, used to observe the growth of fungi during storage.
Comment 11: Line 131 - provide literature references for the Fungal Spore Number technique.
Response: Thank you very much for your careful reminder and valuable advice. The determination of fungal spore number is based on LS/T6132-2018, and previous literature (Wang et al., 2021; Wu et al., 2020) has reported spore counting results.
Wang, X.M.; Xie, Q.Z.; Shi, J.F.; Zhou, X.Q. Cloud image analysis of temperature changes during bulk corn microbiological heating. Int. J. Food Prop. 2021, 24(1), 1777−1789. https://doi.org/10.1080/10942912.2021.2000432.
Wu, Z.D.; Zhang, Q.; Yin, J. Wang, X.M.; Zhang, Z.J.; Wu, W.F.; Li, F.J. Interactions of mutiple biological fields in stored grain ecosystems. Sci. Rep-Uk. 2020, 10(1), 9302. https://doi.org/10.1038/s41598-020-66130-6.
LS/T6132-2018; Inspection of Grain and Oils–Storage Fungal Examination–Enumeration Spores of Fungi. State Administration of Grain: Beijing, China: 2018.
Page 4, Lines 148−150:
To avoid measurement errors, each sample was measured three times, and the average value of the three-test data was considered after eliminating unreasonable values [6,15,22].
Comment 12: Line 141 - The usual terminology is dry matter loss (DML). I suggest to use DML to avoid confusing.
Response: Thank you very much for your careful reminder and valuable advice. We have changed "LDM" to "DML" according to your suggestions, and conducted a full-text inspection.
Page 4, Line 151:
2.2.6 Dry matter loss (DML)
Comment 13: Line 144 - I think this equation is wrong, since I could not obtain the value of DML with the information provided. Delta CO2 indicates respiration. Delta O2 also indicates respiration. In case that the RQ (RCO2/RO2) = 1, then, according to this equation, both terms will cancel each other. In addition to that, there is no reference to the publication where this equation was derived. I suggest to use a more widespread and accepted equation for computing DML as the one extensively used by several authors:
Al-Yahaya, S.A., Bern, C.J., Misra, M.K., Bailey, T.B., 1993. Carbon dioxide evolution of fungicide-treated high-moisture corn. Trans. ASAE 36, 1417–1422.
Bern, C.J., Steele, J.L., Morey, R. V, 2002. Shelled corn CO2 evolution and storage time for 0.5% dry matter loss. Appl. Eng. Agric. 18, 703–706.
Lacey, J., Hamer, A., Magan, N., 1994. Respiration and losses in stored wheat under different environment conditions, in: Highley, E.; Wright, E.J.; Banks, H.J.; Champ, B.R. (Ed.), Proceedings of the 6th International Working Conference on Stored-Product Protection. 17-23 April 1994, Canberra, Australia, pp. 1007–1013.
Marcos Valle, F., Gastón, A., Abalone, R., de la Torre, D., Castellari, C., Bartosik, R., 2021. Study and modelling the respiration of corn seeds (Zea mays L.) during hermetic storage. Biosyst. Eng. 8, 45–57. https://doi.org/10.1016/j.biosystemseng.2021.05.009
Rukunudin, I.H., Bern, C.J., Misra, M.K., Bailey, T.B., 2004. Carbon dioxide evolution from fresh and preserved soybeans. Trans. ASAE 47, 827–834.
Steele, J.L., Saul, R.A., Hukill, W. V, 1969. Deterioration of shelled corn as measured by carbon dioxide production. Trans. ASAE 12, 685–689.
Response: Thank you very much for your careful reminder and valuable advice. The model used to estimate DML takes into account the simultaneous presence of aerobic and anaerobic respiration processes in a confined space. The DML caused by respiration occurs through two different mechanisms of glucose breakdown. During aerobic respiration, carbohydrates are broken down into CO2 and H2O, while during anaerobic respiration, carbohydrates are broken down into CO2 and C2H5OH:
where x and y are the molar amounts of glucose consumed according to equations, respectively.
To determine the dry matter loss during storage, these molar amounts are determined by the concentration of CO2 produced and O2 consumed within the sealed bin throughout the entire storage period. Considering the simultaneous occurrence of aerobic and anaerobic respiration processes in a sealed system, the final model for estimating DML can be represented by equation (1). Thank you again sincerely for your careful suggestions and professional guidance.
Page 4, Lines 152-153:
An estimation model considering aerobic and anaerobic respiration is used to determine the DML over time [23].
(1)
Santos, S. B.D.; Martins, M.A.; Faroni, L.R.D.A.; Brito Junior, V.R.D. Dry matter loss in corn kernels stored in airtight bags. Rev. Cienc. Agron. 2012, 43, 674–682. https://doi.org/10.1590/S1806-66902012000400008
Comment 14: Lines 170-173 - This sentence needs a more comprehensive explanation. Why the airflow, in the horizontal plane, would be higher in y=046 than in y=0.08?
Response: Thank you very much for your careful reminder and valuable advice. When the temperature of the hot wall increases, the kernels near the hot wall heat up more than the kernels towards the center of the mass, as does the air that is close to the hot wall, causing its density to decrease and upward currents of air to be formed close to the hot wall, thereby causing air molecules in the cold wall of the test bin to form a downward stream of cold air. It causes the airflow velocity between the upper layer (y=0.46 m) pores is greater than that in the lower layer (y=0.08 m) under the action of thermal buoyancy force (Fig. S1).
Page 5, Lines 182-189:
When the temperature of the hot wall increases, the kernels near the hot wall heat up more than the kernels towards the center of the mass, as does the air that is close to the hot wall, causing its density to decrease and upward currents of air to be formed close to the hot wall, thereby causing air molecules in the cold wall of the test bin to form a downward stream of cold air. It causes the airflow velocity between the upper layer (y=0.46 m) pores is greater than that in the lower layer (y=0.08 m) under the action of thermal buoyancy force (Fig. S1). The result is similar to that reported by Lopes et al.[24]
Lopes, D.C.; Martins, J.H.; Castro Melo, E.; Barros Monteiro, P.M. Aeration simulation of stored grain under variable air ambient conditions. Postharvest Biol. Technol. 2006, 42(1), 115−120.https://doi.org/10.1016/j.postharvbio.2006.05.007
Comment 15: Line 200 - Proportion of what? total amount of grain? Define better this proportion.
Response: Thank you very much for your careful reminder and valuable advice. We apologize for the lack of rigor and clarity in our wording here. The proportion here refers to the ratio of the area in the maize bulk where the temperature of the mid-plane is higher than 30 ℃ to the area of the mid-plane. We have revised the manuscript according to your suggestions.
Page 6, Lines 217-219:
Fig. 5 shows the proportion of the area in the maize bulk where the temperature of the mid-plane is higher than 30 ℃ to the area of the mid-plane.
Comment 16: Lines 211-214 - Also, BK increases respiration (and heat release) because the grain has the endosperm directly exposed to the microbial action. Thus, more proportion of BK in the bulk also implies more heat release and, hence, a larger area affected. The authors must also address this issue.
Response: Thank you very much for your careful reminder and valuable advice. Your suggestion has made the explanation of the proportion of HTA caused by the increase in BKC clearer, and we have supplemented this part according to your suggestions. Thank you again sincerely for your careful suggestions and professional guidance.
Page 6, Lines 226-236:
The room temperature fluctuation caused the heat of fungal respiration to be lost through the PMMA plate from 897 h to 1432 h. However, the heat generated by rapid fungal growth was higher than the lost heat, and the proportion of HTA in BKC6.14 is higher than that in BKC4.26. The broken kernels increase respiration (and heat release) because the grain has the endosperm directly exposed to the microbial action. Thus, the higher the proportion of BKC in maize bulk, the more heat is released, and the larger the affected area. After 1432 h, the proportion of HTA in BKC6.14 is slightly lower than that in BKC4.26, We speculate that the decrease in respiratory intensity is due to the consumption of oxygen and organic matter, and the increase in broken kernels in the grain bulk increases the contact area between maize kernels, improves thermal conductivity, and accelerates the heat loss in maize bulk.
Comment 17: Lines 217-228 - The authors should offer a more convincing explanation of why the RH and MC (Fig 8) close to the hot wall increases, in apparent contradiction with the hypothesis that water vapor flows towards the cold wall.
Response: Thank you very much for your careful reminder and valuable advice. When the temperature at the hot spots continues to rise and is higher than the control temperature of the hot wall, a temperature gradient is formed between the hot spots and the cold wall, as well as between the hot spots and the hot wall. The maize kernels at the hot spots desorb water, and under the action of the temperature gradient, a water vapor pressure gradient in the same direction as the temperature gradient is formed in maize bulk, causing water vapor to diffuse along the temperature gradient direction. Moreover, due to the density difference of air inside the maize bulk caused by temperature gradient, natural convection of air is formed, which also promotes the transfer of moisture along the direction of temperature gradient.
Page 7, Lines 247-256:
The reason is that when the temperature at the hot spots continues to rise and is higher than the control temperature of the hot wall, a temperature gradient is formed between the hot spots and the cold wall, as well as between the hot spots and the hot wall. The maize kernels at the hot spots desorb water, and under the action of the temperature gradient, a water vapor pressure gradient in the same direction as the temperature gradient is formed in maize bulk, causing water vapor to diffuse along the temperature gradient direction. Moreover, due to the density difference of air inside the maize bulk caused by temperature gradient, natural convection of air is formed, which also promotes the transfer of moisture along the direction of temperature gradient.
Comment 18: Lines 271-272 - Are this differences statistically significant? Was a statistic test performed?
Response: Thank you very much for your careful reminder and valuable advice. FSN data were analyzed using the one-way analysis of variance (ANOVA) followed by Tukey’s post hoc mean separation test in SPSS version 22.0, with data variability expressed as the standard error of the mean. p < 0.05 was considered statistically significant. The results showed that there was no significant difference in FSN between the two samples (p>0.05), but the FSN of BKC6.14 was higher than that of BKC4.26.
Page 9, Lines 301-302:
The results showed that there was no significant difference in FSN between the two samples (p>0.05), but the FSN of BKC6.14 was higher than that of BKC4.26.
Comment 19: Lines 290-305 - The model was not validated with an independent set of data, so I would suggest to address this issue for the reader.
Response: Thank you very much for your careful reminder and valuable advice. We conducted experiments using two sets of maize samples with different broken kernel contents in the manuscript. Although the location of hot spots, temperature rise, respiration, and other factors were different, resulting in different parameters for each item, the equation form was the same, and we also compared it with the experimental results. Overall, this is our first exploration of the relationship between local hot spots development and multiple physical factors. We are also conducting local mold tests on maize bulk with different moisture contents using the same experimental equipment. At the same time, we will conduct more in-depth research to verify the universality of the equation. Thank you again sincerely for your careful suggestions and professional guidance.
Comment 20: Line 371 - In fact, corn at 16% MC can hold microbial activity. Most likely, the O2 consumption and CO2 release observed at the early stages was also due to fungal growth, rather than to the seed metabolism. For more information, you can review Walters, C., Hill, L.M., Wheeler, L.J., 2005. Dying while dry: Kinetics and mechanisms of deterioration in desiccated organisms. Integr. Comp. Biol. 45, 751–758. https://doi.org/10.1093/icb/45.5.751.
Response: Thank you very much for your careful reminder and valuable advice. Your suggestion has made our understanding of the production of carbon dioxide and the consumption of oxygen in grain bulk clearer and more accurate. We have revised this section according to your suggestions. Thank you again sincerely for your careful suggestions and professional guidance.
Page 12, Lines 400-401:
Before local hot spots occur, the rate of oxygen decrease and carbon dioxide increase is relatively low due to the weak respiration of fungi [33].
Walters, C.; Hill, L.M.; Wheeler, L.J. Dying while dry: Kinetics and mechanisms of deterioration in desiccated organisms. Integr. Comp. Biol. 2005, 45, 751−758. https://doi.org/10.1093/icb/45.5.751.
Comment 21: Lines 381-383 - I disagree with this sentence. What does "inability of organic matter consumption to meet the needs of fungal growth" even mean? It lacks biological relevance and clarity! Additionally, molds can grow with O2 concentrations really low. However, increasing temperatures might affect the development of some fungal species. This would be the more accepted interpretation of why the hot spot dies out (and the reduction in the RH, off course).
Response: Thank you very much for your careful reminder and valuable advice. Due to our insufficient understanding of Wu et al.'s report on the development of microorganisms in grain bulk, the explanation here is not rigorous enough. Wu et al. summarized that high temperature, consumption of organic matter, decrease in oxygen content, and increase in carbon dioxide concentration are all physical conditions that may limit microbial growth. When the temperature reaches the thermal death limit for fungi, the fungi will be killed. Your suggestions are very helpful for us to understand the evolution of microorganisms in grain storage. Thank you again sincerely for your careful suggestions and professional guidance.
Page 12, Lines 410-416:
The temperature at the hot spots reached its peak and then decreases as reported by Wu et al [15], who concluded that excessively high temperatures can affect the development of some fungal species, and the reduction of available grain energy supply, oxygen consumption, increase in carbon dioxide concentration, or accumulation of other metabolites may all limit fungal growth. In this study, in addition to temperature fluctuations caused by environmental factors, the temperature at hot spots showed an overall upward trend. The maximum temperature values are all below 40 °C.
If you and reviewers have any other questions, please do not hesitate to contact us as soon as possible. We thank you and reviewers again for your patience, help and constant attention to our manuscript.
Sincerely yours,
Guixiang Chen
cgx@haut.edu.cn
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for Authors
In the study titled Analysis of heat and moisture transfer and fungi-induced hot spots in maize bulk with different broken kernel content the problem of storage safety of corn bulk with various content od broken kernel was described. Authors analyzed the effect of various contents of broken kernels in bulk on the formation of hot spots. Additionally the changes of local moisture content and loss of dry matter in the hot spots was investigated. Based on the results the model for prediction of temperature of hot spots was developed and validated.
The issues raised in the study are interesting and important for safe storage of maize kernels. The knowledge about the mechanism of fungal growth and the effect of storage conditions and materials parameters are crucial for storage optimization to prevent the fungal growth and kernel quality deterioration. The results presented in the study can be used in practice as a guide for choosing proper storage condition and prevent kernel loses.
In overall the paper was prepared carefully. The content is well organized and easy to follow for readers. The title, abstract and keywords corresponds to the content of the article. The figures and tables were properly choose and clear. The main advantage of the paper is the new knowledge about the relations between the temperature raises in the hot spots and moisture content, carbon dioxide and oxide concentrations in the maize bulk, which brings closer to explain the mechanism of fungal growth in damaged kernels.
Despite the good reception of the work, its careful preparation and substantive correctness, there are some imperfections and issues requiring clarification and supplementation, presented below:
· 1) In the introduction section the wider discussion of the effect of different factors on fungal growth in bulk kernels will be beneficial. Moreover the recent studies showing the role of broken kernels on fungal growth should be added.
· 2) How the model described by equation 2 was obtained? Which statistical methods were used? What was confidence level? Was all the factors included in the model significant? Which of the factors have the highest influence on the temperature prediction? Are all of the constants of the model presented in the table 1 significant?
· 3) In the discussion section you could also consider the effect of the maize type and fungal species on the hot spot formation.
Author Response
Manuscript ID: agriculture-3432477
Title: Analysis of heat and moisture transfer and fungi-induced hot spots in maize bulk with different broken kernel content
Journal: Agriculture
24-Jan-2025
We have received your letter dated January 19, 2025, giving us your and reviewers′ comments for the modifications on our manuscript (agriculture-3432477). The authors much appreciate the respectful editor and reviewers for their careful review of our manuscript. The scientific quality of the manuscript has been enhanced in light of the valuable comments. The authors have taken full considerations of all these comments and made clarifications and corrections as advised by the reviewers. A detailed list of changes mentioned point by point with respect to the reviewers’ comments is included in this reply letter, and it is clearly indicated in what part of the revised manuscript these comments are implemented. In this context, the black texts are those given by the respectful reviewers. The blue texts are our response in this file, which might be more than those included in the revised manuscript. The green texts are the main content included in the revised manuscript. Thanks again to the hard work of the editor and reviewers!
Reply to reviewer: 2
We are grateful to reviewer#2 for his/her effort in reviewing our manuscript and his/her positive feedback. The summary of our work as written by this reviewer is very supportive. Here below we address the questions and suggestions raised by reviewer#2.
Comment 1: In the introduction section the wider discussion of the effect of different factors on fungal growth in bulk kernels will be beneficial. Moreover, the recent studies showing the role of broken kernels on fungal growth should be added.
Response: Thank you very much for your careful reminder and valuable advice. Your suggestions have been very helpful in improving the rationality of our introduction structure, and we have revised the introduction section based on your suggestions. Thank you again sincerely for your careful suggestions and professional guidance.
Page 2, Lines 44-52:
The factors that affect fungal growth in stored grain bulk are complex, such as temperature, moisture, oxygen concentration [7], impurities [8], and local grain conformation. Appropriate temperature and moisture conditions will promote the continuous growth of fungi, and the heat and water produced by the fungi can induce a self-accelerating heating process that can create hot spots in grain bulk, thereby accelerating the deterioration of grain quality, ultimately resulting in significant losses in grain quality and quantity [9, 10]. The recent studies showing the structure of maize kernels is damaged during mechanical harvesting, transportation, and loading, making them more susceptible to damage from fungi and insect [11, 12].
Comment 2: How the model described by equation 2 was obtained? Which statistical methods were used? What was confidence level? Was all the factors included in the model significant? Which of the factors have the highest influence on the temperature prediction? Are all of the constants of the model presented in the table 1 significant?
Response: Thank you very much for your careful reminder and valuable advice. According to the strong coupling relationship between temperature and humidity, the development process of HTA is related to time, hot spots temperature, relative humidity, and fungal respiration heat. Regression analysis and data fitting methods are used to establish a prediction model for HTA. HTA data were analyzed using the one-way analysis of variance (ANOVA) followed by Tukey’s post hoc mean separation test in SPSS version 22.0, and the results showed p<0.05, which is considered statistically significant.
The development of HTA is mainly due to the heat released by fungal respiration. During fungal respiration, the concentration of carbon dioxide, temperature, and relative humidity all dynamically change over time. Therefore, when establishing the equation, all these factors were comprehensively considered. Because fungal respiration releases a large amount of heat, and the resulting increase in grain bulk temperature accelerates fungal development, the temperature rise at the hot spots has a significant impact on HTA, which can be indirectly reflected by the parameter size of the Ths item. Table 1 provides the parameters for each item. Although the parameters containing the carbon dioxide concentration item are small, it is not recommended to ignore each item in Table 1 based on the behavior of fungal respiratory heat.
Anyway, this is our first exploration of the relationship between local hot spots development and multiple physical factors. We are also conducting local mold tests on maize bulk with different moisture contents using the same experimental equipment. At the same time, we will conduct more in-depth research to verify the universality of the equation. Thank you again sincerely for your careful suggestions and professional guidance.
Comment 3: In the discussion section you could also consider the effect of the maize type and fungal species on the hot spot formation.
Response: Thank you very much for your careful reminder and valuable advice. I apologize for not fully considering a more reasonable experimental plan. In this study, we only considered one maize type, and only commissioned testing institutions to conduct fungal spore number testing in fungal testing. Please forgive our lack of comparison on the relationship between maize type, fungal species, and hot spots formation. Your opinion is very inspiring for our future research. And we will consider this issue as part of our future research work. Thank you again sincerely for your careful suggestions and professional guidance.
Page 13, Lines 439-440:
The effect of the maize type and fungal species on the hot spot formation.
If you and reviewers have any other questions, please do not hesitate to contact us as soon as possible. We thank you and reviewers again for your patience, help and constant attention to our manuscript.
Sincerely yours,
Guixiang Chen
cgx@haut.edu.cn
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report
Comments and Suggestions for Authors
Dear Authors,
thank you very much for provided changes. Please include the response for my comment 2 in the text of the manuscript.
Comment 2: How the model described by equation 2 was obtained? Which statistical methods were used? What was confidence level? Was all the factors included in the model significant? Which of the factors have the highest influence on the temperature prediction? Are all of the constants of the model presented in the table 1 significant?
Response: Thank you very much for your careful reminder and valuable advice. According to the strong coupling relationship between temperature and humidity, the development process of HTA is related to time, hot spots temperature, relative humidity, and fungal respiration heat. Regression analysis and data fitting methods are used to establish a prediction model for HTA. HTA data were analyzed using the one-way analysis of variance (ANOVA) followed by Tukey’s post hoc mean separation test in SPSS version 22.0, and the results showed p<0.05, which is considered statistically significant.
The development of HTA is mainly due to the heat released by fungal respiration. During fungal respiration, the concentration of carbon dioxide, temperature, and relative humidity all dynamically change over time. Therefore, when establishing the equation, all these factors were comprehensively considered. Because fungal respiration releases a large amount of heat, and the resulting increase in grain bulk temperature accelerates fungal development, the temperature rise at the hot spots has a significant impact on HTA, which can be indirectly reflected by the parameter size of the Ths item. Table 1 provides the parameters for each item. Although the parameters containing the carbon dioxide concentration item are small, it is not recommended to ignore each item in Table 1 based on the behavior of fungal respiratory heat.
Anyway, this is our first exploration of the relationship between local hot spots development and multiple physical factors. We are also conducting local mold tests on maize bulk with different moisture contents using the same experimental equipment. At the same time, we will conduct more in-depth research to verify the universality of the equation. Thank you again sincerely for your careful suggestions and professional guidance.
Author Response
Comment 1: Please include the response for my comment 2 in the text of the manuscript.
Response: Thank you very much for your careful reminder and valuable advice. We have incorporated the content of our previous response into the manuscript based on your suggestion. Thank you again sincerely for your careful suggestions and professional guidance.
Page 10, Lines 321-325:
The HTA changes in maize bulk caused by fungal development are influenced by the temperature, relative humidity, CO2 concentration, and storage time at the hotspot location. Considering the strong coupling relationship between temperature and humidity, the following HTA prediction model was developed using regression analysis and data fitting methods:
Page 10, Lines 336-340:
The HTA data were analyzed using the one-way analysis of variance (ANOVA) followed by Tukey’s post hoc mean separation test, and the results showed p<0.05, which is considered statistically significant, and the analysis results indicate that the temperature rise at the hot spots has a significant effect on HTA.
Author Response File: Author Response.pdf
