Effects of climate change on the aeration of stored beans in Minas Gerais State, Brazil

Effects of climate change on the aeration of stored beans in Minas Gerais State, Brazil

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Research Paper

Effects of climate change on the aeration of stored beans in Minas Gerais State, Brazil Daniela C. Lopes*, Antonio Jose Steidle Neto ~ o Joa ~ o del-Rei, Campus Sete Lagoas, MG 424, Km 47, Sete Lagoas, 35701-970, Minas Gerais, Federal University of Sa Brazil

article info

The beneficial effects of the aeration of stored grains and legumes with ambient air can be

Article history:

affected by changes in climate causing disorders in air temperature and relative humidity

Received 27 March 2019

that directly affect the control strategies. The impacts of the climate change on the bean

Received in revised form

aeration in 11 mesoregions of Minas Gerais State (Brazil) were evaluated. For this, 132

1 August 2019

simulation scenarios were analysed, including simulations of three bean harvests using

Accepted 8 October 2019

measured climatic conditions, and three possible projections, representing low, intermediate and high radiative forcing levels. Based on the simulation profiles, total aeration time, grain cooling, and electrical energy consumption during bean aeration were calculated.

Keywords:

Results were strongly affected by the weather patterns of each mesoregion and by the

Stored grain

harvest periods of the crop. Projected climate changes tended to reduce the cooling po-

Global warming

tential, while increasing fan operation time and electrical energy requirement when

Grain quality

aerating common beans in Minas Gerais State. The Jequitinhonha and Mucuri valleys and the North and Northwest mesoregions were predicted as no longer having suitable aeration potential since they were the most impacted by climate changes. Chilling aeration is recommended when aerating bean in these mesoregions even with the present climate and this must be intensified when considering the climate changes. In the other mesoregions, aeration with ambient air is currently suitable and this can remain viable even with the projected climate changes, but this is with the proviso that good storage practices are followed and efficient control strategies are applied. © 2019 IAgrE. Published by Elsevier Ltd. All rights reserved.

1.

Introduction

The aeration of grains and legumes is considered one of the safest, most economic and efficient preventive practices in the postharvest sector (Serna-Saldivar & Garcı´a-Lara, 2015). This technology is used to modify the bulk microclimate during storage by insufflating cool and dry air into the grain bulk. By

* Corresponding author. Fax: þ55 31 3775 5500. E-mail address: [email protected] (D.C. Lopes). https://doi.org/10.1016/j.biosystemseng.2019.10.010 1537-5110/© 2019 IAgrE. Published by Elsevier Ltd. All rights reserved.

using aeration to maintain grain temperatures and moisture contents at safe level, harmful or damaging organisms are reduced or eliminated (Steidle Neto & Lopes, 2015). Grain aeration can be performed with either chilled or ambient air, the latter being dominant in commercial systems. Despite the shortage of sufficient cool air in some regions and/or some times of the year, the efficacy of ambient

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air aeration is proven (Edde, 2012; Nawi, Chen, & Zare, 2010). However, the beneficial effects of this technique tend to be affected by the climate changes, since modifications in air temperature and relative humidity directly impact on control strategies, demanding research on the possible changes in grain and legume aeration required for different geographical regions and seasons. Moses, Jayas, and Alagusundaram (2015) noted that changing seasonal and geographical climatic patterns would promote favourable conditions for the growth and multiplication of different biotic factors which are detrimental to safe storage. These authors also commented that in the context of climate change, damp winters and improper aeration would tend to amplify the problems resulting from more rapid increases in grain temperature, thus developing more favourable conditions for grain deterioration. There is a consensus that a large fraction of the detected global warming is attributed to anthropogenic carbon dioxide emissions (Hoegh-Guldberg et al., 2018). The natural carbon cycle has been perturbed mainly from fossil fuel combustion, greenhouse gases, land use changes, aerosols and their precursors. Global warming is likely to reach 1.5  C between 2030 and 2052 if it continues to increase at its current rate, and to limit this CO2 emissions should be reduced by about 25% by 2030 (IPCC, 2018). The carbon dioxide data, measured as the mole fraction in dry air on Mauna Loa (Hawaii), constitute the longest record of direct measurements of CO2 in the atmosphere. The values have been observed from December 1958 to February 2019 and values have ranged from 314.67 to 411.75 ppm (NOAA, 2019). According to IPCC (2014), the impacts associated with the projected atmospheric CO2 concentrations >450 ppm are likely to be associated with increased coral bleaching, rises in sea levels, and increased cyclone intensity, among other effects. Chou et al. (2014) simulated the climate change over South America considering three periods of time (2011e2040; 2041e2070 and 2071e2100), and they reported that in Central and Southeast Brazil major warming is likely to occur. Indicators also showed that in Southeast Brazil there is likely to be a decrease in annual rainfall and a reduction in relative humidity, making this region drier. Minas Gerais State, in Southeast Brazil, has a variety of climatic conditions, from semi-arid to humid (Leite, Silva, & van Ittersum, 2014). Furthermore, the state is the largest producer of coffee and the second largest producer of common beans, also producing soybean, sorghum, wheat, and maize (Conab, 2018; Lehner et al., 2015). Thus, using the above, this study was carried out to evaluate the predicted impact of climate change on the conditions required for the aeration of common beans held in storage in the 11 mesoregions of Minas Gerais State, Brazil.

2.

Methodology

Simulations were carried out by using software specifically developed for this purpose, written in Pascal programming language and based on the well-established model proposed by Thorpe (2001) and validated by Lopes, Steidle Neto, and Vasco Ju´nior (2015). The software allows simulating the aeration process under variable air conditions and also

considers different control strategies for different grain types (Lopes, Martins, Melo, & Monteiro, 2006). In this study, the software was set to simulate the aeration of common beans controlled by the Zephyrus strategy, which is a new and simple aeration controller based on the prediction of air speeds and changes of temperature and moisture while air is passed through a grain bulk. This work focused on common beans (Phaseolus vulgaris) because the studied region is one of the major producers and consumers of this legume, which is one of the main components of human diets. Additionally, it is one of the agricultural products which is predicted to increase in yield (around 45% between 2020 and 2050) due to the climatic change (Costa et al., 2009). The main equations of the Thorpe model were coupled and solved by using the finite difference numerical method. Psychrometric relationships and equilibrium models were also required during simulations. The grain bulk was divided into layers in the direction of the airflow. The grain moisture contents and temperatures were calculated after each time interval (3600 s) for each layer in an iterative way, considering the control strategy conditions and fan status (on or off). Simulation input data were the diameter of the silo (10 m), the height of grain bulk (8.5 m), the grain type (beans), the specific airflow rate (6 m3 h1 t1), the local atmospheric pressure, and a file with air temperatures and relative humidities along the analysed period. Data of ambient dry bulb temperature and relative humidity for the studied locations were obtained from Brazilian National Institute of Meteorology (Inmet, 2018). It consisted of a dataset covering five years (2012e2017) collected hourly. A consistency analysis was performed on the meteorological data with electronic spreadsheet functions to remove all inconsistent values. Additionally, visual analysis of graphs relating the variables to time complemented the data evaluation. Temperature and humidity gaps of 1e3 h were filled using the mean values from before and after. Finally, for each day and hour, the five-year periods were averaged to produce one 12-month series of hourly temperature and relative humidity values, and the model equations were applied iteratively considering their variations. The five-year average was compiled to ensure representative data, detect spatial/temporal changes that have occurred over the time and treat unexpected values in the datasets. It also provided better context on the changes to climate within each mesoregion than data from a single year. It was assumed that beans were stored for one year after each harvest with aeration processes starting from the middle of summer (first harvest: January), late fall or autumn (second harvest: May), and early spring (third harvest: September). Figure 1 presents the various mesoregions of Minas Gerais State considered during simulations. They were selected based on the divisions proposed by the Brazilian Institute of Geography and Statistics (IBGE, 2018). Each mesoregion was represented by a city selected based on its bean production (Conab, 2018), as well as on the availability of weather data (Inmet, 2018). Figure 1 also shows the atmospheric pressure, € ppen's climate classification, and the geographical cothe Ko ordinates for each studied city. € ppen's classification, Aw climate is According to the Ko ^ ngulo Mineiro and Alto predominant in a wide range of Tria Paranaı´ba, Jequitinhonha and Mucuri valleys, North and

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Fig. 1 e Mesoregions of Minas Gerais State, Brazil, used for simulating the effects of climate changes on bean aeration potential. Northwest mesoregions and is characterised as tropical with a dry winter. The other mesoregions are predominantly classified as Cwa climate (humid subtropical), with dry winter and hot summer (Alvares, Stape, Sentelhas, Gonc¸alves, &  Ju´nior, Carvalho, Silva, Alves, 2012). Sparovek, 2013; Sa For each mesoregion and bean harvest, the measured climatic conditions and three representative concentration pathways (RCP) were simulated. Each RCP represented different changing projections in mean temperatures, totalling 132 simulation scenarios. According to IPCC (2014), each RCP provides spatially resolved data sets of land use change and sector-based emissions of air pollutants, specifying annual greenhouse gas concentrations and anthropogenic emissions up to 2100. The RPC2.6 includes a climate changing mitigation scenario, leading to a very low radiative forcing level. The stabilisation scenario RCP4.5 represents an intermediate radiative forcing level, while the RCP8.5 scenario projects very high greenhouse gas and anthropogenic emissions. The different levels of radiative forcing of the atmosphere are relative to preindustrial levels and are expressed in units of W m2. During simulations, projected increases in air temperatures were added to the actual temperatures registered in the

datasets. As reported by IPCC (2014), these projections were calculated by the Working Group on Coupled Modelling (CMIP5), based on a multi-model ensemble, which was composed by more than 50 mathematical models relating CO2 concentrations to climate effects. The CMIP5 model output is freely available and has been successfully used by a number of scientists to perform different studies about the global  ntano & Penalba, 2018), food prowarming effects on soil (Pa duction (Stuecker, Tigchelaar, & Kantar, 2018), different ecosystems (Woodworth-Jefcoats, Polovina, Drazen, 2017), among others. Changes in relative humidity due to the temperature increases were estimated using psychrometric equations, considering the air heating process (Lopes et al., 2015). Following the projections presented by IPCC (2014) for the year 2050 and the Minas Gerais State (Southeast South America), RCP's 2.6, 4.5 and 8.5 corresponded to average temperature increments of 0.8, 1.3 and 1.9  C, respectively. In all simulations it was considered that beans were stored clean, dry (at 13% w.b.) and at a uniform temperature (35  C). For each simulated scenario, the bean temperature and moisture content profiles during the aeration period were generated, as well as the aeration air temperature and relative

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humidity profiles and the fan operation profile. Based on this information, the total aeration time, the bean temperature drops, and the electrical energy consumption for bean aeration in each mesoregion and storage period were calculated. Simulated data were submitted to variance analysis and averages compared by the F and ScotteKnott tests (p < 0.05) through SISVAR software (Ferreira, 2011).

3.

Results and discussion

Comparison of the effects of climate changes in the different mesoregions of Minas Gerais State (Brazil) was based on the

ability to minimise the potential for spoilage, fungal activity, and insect development. These are some of the parameters used to define safe storage conditions and they strongly depend on grain moisture content and temperature. There is a common understanding that increases in moisture content decrease germination, as well as increase microflora growth (Mohapatra, Kumar, Kotwaliwale, & Singh, 2017; Navarro, 2012; Weinberg et al., 2008). However, high temperatures can accelerate respiratory process, mite, fungi and insect, interfering in dry matter loss and increasing the possibility of product contamination (Morales-Quiros et al., 2016; Serna-Saldivar & Garcı´a-Lara, 2015; Taruvinga, Mejia, & Alvarez, 2014). Additionally, aeration time and electrical energy consumption were

Fig. 2 e Examples of moisture content profiles obtained during the simulations.

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compared, since these are important variables when analysing the costs of aeration (Steidle Neto & Lopes, 2015). In general, safe moisture contents were successfully maintained both for measured and projected climates for all mesoregions and storage periods, with an average decrease of 0.8% w.b., as exemplified by the profiles showed in Fig. 2(a) for the South/Southwest mesoregion and storage period from January to December (after the first harvest). An exception to this was the North mesoregion where an average decrease of 3.4% w.b. was predicted during the aeration period for all simulated climate scenarios, as showed in Fig. 2(b), also considering the storage period from January to December. Bean storage after the third harvest also resulted in a predicted average decrease of 2.8% w.b. in Northwest mesoregion, considering the measured climate and the changing projections. In the Metropolitan mesoregion, a decrease of 2.5% w.b. was predicted when storing beans after third harvest when simulating RCP's 4.5 and 8.5. The simulated initial moisture contents were 13% w.b., corresponding to an equilibrium relative humidity of 70% when considering temperatures around 25  C. As reported by Weinberg et al. (2008), under these conditions the development of microorganisms can be efficiently prevented. Steidle Neto and Lopes (2015) confirmed that changes from 0.2 to 1.0% w.b. can be expected during aeration since the relative humidity of the insufflated air is different than the interstitial grain bulk relative humidity, resulting in heat and moisture transfers. Commonly, aeration effects on grain moisture content are limited to product located closed to the air intake, given that the temperature front travels rapidly when compared to with the moisture front. However, major moisture content changes must be controlled, since over drying of product causes internal stresses and reduces the bulk weight, lowering market value. Climate changes tended to increase the aeration times in all studied regions, without improving grain cooling and with the optimistic projections resulting in minor differences when compared with the measured climate (Table 1). Both RCP's 2.6 and 4.5 presented mean aeration times statistically equal, but significantly different from actual climate (mean difference of 12.3%) and RCP 8.5 (mean difference of 8.8%). The high mean

aeration times were influenced mainly from the Jequitinhonha and Mucuri Valleys, as well as by North and Northwest mesoregions, which required longer fan operations in all studied storage periods and climate projections, not reaching effective grain cooling and resulting in lower aeration potentials. Also, relatively high standard deviations were observed, evidencing the large variability in aeration times found in the different mesoregions of Minas Gerais State. When mesoregions were evaluated separately, climate change was found to significantly affected the aeration times in the Jequitinhonha and Mucuri valleys, West, and Central mesoregions. Jequitinhonha and Mucuri valleys, which also presented the highest standard deviation, was the mesoregion most impacted by the projections of intermediate radiative forcing level and of very high greenhouse gas and anthropogenic emissions. The West region was equally affected by the three climate changing projections, but the Central region was only affected by the pessimistic projection (RCP 8.5). The South/Southwest, Zona da Mata and the Rio Doce valley mesoregions were the less impacted when considering the variable of aeration time and the global warming. They also presented the shortest aeration times. The stability observed in these regions was also demonstrated by their low standard deviations when evaluating the climate projections. The variations in weather from region to region, as well as among cropping seasons, appeared as the main variable affecting the operation of aeration in this study. The large average numbers of aeration hours were mainly affected by the third bean harvest, which occurs from early Spring to middle Summer, and when suitable aeration hours for cooling grain in most of studied mesoregions are limited. Thus, as also noted by Navarro and Noyes (2001, p. 672), aeration was performed mainly to equalise bean temperatures progressively as decreases in ambient air temperatures and safe relative humidities were verified. Probably, this contributed to increase the mean aeration times. This was more apparent in the mesoregions where dry season is more pronounced and ambient temperatures are higher, such as North, Jequitinho^ ngulo Mineiro and nha and Mucuri valleys, Northwest, Tria Alto Paranaı´ba, West and Metropolitan mesoregions.

Table 1 e Comparison results of the studied mesoregions, current climate conditions, and the three representative concentration pathways for simulated aeration times (h). Mesoregion

Current

RCP 2.6

RCP 4.5

RCP 8.5

Mean

St.Dev.

North Jequtinhonha and Mucuri valleys Northwest ^ ngulo Mineiro and Alto Paranaı´ba Tria West Zona da Mata Central Metropolitan Rio Doce valley Campo das Vertentes South/Southwest Mean St.Dev.

2517 aA 1473 bA 1363bA 1260 bA 914 cA 529 dA 538 dA 963 cA 551 dA 508 dA 484 dA 1010 A 622.69

2674 aA 1792 bB 1470 cA 1264 cA 1211 dB 535 eA 538 eA 1084 dA 554 eA 590 eA 490 eA 1116 B 685.36

2699 aA 2025 bC 1471 cA 1277 cA 1219 cB 536 dA 558 dA 1213 cA 557 dA 651 dA 499 eA 1153 B 710.25

2781 aA 2245 bC 1625 cA 1344 dA 1286 dB 539 eA 758 eB 1311 dA 569 eA 787 eA 503 eA 1244 C 739.74

2668 a 1884 b 1482 c 1287 d 1158 d 535 e 598 e 1143 d 558 e 634 e 494 e

110.40 330.45 107.82 39.18 165.78 4.12 107.08 151.66 7.89 117.63 8.60

Means followed by the same lower case letters in a column and capital letters on the lines do not differ significantly using the ScotteKnott test (p < 0.05).

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Table 2 e Comparison results of the studied mesoregions, current climate conditions, and the three Representative Concentration Pathways for electrical energy requirements (kW h t¡1  C¡1). Mesoregion North Jequtinhonha and Mucuri valleys Northwest ^ ngulo Mineiro and Alto Paranaı´ba Tria West Zona da Mata Central Metropolitan Rio Doce valley Campo das Vertentes South/Southwest Mean Std.Dev.

Current 0.59 0.46 0.27 0.17 0.12 0.06 0.06 0.12 0.07 0.06 0.05 0.18 0.18

aA aA bA bA bA bA bA bA bA bA bA A

RCP 2.6

RCP 4.5

RCP 8.5

Mean

Std. Dev.

0.78 aB 0.62 aB 0.33 bA 0.20 bA 0.20 bA 0.06 cA 0.06 cA 0.17 bA 0.07 cA 0.07 cA 0.05 cA 0.24 B 0.24

0.90 0.76 0.36 0.20 0.23 0.06 0.06 0.23 0.08 0.08 0.05 0.27 0.29

1.12 aD 1.08 aC 0.42 bA 0.21 cA 0.25 cA 0.06 dA 0.1 dB 0.26 cA 0.08 dA 0.10 dA 0.06 dA. 0.34 D 0.40

0.85 a 0.73 b 0.34 c 0.20 d 0.20 d 0.06 e 0.07 c 0.20 d 0.08 c 0.08 c 0.05 c

0.22 0.26 0.06 0.02 0.06 0.01 0.02 0.06 0.01 0.02 0.01

aC aB bA bA bA cA cA bA cA cA cA C

Means followed by the same lower case letters in a column and capital letters on the lines do not differ significantly using the ScotteKnott test (p < 0.05).

Fig. 3 e Average final bean temperature drops after aeration in the mesoregions of Minas Gerais State, Brazil, simulated for actual climate, RCP 2.6, RCP 4.5 and RCP 8.5. Averages followed by different lower case letters indicate significant differences among regions, while capital letters indicate significant differences among climate projections by the ScotteKnott test (p < 0.05).

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Fig. 4 e Grain temperature profiles of the most affected mesoregions by climate changes considering storage from May to September.

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With regard to mean electrical energy requirements, which depend on aeration time and grain temperature drop, measured climate and all the simulated projections differed statistically among themselves (Table 2). Furthermore, all standard deviations were equal or greater than the mean, evidencing the high level of variability among the studied mesoregions. Generally, increasing the radiative forcing levels the electrical energy requirements tend to be higher. Exceptions were the Zona da Mata, Rio Doce valley, South/Southwest and Central mesoregions, where this variable did not change with the predicted global warming. The electrical energy requirement for grain aeration in Central region was significantly influenced only by the RCP 8.5, while the Jequitinhonha and Mucuri valleys resulted in significantly larger electrical energy requirements for this projection, followed by RCP's 2.6 and 4.5, which did not significantly differ among themselves, and by the measured climate. However, the mesoregion most affected by climate changes regarding electrical energy requirements was the North of Minas Gerais State, which demonstrated significant differences among all climate scenarios, with those with higher radiative forcing levels resulting in larger electrical energy consumptions. North mesoregion, as well as Jequitinhonha and Mucuri valleys, were the mesoregions with the highest standard deviations, and consequently large variability in electrical energy requirements, when the different climate projections were considered. The same mesoregions that were little affected by climate change when considering aeration time were also less impacted when evaluating the electrical energy requirements, presenting the lowest values for this variable. When evaluating average grain temperature drop following aeration, significant differences were identified between the measured climate (11.7  C), RCPs 2.6 and 4.5 (11.0 and 10.9  C), and RCP 8.5 (10.5  C), indicating that the global warming is predicted to further limit aeration with ambient air in Minas Gerais State. Figure 3 shows the average final bean temperature drop following aeration, considering the studied mesoregions of Minas Gerais State using measured climate and the three RCPs. Considering the simulated bean temperature drop for measured climate, large differences were observed, mainly between the South/Southwest mesoregion and the Vale do Jequitinhonha and Mucury valleys. The mesoregions that required lower electrical energy and aeration time, were also predicted to reach the most effective grain cooling. These results were strongly affected by the weather patterns of each mesoregion and by the harvest periods of beans in Minas Gerais State. The aeration with ambient air in Jequitinhonha and Mucuri valleys, North, Northwest, Rio Doce valley, and ^ ngulo Mineiro did not reach the temperatures recomTria mended for safe storage (~21  C). As shown by Taruvinga et al. (2014) and Mohapatra et al. (2017), stored product insect development is significantly suppressed below 21  C and generally stops below 16  C. Low temperatures also minimise the risks associated with grain spoiling and dry matter losses. For these mesoregions it is recommended that the economic feasibility of using chilling aeration is explored. Another possibility is to build grain storages only in favourable mesoregions of Minas Gerais State, but in this case an economic analysis including grain transportation, labour and

management costs is required. Despite the high investment required by this technology, it generally results in less aeration time and fan operation. It also shows a greater potential for reducing grain temperatures independent of ambient conditions. Considering the climate projections, a trend for decreasing of aeration potential was noted for all mesoregions studied as ^ ngulo Mineiro and Zona radiative forcing levels increased. Tria da Mata were the less impacted mesoregions, resulting in temperature drop reductions for the RCP 8.5 of 3.4 and 3.1%, respectively. There were no differences in the simulated bean cooling when comparing measured climate with RCP's 2.6 and ^ ngulo Mineiro, while decreases of 0.8 and 1.5% 4.5 in the Tria were verified in the Zona da Mata. The most affected mesoregion regarding aeration potential was the North, reaching simulated bean temperature drop 20, 33 and 47% smaller than those of actual climate when simulating RCP's 2.6, 4.5 and 8.5, respectively. For Northwest the reductions were 16, 23 and 32%, while for Jequitinhonha and Mucuri valleys they were 8, 16 and 25%. Predicted bean cooling in the Metropolitan mesoregion also tended to be prejudiced by global warming, resulting in temperature drop decreases of 7, 12 and 17% for the three simulated climate projections. The other mesoregions presented temperature drop reductions of 3, 5 and 7% on average for RCP's 2.6, 4.5 and 8.5, respectively. Average final bean temperatures ranged from 20.9 to 24.5  C when simulating the climate projection changes in most of the mesoregions of Minas Gerais State. Exceptions were the mesoregions of Jequitinhonha and Mucuri valleys, North and Northwest, where the probability of insect infestation was increased because aeration with ambient air is not capable of properly cooling the bulk. In these mesoregions, the simulated final bean temperatures when considering the global warming were between 26.8 and 30.1  C. At these locations applying chilling aeration tended to be the more appropriated remedy for global warming due to the high aeration time required and the limited aeration potential using ambient air. According to Morales-Quiros et al. (2016) and Navarro (2012), chilling is becoming more popular globally due to its advantages in situations where ambient air aeration is not sufficient to properly cool the grain bulk and when the system features make its use economically feasible. In the other mesoregions, it appears possible to store grain safely for some time even with the climate changes, if the storage structure is well sealed, the grain bulk is stored free of insects or with minimal insect presence and the bean bulk is stored clean and dry. In these mesoregions is also very important maintaining low temperature gradients throughout the bulk, preferably <3  C. Navarro and Noyes (2001, p. 672) affirmed that this procedure prevents moisture migration, which causes moisture to slowly accumulate in the coldest grain layers and can contribute for fungal development. Figure 4 presents an example of temperature profile, simulated for the most affected mesoregions by climate changes, considering the storage from May to September (after the second harvest). According to the weather pattern in Brazil, these profiles show the storage period from late autumn (May) to early spring (September), which allowed an initial rapid cooling of grain in all mesoregions and for all climate projections, with global warming scenarios resulting

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in a slight reduction in the cooling potentials. These effects were more evident as air temperatures rise, from July to September. During this period, the grain bulk tends to warm, and aeration is applied in order to maintain low grain temperature gradients, cooling the product whenever possible. As mentioned by Lopes et al. (2015) and Navarro (2012), this is an important aspect in tropical and subtropical regions, where the feasibility of using ambient aeration to cool grain is limited and the main aeration objective becomes the equalisation of temperature throughout the grain bulk. Aeration with natural air is influenced by many factors, including harvest time, initial bulk temperature and moisture contents, as well as the weather patterns of the different regions. Simulations carried out in this work showed that for the three bean harvests, a similar behaviour was verified. That is, a slight reduction in the cooling potential during the coldest months and a trend for greater grain warming during the spring and summer seasons as radiative forcing levels increase. This will probably be more evident as initial grain moisture contents differ from the recommended safe levels, as well as when initial grain temperatures are higher. Simulations also allowed a spatial comparison of the climate change effects considering the different weather patterns of the studied mesoregions. Results confirmed that global warming tend to affect each one of them differently. But other studies, using data from different world regions, are important and recommended as future works, in order to better understanding the effects of the climate changes in the grain/ legume storage sector. Other important observation is regarding the control strategy. In this study, simulations were carried out according to an aeration control strategy based on predictions of speeds and changes of temperature and moisture fronts while air is passed through a grain bulk. This kind of controller automatically adjusts its set points, accommodating local weather conditions and optimizing the aeration process, independently of the geographic region or season. Thus, if a less efficient control strategy is applied, the aeration potentials presented in this study will tend to worsen. Additionally, the increasing CO2 concentrations tend to affect grain quality, leading to more postharvest losses. According to Moses et al. (2015), elevated levels of CO2 and temperature can significantly stimulate the production of some mycotoxins, which are extremely toxic, carcinogenic and immunosuppressive. Other effects associated with higher radiative forcing are reductions in the germination capacity of seeds and in cooking quality of grain. Chakraborty and Newton (2011) reported that increased anthropogenic CO2 emissions and warming tend to lower some micronutrients of grain during storage, as well as their protein contents. Nnaji and Brooks (2016) affirmed that climate changes will also influence insects and mites associated with stored products, forcing their migration toward to different regions, as well as changing their developmental cycles. Finally, Stathers, Lamboll, and Mvumi (2013) noted that changes on CO2 concentrations can increase moisture migration and condensation processes, resulting in more hotspots in grain bulk. The reduction on the efficacy of some grain protectants and the increased fire risk associated with matured grain are also highlighted.

4.

163

Conclusions

Results of simulations of aerating common beans in Minas Gerais State showed that predicted climate changes caused by increased greenhouse gas and anthropogenic emissions will tend to increase fan operating time and electrical energy requirements, while reducing grain temperature drop, mainly because of the changing projections representing the intermediate and high radiative forcing levels. The most affected mesoregions predicted were Jequitinhinha and Mucuri valleys, North and Northwest. They do not have suitable aeration potential and predicted bean temperature drops considering the global warming were from 8 to 47% smaller than those currently observed. The less impacted ^ ngulo Mineiro and Zona da Mata, mesoregions were Tria which appear able to maintain cooling effects, process times and energy requirements for bean aeration even with the predicted climate changes. The different projected radiative levels should have little effect on the Rio Doce valley, West, Campo das Vertentes, Central and South/ Southwest, mesoregions but they could reduce the aeration potential in the Metropolitan mesoregion. Chilling aeration is recommended when aerating beans in the Jequitinhinha and Mucuri valleys, North and Northwest mesoregions considering the present climate and future climate changes. In the other mesoregions aeration with ambient air is currently suitable and this should remain the case provided that good storage practices are followed and efficient control strategies are applied. The results of this study were strongly affected by the weather patterns of each mesoregion, and by the harvest periods of beans in Minas Gerais State. Thus, studies using data from different world regions are recommended for future work in order to understand better the effects of the global warming on the grain/ legume storage sector.

Declaration of Competing Interest The paper entitled “Economic and technical feasibility of grain chilling in Brazil” has no conflict of interest.

Acknowledgements The authors would like to acknowledge the FAPEMIG/Brazil (grant number CAG - APQ-01389-15) for the financial support.

references

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