Impact of Delayed Cooling and Precooling Parameters on Physical Properties of Potatoes: A Storage Study

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Impact of Delayed Cooling and Precooling Parameters on Physical Properties of Potatoes: A Storage Study

https://doi.org/10.21203/rs.3.rs-3129967/v1

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Field Heat is one of the significant factors contributing to post-harvest losses of various agricultural produce. Precooling is necessary to counter the field heat, maintain the quality and increase the shelf life of the farm produce. Potato was chosen as it is one of the most essential staple products worldwide and can be consumed in various forms. This study was conducted to determine the impact of field heat and precooling parameters on potatoes' quality and shelf life. The study constitutes two components. The first component aims to understand the implications of field heat on the quality of the produce by gradually increasing the time delay between harvest and precooling from 0h to 64h. As the time of exposure to field heat increased, the quality of potatoes seemed to decrease gradually. The second component was conducted to understand the effect of precooling variables (Temperature & Relative Humidity) on the quality of produce by varying temperature between 6°C to 10°C and relative humidity between 87–95%. A comparison was made between precooled and not precooled potatoes to understand the effect of precooling on the overall quality of the potatoes. The residual values obtained from comparison revealed that the precooled samples had significantly less variation from fresh samples than those that were not precooled.

Potato

Precooling

Field Heat

Moisture Content

Texture

Potato, inarguably, is one of the most important staple foods in today’s world. And so it has an essential place in the food processing industry as well. It is believed that the vegetable originated in the Andes, South America, and spread throughout the world. In India, potato production rose from 3.65 crore tonnes in 2010 to 5.02 crore tonnes in 2019 (Faostat), and worldwide, the production of potatoes continues to proliferate. FAO also estimates that it is consumed by more than a billion people worldwide every year. The state of West Bengal, where this experiment was conducted, was and continues to remain a significant crop producer. The moderate demand growth scenario estimates that the demand for potatoes in India will almost double, reaching numbers as high as 6.8 crore tonnes by 2030 (Scott et al., 2019).

It was determined that during the post-harvest period, the majority of the losses occur during harvesting, followed by grading and packaging (Raghuvanshi, 2018). A potato tuber, after harvest, is capable of respiration, transpiration, and reproduction. Due to this, potato needs to improve in the field and at various stages of marketing. The heat that has to be removed in order to preserve the quality of the product then emanates from two primary sources: Field heat and respiration heat.

Field heat is defined as "the difference in temperature between the crop harvested and the optimal storage temperature of the product. "Hence the temperature management of any produce begins right at its harvest, in the field. It was recommended that the time between harvest and initial cooling must be reduced, and the produce ought to be protected from solar heat gain (Thompson, 2004).

Precooling is required for the rapid removal of the field heat present in the product immediately after harvest. Removing the field heat as quickly as possible is vital because even an hour delay at the field conditions of about 35◦C will lead to a shelf-life reduction of one day, even at optimal storage conditions (National Horticultural Board,2010). This is a critical step in reducing post-harvest losses, which is one of the most efficient ways to improve the livelihood of farmers (Yang, 2000).

The heterogeneity of product temperature is a significant factor in the storage life of the produce. Precooling presents the best opportunity to reduce this heterogeneity and promote batches of food with uniform quality, increasing storage efficiency (Mercier et al., 2019).

2.1. Precooling and Storage Conditions

The potatoes were harvested from a nearby farm and were immediately transported to the laboratory before being packed and placed in a precooling chamber. The potatoes were heated in a hot air oven at 35°C in order to simulate the field heat conditions West Midnapore district in West Bengal, India. After heating, the potatoes were precooled and transported to the cold storage facility operating at 2°C and 98% RH, where they were stored for 60 days.

This study was conducted in two parts: The first part of the study was to understand the impact of delay in placing the product in the precooling unit after harvest. This is done by varying the time delay between 0–64 hours while holding the precooling parameters constant.

The second part of the study was to understand the impact of precooling parameters on the shelf life and the quality of the potatoes. This was done by varying the precooling parameters of temperature (6°C − 10°C) and relative humidity (87% − 95%). A lower temperature than 6°C could spell damage as it leads to rapid cooling of the potato, which might cause a freeze injury, while a temperature higher than 10°C might not achieve the intended precooling effect. The relative humidity was similarly chosen in order to avoid extreme moisture loss or gain at the very beginning of the storage period in order to curb the loss of texture and microbial activity.

2.1. Weight loss

Weight loss is caused by respiration (which produces heat while breaking down the substances in the produce), evaporation of moisture through the surface, and the activity of pathogens (Misener & MacDonald, 1975). Studies show that weight loss roughly doubles for every 10°C rise in temperature (Pyke, 1981). Hence weight loss becomes an important factor in determining the quality of potatoes in storage. This was done by determining the difference between the sample weight prior to heating and after the storage period. Furthermore, the weight loss value is given as g per kg.

2.2. pH

pH is an important quality parameter and can be used to understand various enzymatic functions and other processes occurring at a cellular level (Pecherina et al., 2021). A representative sample was washed, peeled, and then ground in a juicer. pH was measured using a pH meter. After each measurement was taken, the probe was cleaned with distilled water and wiped with tissue paper in order to avoid errors in the subsequent measurement.

2.3. Total Soluble Solids (TSS) Content

Total Soluble Solids content is an essential indicator of quality as it is directly related to nutritional value and taste (Sanchez et al., 2020). A representative sample was washed, peeled, and then ground in a juicer. TSS was measured using a handheld refractometer (0–20 brix).

2.4. Texture Analysis

The study of mechanical properties like texture helps us understand the cultivar and the changes that occurred during the storage period (Bentini et al., 2009). The surface texture was potatoes was measured using a TA.XT plusC texture analyzer. The diameter of the probe was 10 mm, which was made of the material Derlin. The shear applied was 7 g with a compression of 70% and a force speed of 0.5 mm/s (Yu-mei et al., 2016).

2.5. Moisture Content

Moisture content is a vital factor in determining the potato texture, both raw and cooked, which then becomes a defining attribute for great mouthfeel and hence consumer acceptance (Gomez-Castillo et al., 2013). Moisture content was measured by oven drying by keeping the sample at 105°C for 24 hours according to AOAC official method, 1998.

2.6. Colour

Escuredo et al. (2018) demonstrated a significant correlation between the surface color of the potatoes and the antioxidant content. Vaitkevičienė N (2019) arrived at similar conclusions regarding the mineral content of potato peels. The surface color of the potato was measured using an NH310 portable colorimeter. ΔE, which depicts the deviation in L, a, and b of the sample from the standard (fresh) sample, was reported for this study.

$$ΔE= \sqrt{{(L-{L}_{s})}^{2}+ {(a-{a)}_{s}}^{2}+ {(b-{b)}_{s}}^{2}}$$

2.7. Statistical Analysis

Table 1

Levels of independent variables
Parameter			Levels
	-1		0		1
Temperature	6		8		10
Relative Humidity	87		91		95
Time Delay	0	4	8	16	32	64

The data was analyzed using the Factorial method. Stat-Ease 22.0.1 was used to perform the analysis.

Impact of Field Heat on Quality Parameters

As the time between harvest and cooling increased, the weight loss, pH, TSS, and color deviation from the fresh sample increased, and moisture content and texture decreased. These observations indicate a significant reduction in the quality of the product with an increase in the time delay between harvest and cooling. Because as the delay increases, the field heat absorption in the produce also increases, which causes damage at a cellular level. This damage is carried forward throughout the storage, impacting the quality and shelf life of the produce.

Impact of Precooling Parameters on the Quality of Potatoes During Storage

Table 3

Summary of Responses
Response	Name	Units	Minimum	Maximum	Mean	Std. Dev	Ratio
R1	Weight Loss	g	5	60	26.91	17.13	12
R2	Moisture Content	%	81.07	87.97	84.31	1.90	1.09
R3	Texture	g force	12934.6	15395.8	14207.12	682.96	1.19
R4	Color	-	13.39	26.96	22.17	3.56	2.01
R5	pH	-	5.88	6.68	6.38	0.2086	1.14
R6	TSS	°brix	5.4	7.9	6.54	0.8261	1.46

Table 4

Regression models developed for prediction of the response to precooling
Response	Regression Model	R²	Adj.R²	CV (%)
Weight loss (mg)	27.69 + 19.55A + 7.31B	0.973	0.965	11.98
MC (%db)	84.52 + 0.75A – 2.27B – 0.383AB	0.992	0.985	0.27
Texture (g)	14181.96–693.67A – 310.5B + 128.99AB	0.989	0.978	0.71
Color^2.5	2322.39–386.5A + 1068.3B	0.963	0.951	3.57
pH	6.36–0.266A + 0.106B	0.958	0.944	0.771
TSS (°brix)	6.52–0.9A – 0.48B	0.994	0.992	1.1

A – Temperature; B – Relative humidity;

The summary of the responses (weight loss, moisture content, texture, color, pH and TSS) has been given in Table 3 and the regression model analysis summary has been given in Table 4. The effect of each

Effect of process variables on weight loss:

The weight loss varied from 0g to 60g with increasing precooling temperature and relative humidity (Fig. 1). The weight loss in potatoes occurs mainly due to moisture loss and respiration and hence was significantly impacted by varying temperatures and RH. In potatoes, weight loss due to respiration is insignificant compared to the weight loss due to evaporation of moisture (Misener & MacDonald, 1975). A large vapor pressure deficit between the product's surface and the surrounding air could lead to an enhanced rate of moisture loss (Hamdami et al., 2004) from the product, leading to a higher weight loss during storage. Hence, precooling at higher relative humidity slows the moisture loss in the initial storage stage significantly, contributing to lesser weight loss.

Effect of process variables on moisture content:

The moisture content of the products varied from 82–87% (Fig. 2). The coefficients of the equation shows that the moisture content is negatively impacted by the temperature while positively impacted by the RH. The product with the highest moisture content was obtained at 6°C and 95% RH, while the lowest product with the lowest moisture content was obtained at 10°C and 87% RH. The moisture content of the potato significantly influences its thermal conductivity, which plays a vital role in modeling and optimizing processing methods like drying and rehydration. (Wang & Brennan, 1992). The developed model shows that precooling the potatoes at lower temperatures and higher RH prevents the loss of moisture content at earlier stages of storage, which is reflected in the observations taken after the storage period. Moreover, as the temperature of precooling increases and the RH of precooling decreases, it seems to increase the moisture loss throughout the storage period.

Effect of process variables on texture:

The texture of the produce varied from 12900 g to 15900 g (appx) (Fig. 3). Both precooling temperature and RH had a significantly positive impact on texture. The potatoes that were precooled at 10°C and 95% RH took the highest shear force for the probe to break through the surface, indicating a firmer texture and overall quality. Alvarez and Canet (1997) determined that precooling had a significant impact on the rheological properties of potatoes. An increase in mechanical strength was observed in potatoes that were precooled. The textural structure of potatoes is significantly dependent on physiological changes occurring at the level of tissues, especially on cell water (Brusewitz et al., 1989). Furthermore, as temperature and RH of precooling increase, the production of cell water due to respiration seems to be more than the loss of the same due to evaporation, thereby contributing to an increase in the mechanical strength of potatoes.

Effect of process variables on color:

The color of the potato surface varied from 13.4 to 26.9 (appx) (Fig. 4). From a consumer's point of view, skin color plays a vital role. Hence color is an essential parameter in understanding the quality of the product. The skin color of the potato gradually became darker as the storage time progressed (Mostofa et al., 2019). The higher deviation from the fresh sample could be due to a reduction in reflectance caused due internal structural changes in the cell (Zhang et al., 2018). The least deviation in color during storage was observed in potatoes that were precooled at 6°C and 95% RH. The lower precooling temperature and high RH preserve the moisture content, which was also observed in this study, leading to less change in skin color during storage.

Effect of process variables on pH:

The pH varied from 5.88 to 6.7 (Fig. 5). While the precooling temperature had a significantly positive impact on the pH, the precooling RH showed a significantly negative impact. The samples that were stored at a temperature of 10°C and RH of 87% had the highest pH value. The lower pH could indicate fungal growth in the potato, which causes fermentation and increases the overall acidity in the potato pulp (Oda et al., 2002). pH values of potatoes, in general, are expected to rise during storage (Paik, 2007; Khorramifar et al., 2022). Hence, a reduction in pH could indicate an increase in bacterial activity and a decrease in the overall quality of potatoes. The pH decreased with an increase in RH, and this could be attributed to an increase in microbial activity due to an increase in surrounding water activity. A combination of lower precooling temperature and lower precooling RH seems to maintain the pH of the sample throughout the storage period.

Effect of process variables on TSS:

The content of Total Soluble Solids varied from 5.4 brix to 7.9 brix (Fig. 6). TSS was significantly impacted by both temperature and relative humidity. The samples that were precooled at 10°C and 95% RH had the highest amount of TSS, while those stored at 6°C and 87% C had the least amount of TSS. The higher amount of TSS is generally associated with lower quality since it can indicate a higher rate of hydrolysis of starch to simple sugars (Sugri et al., 2017) hence displaying that precooling at the appropriate temperature and RH can have a significant impact on potato quality in storage.

Table 5

ANOVA for regression analysis of precooling parameters on the quality of potato after storage
Treatment Variable	F						P
	WL	MC	Texture	Color	pH	TSS	WL	MC	Texture	Color	pH	TSS
Temperature (°C) - A	179.68	48.42	272.22	61.68	126.92	777.6	< 0.0001	< 0.0001	< 0.0001	< 0.0001	< 0.0001	< 0.0001
RH (%) - B	24.84	505.33	56.53	254.13	20.72	187.1	< 0.0001	< 0.0001	< 0.0001	< 0.0001	0.0001	< 0.0001
AB		7.2	6.2					0.0092	0.0142

Comparative analysis of product quality post-storage

Table 6

Comparison of physical properties of potatoes, without and with precooling
Parameter	Control Sample	Precooling Sample	Residual
Weight Loss (g)	26	5	21
Moisture Content	84.02	81.2	2.82
Texture	12165.8	15395.8	3230
pH	6.23	6.68	0.45
TSS	6.6	5.4	1.2
Color	20.24	13.39	6.85

Table 7

Comparison of physical properties of potatoes, freshly harvested and stored after precooling
Parameter	Fresh Sample	Precooling Sample	Residual
Weight loss (g)	-	5	-
Moisture Content	83.97	81.2	2.77
Texture	12681.9	15395.8	2713.9
pH	6.51	6.68	0.17
TSS	5.3	5.4	0.1
Color	-	13.39	-

As can be seen from the Tables 6 & 7, the residual value between the control sample and the precooled sample is significantly higher than the value between the freshly harvested sample and the precooled sample. These tables give us an indication that not only does precooling helps preserve the quality of the potato, but it can significantly improve the texture. A comparison of residual values in Table 6 and Table 7 shows how precooling helps preserve the quality of potatoes during storage.

The study concludes that precooling is necessary for preserving the quality of potatoes during the storage period and could prove beneficial. The first part of the study demonstrates that with an increase in time delay, the rate of deterioration of the quality of potatoes during storage increases. The second part of the study shows that the precooling parameters play a significant role in maintaining the quality of the potatoes during storage. Precooling has a better impact on potatoes when compared with potatoes that were not precooled.

Competing interests

The authors have no competing interests to declare that are relevant to the content of this article.

Acknowledgements

The authors would like to thank the Physical Properties lab, Agricultural and Food Engineering Department, IIT Kharagpur, for instrumental facilities. Aphiya Amulya Palle additionally acknowledge the financial support of Ministry of Education (formerly, MHRD), Government of India.

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Table 2 is available in the Supplementary Files section.

Table2.docx

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Impact of Delayed Cooling and Precooling Parameters on Physical Properties of Potatoes: A Storage Study

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Abstract

Figures

1. Introduction

2. Materials and Methodology

2.1. Precooling and Storage Conditions

2.1. Weight loss

2.2. pH

2.3. Total Soluble Solids (TSS) Content

2.4. Texture Analysis

2.5. Moisture Content

2.6. Colour

2.7. Statistical Analysis

3. RESULTS AND DISCUSSION

Conclusions

Declarations

References

Table

Supplementary Files

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