Influence of nutritional components on colour, texture characteristics and sensory properties of cooked potatoes

ABSTRACT

The quality of cooked potato depends on its nutritional components. This study aimed to select suitable potato cultivars for cooking through correlation analysis of their nutritional composition and cooking characteristics. The nutritional components and sensory properties of 10 potatoes from the Xinjiang province were determined. Correlation analysis showed that protein and calcium, as well as the dietary fiber, iron, and phosphorus contents were significantly associated with the total colour difference (ΔE) and softening (p < .05). The umami and kokumi of potatoes after cooking were significantly correlated with isoleucine and tyrosine, as well as lysine, leucine, and isoleucine (p < .01). It could be deduced from the colour, texture characteristics and sensory properties that Longshu11 was suitable for processing mashed potato products, and that Jizhang12, Longshu10 and Heijingang were suitable for fresh-cut. The results provided new ideas and theoretical support for efficiently selecting suitable potato varieties for cooking and processing.

KEYWORDS:

• Potato
• nutritional component
• colour
• texture
• sensory properties
• correlation analysis

1. Introduction

Potato (Solanum tuberosum L.) is the fourth largest food crop after wheat, corn, and rice. Potatoes are widely grown, highly productive and nutritious. At present, the Chinese potato planting area and output are ranked first in the world (Zhou et al., 2019). Compared with other crops, potatoes have high-quality protein, a balanced amino acid composition and are rich in vitamins and minerals, while being low in fat and having few allergens (Bártová et al., 2015). Additionally, research revealed that potatoes’ nutritional qualities depend significantly on the variety (Motalebifard et al., 2013).

Potato cultivars differ in their nutritional value and makeup, which leads to significant differences in processing suitability. The success of introducing a new potato variety to the market depends on many variables, including the dry matter content (texture), yield (an economic factor), pest resistance, and consumer acceptance (Leighton et al., 2010). Potatoes, unlike the majority of vegetables, should not be consumed uncooked. Potatoes are processed in different ways, such as cooking, baking, and/or boiling (Silveira et al., 2020).

Cornacchia et al. (2011) observed the colour and overall appearance of four potatoes during storage to classify their fresh food suitability and found that “Safrane” received the highest appearance score during storage at both storage temperatures. Singh et al. (2005) screened several processed varieties of fries through potato physicochemical analysis. They found that potatoes with a higher dry matter and starch content, as well as a lower reducing sugar content, had more suitable texture properties as fries. The texture and sensory properties of potato change after thermal processing, which can be affected by the proximate compositions. Tian et al. (2016) studied the effects of seven maturation methods on the nutrient content and antioxidant activities of purple potatoes, and found that steaming retains potato nutrients to the greatest extent compared with other processing methods.

In recent years, research at home and abroad has mainly focused on essential nutritional evaluation (Kasnak & Palamutoglu, 2022; Zhou et al., 2019), and the impact of processing techniques on the nutrients in potatoes. For example, Y. Yang et al. (2016) found that microwaving led to faster potato starch gelatinization compared to boiling and baking, and the starch retention of potatoes after being baked and microwaved was higher than those that had been boiled. Z. Dong et al. (2021) proved that boiling and frying reduced the Se content of potato tuber, and suggested that boiling is more appropriate for cooking selenium-enriched potatoes. Zhao et al. (2022) systematically analysed the nutritional quality and volatile aroma compounds of stir-fried shredded potatoes, which had higher dietary fibre and calcium contents than deep- fat-fried and shallow-fried potatoes and an excellent essential amino acid composition, and effectively reduced the glycoalkaloid concentration. However, little research has been conducted on the effect of the nutrient content of raw potatoes on their quality after processing. Therefore, this study used current nutritional or physical and chemical data to efficiently select suitable potato types for cooking. At the same time, improved the nutrition and quality of potatoes and promoted potato consumption.

Ten potatoes from Xinjiang were selected for nutrient composition determination and sensory evaluation. We conducted an analysis of the characteristics of potatoes after cooking to determine the raw potato nutrient content and its effect on cooking quality. This research provides a new method and theoretical basis for efficiently screening suitable potato cultivars for cooking using nutrient content data.

2. Materials and methods

2.1 Chemicals

A 16 amino-acid mixed standard (13–08391, Wako, Tokyo, Japan was used. Other analytical-grade reagents were obtained from Tianjin Chemical Reagent Co., Inc. All chemicals used in the present study were analytical or high-grade.

2.2 Sample preparation

Ten potato cultivars from the Xinjiang Academy of Agricultural Sciences Comprehensive Experiment, China, were evaluated, including Ningshu16 (the main potato variety in Ningxia Province), Longshu10 (the main potato variety in Gansu Province), Longshu11, Jizhang12, Longshu7, Heijingang, Gannong5, Favorita, Qingshu9, and Qingshu10 (the eight main potato varieties in Xinjiang Province). The potatoes were cultivated under the same conditions in the fields of the Potato Research Institute in Xinjiang Province. Standard agricultural practices including fertilization, irrigation, disease and pest control, were followed for all potato cultivars. Potato tubers weighing more than 50 g and less than 100 g were selected after being harvested at full maturity. Mechanically damaged, green or sprouted potatoes were eliminated. All tubers were harvested in October 2021 from the research field at the Xinjiang Academy of Agricultural Sciences Comprehensive Experiment, China. A total of 10 kg of each cultivar was collected and stored in plastic bags, transported to the School of Food and Health, Beijing Technology and Business University, and kept at 4°C until use.

2.3 Raw potatoes sample

All tubers were selected, washed, peeled, and cut into 5 × 5 cm slices. The colour and hardness of the potatoes were determined. The potato tubers were chopped, freeze-dried and ground through an 80-mesh sieve, and then the nutrient content of the potatoes was determined

2.4 Cooked potatoes

All tubers were selected, washed, peeled and cut into 1 × 1 × 1 cm slices, placed in an aluminium jar and covered. After boiling in distilled water in an electric steamer (ZN28YK807–150, Zhejiang SUPOR Electrical Appliance Manufacturing Co., Ltd), the aluminium can was placed in the cooking drawer for 30 min, and cool for 20 min. The colour, hardness and sensory properties of the potatoes were measured. The potato tubers were chopped, freeze-dried and ground through an 80-mesh sieve, and then free amino acids were determined.

2.5 Proximate composition analysis

Dry matter content was determinea d by oven drying the potatoes at 105°C until a constant weight was reached muffle furnace was used to determine the ash content. The protein content was determined using the Kjeldahl technique, according to the method 920.152 (AOAC, 2005). The reducing sugar content was determined using Fehling’s reagent titration method (Q. Yang et al., 2019). The dietary fibre content of the freeze-dried, ground samples was determined using the enzymatic and gravimetric method according to the AOAC method 985.29 (AOAC, 1995) Starch content was determined via acid hydrolysis. Fat content was determined using the Soxhlet method (AOAC, 2003).

2.6 Mineral analysis

Minerals content including iron(Fe), calcium(Ca), potassium(K) and phosphorus(P) were determined using the method described by Sun et al. (2011) with certain modifications. A total of 250 mg of sample was mixed with 8 mL of 65% (v/v) HNO₃ for 1 h and then 30% (v/v) H₂O₂ was added. This mixture was digested using a microwave digestion system (MARS 5, CEM Company, NC, U.S.A). The completely digested sample was diluted with Milli-Q water (Bedford, MA, U.S.A) to bring the total volume up to 100 mL and kept at 4°C for further analysis Inductively coupled plasma mass spectrometry (ICP-MS, 7700×; Agilent, CA, U.S.A) was carried out on the sample.

2.7 Vitamins

Vitamin C, B1, B2, and B3 were analysed using the method described by Liu et al. (2017). A total of 1 g of sample was mixed with 9 ml of 0.1 M HCl or ethanol and maintained at 100°C for 30 min in a water bath. After cooling, 6 ml of 2.5 M sodium acetate and 1 ml of 10% (w/v) taka-diastase solution were added. Samples were incubated overnight at 37°C and centrifuged at 500 g for 5 min at 4°C. The resulting supernatant was adjusted to 20 ml with ultrapure water. An aliquot (5 ml) was purified using an Oasis MCX cartridge (6 cc–150 mg, Waters Corp., Manchester, UK) for the simultaneous determination of vitamin C, B1, B2 and B3 contents. HPLC-DAD/FLD analyses were performed in a Waters System (Waters Corp., Manchester, UK) equipped with a 717 Plus autosampler, a 1525 binary HPLC pump, a 2996 photodiode array detector and a 2475 fluorescence detector (Waters Corp., Milford, MA). A linear gradient elution between solvent A (0.2% H3PO4 in 20% w/v MeOH) and solvent B (0.2% H3PO4 in 20% w/v water) was carried out by varying B from 100% to 30% for 5 to 10 min. The linear regression equations of vitamins C, B1, B2 and B3 were y = 66, 108× − 3548.7 (R2 = 0.9994), y = 64,112× − 6724.8 (R2 = 0.9993), y = 42,804× − 95.194 (R2 = 0.9997), and y = 41,831× − 2600.9 (R2 = 0.9995), respectively.

Vitamin B6 analyses were performed according to the method reported by Tuncel et al. (2014). The sample extract was used directly after filtering through a 0.45 mm membrane filter. Different forms of vitamin B6 (pyridoxamine and pyridoxine) were separated on a Zorbax Eclipse C₁₈ column (250 mm, 4.6 mm i.d. and 5 mm particle size) operated at 20°C using an isocratic elution with a mobile phase consisting of 0.01 M H2SO4. The injection volume was 20 mL. The flow rate was kept constant at 1 mL/min throughout the analysis. The fluorescence detector was set at 290 and 395 nm for excitation and emission, respectively. Quantitation of vitamin B6, as determined by HPLC, was based on peak area with linear calibration curves built for each of the compounds identified in the samples. Peaks were identified by comparison of their retention times with those of the standards. Vitamin C, B1, B2, B3 and B6 were expressed as milligrams per 100 g of dry weight sample (mg/100 g DW).

2.8 Free amino acids

Amino acid contents were estimated according to X. Dong et al. (2014) with slight modifications. Freeze-dried potato flour (80 mg) was weighed and put into a Pyrex glass tube. Then, 10 mL of 6 mol/L HCl was added and allowed to flush with nitrogen for 1 min. The mixture was reacted at 110°C for 24 h. The hydrolyte was filtered and transferred to a 50 mL volumetric flask, and diluted with Milli-Q water. A total of 1 mL of diluent was dissolved in 1 mL of 20 mmol/L HCl after drying with nitrogen. This solution was filtered through a 0.2 µm filter membranes prior to analysis. Amino acid composition analysis was performed using the Amino Acids Automatic Analyzer (Hitachi Ltd., L-8900, Tokyo, Japan).

2.9 Colour

Colour values were measured using a colorimeter (CR-400/410, Konica Minolta, Japan) and expressed as L*, a* and b*, where L* indicates brightness (0 = black to 100 = white), a*(redness) indicates red (+) or green (-) and b*(yellowed) indicates yellow (+) or blue (-). The total colour difference (ΔE) can be derived from the formula:

(1) $\mathrm{\Delta }E=\sqrt{{(L_0-L)}^2+{(a_0-a)}^2-{(b_0-b)}^2}$(1)

where:

L₀, a₀ and b₀ – refer to the values measured for raw potatoes;

L, a and b – indicate the values measured for cooked potatoes.

2.10 Texture

Texture was determined according to Q. Yang et al.’s (2019) method, with slight modification. The hardness of potato tubers cut into 1 cm thick slices before and after cooking was determined using a physical property tester (TMS-Pilot, FTC, America) with a force-sensing element of 100 N and a P2 (2 mm) probe punch at a distance of 2 cm. Test conditions were as follows: the reserved height was 3.0 mm, the compression ratio was 70.0%, the pre-test, test, and post-test speed was 1.0 mm/s, the residence time was 2.0 s and the trigger force was 0.05 N. The tuber hardness was determined to be the peak force applied during the puncture, with three punches administered to each tuber of all varieties. The softening can be derived from the following equation:

(2) $Softening=\frac{rawpotatohardness-cookedpotatohardness}{rawpotatohardness}\times 100\mathrm{\%}$(2)

2.11 Sensory evaluation

Sensory evaluation was carried out according to Feng et al.’s (2019) method, with slight modifications. We performed quantitative descriptive analysis (QDA) using a 9-point hedonic scale ranging from 1 to 9. The panel was composed of 10 experimentalists (5 male and 5 female, aged 22–26 years) with experience in sensory evaluation. They scored a total of 4 flavours of cooked potatoes, including umami, sweetness, bitterness and kokumi, with taste reference mass concentrations as shown in Table 1 using 3-digit random coding, and filled out evaluation forms for summary analysis.

Table 1. Sensory evaluation and standard definition.

	Sensory evaluation	Reference definitions
Taste	Umami	10 mmol/L monosodium glutamate solution
	Sweetness	5.0 g/100 mL glucose
	Bitterness	0.08 g/100 mL caffeine
	Kokumi	10 mmol/L glutathione solution

2.12 Statistical analysis

The results are expressed as means ± SD (n = 3). IBM SPSS Statistics 26 was used for data processing and statistical analysis, and data were analysed for high significance and significance at the p < .01 and p < .05 level using the Duncan test. Histograms, radar plots, and correlation analysis plots were produced by Origin 2022. Each experiment was conducted in triplicate and average values were taken for the analysis.

3. Results and discussions

3.1 Nutrient composition of raw potatoes

The nutrient content of potatoes depends on many factors, particularly genetic factors (variety) (Toledo & Burlingame, 2006). We explored the differences in the basic nutrients, dry matter, ash, protein, reducing sugar, starch, dietary fibre, crude fat, iron, calcium, potassium, phosphorus, and vitamin C, B1, B2, B3, and B6 contents of 10 potatoes (Table 2). There was a significant difference in nutrient content between the 10 potatoes (p < .05). The dry matter of potatoes mainly includes starch, reducing sugar, protein, etc. The varieties with the highest dry matter, starch and reducing sugar content were Longshu11 (29.42 g/100 g), Heijingang (17.38 g/100 g), and Ningshu16 (0.52 g/100 g), respectively. Potato protein shows excellent biological value (BV, 0.99), being similar to that of a whole egg (1.0) and greater than that of casein (0.88), soybean (0.77–0.84), and wheat (0.59) (Phillips & Williams, 2011). Qingshu10 (2.93 g/100 g) had the highest protein content while Ningshu16 (0.54 g/100 g) had the lowest. The ash content of each array showed slight differences, and Qingshu9 (1.85 g/100 g) had the highest. The fat content of the 10 potatoes ranged from 0.06 (Heijingang) to 3.15 (Longshu10) g/100 g. The dietary fibre content of the 10 potatoes ranged from 1.07 (Longshu10) to 3.32 (Longshu11) g/100 g. Mineral trace elements iron (1.52 mg/100 g) and P (102.50 mg/100 g) were found in the highest quantities in Longshu10. Phosphorus content was higher than iron content. Among the macro elements, the calcium content of the 10 potatoes ranged from 5.46 (Longshu7) to 20.15 (Ningshu16) mg/100 g. All 10 potatoes had a high potassium content, and thus can be said to be a good source of this mineral. Longshu11 (526.89 mg/100 g) had the highest potassium content while Qingshu10 (189.98 mg/100 g) had the lowest. Wszelaki et al. (2005) found that the mineral composition of soil is highly dependent on agronomic measures such as fertilization and irrigation. The vitamin C content of the 10 potatoes ranged from 1.58 (Longshu7) to 13.1 (Qingshu9) mg/100 g. B vitamin content was relatively low in the potatoes, while all 10 potatoes had a high vitamin B3 content, ranging from 0.04 (Longshu10) to 1.59 (Heijingang) mg/100 g. Longshu11 had the highest vitamin B1 and B6 contents, 0.16 mg/100 g and 0.02 mg/100 g, respectively. In addition, Longshu7 and Gannong5 had the highest vitamin B2 range of 0.05 mg/100 g. Genetic diversity influences characteristics such as dry matter and reducing sugar content, among others, and it also affects the quality of the elaborated product (Silveira et al., 2020).

Table 2. Comparative analysis of nutrient components of different cultivars of potato.

Nutritional composition	Ningshu16	Longshu11	Longshu10	Jizhang12	Longshu7	Qingshu7	Gannong5	Favorita	Qingshu9	Heijingang
Dry matter (g/100 g)	15.86 ± 1.40^f	29.42 ± 0.17^a	21.93 ± 0.55^d	24.37 ± 0.20^c	27.11 ± 0.10^b	24.45 ± 0.46^c	28.03 ± 0.02^b	18.74 ± 0.84^e	22.90 ± 0.28^c	19.29 ± 0.21^e
Ash (g/100 g)	0.77 ± 0.14^bc	0.96 ± 0.03^bc	0.60 ± 0.11^c	0.95 ± 0.06^bc	1.18 ± 0.02^abc	0.83 ± 0.07^bc	1.41 ± 0.51^ab	0.84 ± 0.09^bc	1.85 ± 1.07^a	0.94 ± 0.04^bc
Protein (g/100 g)	0.54 ± 0.09^f	0.85 ± 0.08^ef	2.70 ± 0.18^ab	2.26 ± 0.07^c	1.13 ± 0.00^de	2.93 ± 0.16^a	2.67 ± 0.10^ab	2.07 ± 0.37^c	1.46 ± 0.10^d	1.18 ± 0.01^de
Reduced sugar (g/100 g)	0.52 ± 0.08^a	0.23 ± 0.00^cd	0.19 ± 0.02^d	0.41 ± 0.02^b	0.22 ± 0.01^cd	0.19 ± 0.00^cd	0.24 ± 0.01^cd	0.19 ± 0.00^d	0.25 ± 0.01^c	0.25 ± 0.01^c
Fat (g/100 g)	2.99 ± 0.07^b	0.11 ± 0.00^e	3.15 ± 0.10^a	0.23 ± 0.00^d	0.97 ± 0.05^c	0.20 ± 0.01^d	0.11 ± 0.00^e	0.09 ± 0.02^e	0.23 ± 0.02^d	0.06 ± 0.00^e
Starch (g/100 g)	12.12 ± 0.17^ef	10.86 ± 0.87^f	13.59 ± 1.74^cde	12.11 ± 0.62^ef	12.87 ± 0.54^de	14.29 ± 0.77^bcd	14.61 ± 1.02^bcd	15.08 ± 0.46^bc	16.01 ± 1.44^ab	17.38 ± 0.77^a
Dietary fibre (g/100 g)	1.10 ± 0.07^e	3.32 ± 0.21^a	1.07 ± 0.09^e	2.14 ± 0.21^c	2.09 ± 0.30^c	2.67 ± 0.60^b	2.06 ± 0.25^c	1.39 ± 0.21^de	2.18 ± 0.14^c	1.74 ± 0.14^cd
Fe (mg/100 g)	0.22 ± 0.03^f	0.49 ± 0.11^e	1.52 ± 0.01^a	1.18 ± 0.18^bc	0.79 ± 0.06^d	0.47 ± 0.11^e	0.78 ± 0.06^d	0.98 ± 0.11^cd	1.36 ± 0.03^ab	1.40 ± 0.04^a
Ca (mg/100 g)	20.15 ± 0.78^a	7.82 ± 0.06^e	11.70 ± 1.13^b	7.43 ± 0.06^cde	5.46 ± 0.03^de	7.26 ± 0.01^cde	5.83 ± 0.03^de	10.44 ± 0.00^bc	18.68 ± 0.35^a	8.63 ± 0.06^bcd
K (mg/100 g)	299.50 ± 4.95^f	526.89 ± 6.21^a	396.50 ± 14.85^cd	304.78 ± 11.36^f	429.79 ± 4.72^b	189.98 ± 3.38^g	398.35 ± 2.45^cd	356.18 ± 4.12^e	410.34 ± 1.68^c	383.33 ± 3.13^d
P (mg/100 g)	31.55 ± 1.19^e	19.00 ± 1.09^f	102.50 ± 6.36^a	68.00 ± 0.30^c	69.00 ± 1.23^c	71.00 ± 1.34^c	44.00 ± 1.07^d	15.00 ± 1.07^f	78.00 ± 0.88^b	78.00 ± 1.67^b
VC (mg/100 g)	1.84 ± 0.34^e	2.73 ± 0.33^e	15.74 ± 0.09^a	7.07 ± 0.37^d	1.58 ± 0.07^e	11.36 ± 0.44^c	10.68 ± 0.52^c	10.54 ± 0.18^c	13.1 ± 0.49^b	6.60 ± 0.21^d
VB1(mg/100 g)	0.01 ± 0.00^cd	0.16 ± 0.03^a	0.01 ± 0.00^d	0.08 ± 0.00^cd	0.15 ± 0.06^ab	0.10 ± 0.01^cd	0.1 ± 0.01^cd	0.1 ± 0.00^bcd	0.13 ± 0.01^abc	0.11 ± 0.01^bcd
VB2(mg/100 g)	0.04 ± 0.01^a	0.03 ± 0.00^b	0.01 ± 0.00^b	0.04 ± 0.00^b	0.05 ± 0.00^b	0.04 ± 0.00^b	0.05 ± 0.01^b	0.03 ± 0.00^b	0.04 ± 0^b	0.04 ± 0.00^b
VB3(mg/100 g)	0.07 ± 0.01^f	1.30 ± 0.07^b	0.04 ± 0.00^g	0.81 ± 0.00^ef	1.16 ± 0.03^c	0.75 ± 0.01^f	0.89 ± 0.07^de	0.94 ± 0.01^d	1.16 ± 0.06^c	1.59 ± 0.01^a
VB6(mg/100 g)	0.02 ± 0.00^a	0.02 ± 0.00^c	0.01 ± 0.00^b	0.01 ± 0.00^c	0.01 ± 0.00^c	0.01 ± 0.00^c	0.01 ± 0.00^c	0.01 ± 0.00^c	0.02 ± 0.00^c	0.01 ± 0.00^c

^a-hValues in the same column with different letters showed statistically significant differences (p < .05) according to the Duncan test (n = 3); SD – standard deviation.

3.2 Colour of potatoes

The colour of potatoes is a critical factor affecting consumer purchase intention. The colours of the 10 raw and cooked potatoes are shown in Table 3. There was no significant difference between the L*, a* (-), and b* (+) of the potatoes before being cooked, except for Heijingang and Longshu10. Longshu10, which has white flesh had the highest L* . The L* of Heijingang was significantly lower than that of the other potato cultivars, and its a* was positive while its b* was negative, which may be because Heijingng, which has purple flesh is rich in anthocyanins (Lee et al., 2019). After cooking, except for Heijingang and Qingshu10, the L* of the cultivars decreased, indicating that their colour was darkened. The a* of Heijingang increased while that of the other cultivars decreased. The b* of Qingshu10 and Qingshu9 was significantly higher than that of the other cultivars. The ΔE showed significant differences in various cultivars. The ΔE of Jizhang12 was significantly higher than that of the other cultivars, indicating that it experienced the most significant change in colour before and after cooking, and its enzymatic reaction was the most obvious during cooking. The decrease in L* (brightness) and b* (yellowness) indicated that the potato would become darker after cooking. The above results indicate that the higher the L* and b* after cooking, the better the colour quality of the potatoes. Therefore, variety has a significant impact on colour change during potato processing.

Table 3. Results of colour determination of different cultivars of potato.

Potatoes	Raw			Cooking later
	L*	a*	b*	L*	a*	b*	ΔE
Ningshu16	62.65 ± 1.67^ab	−2.83 ± 0.15^bc	12.18 ± 1.15^ab	50.81 ± 0.49^a	−5.01 ± 0.04^b	3.3 ± 0.65^f	15.04 ± 0.88^b
Longshu11	60.83 ± 0.13^ab	−2.35 ± 0.01^bc	10.24 ± 0.36^b	57.92 ± 0.05^a	−4.94 ± 0.05^b	5.8 ± 0.1^d	5.91 ± 0.25^d
Longshu10	69.15 ± 0.63^a	−3.98 ± 0.06^bc	17.14 ± 0.16^ab	58.6 ± 0.4^a	−5.79 ± 0.11^cd	14.43 ± 0.35^b	6.03 ± 5.40^d
Jizhang12	60.28 ± 0.26^ab	−4.05 ± 0.13^bc	14.51 ± 0.66^ab	41.3 ± 0.23^ab	−5.44 ± 0.14^bc	4.44 ± 0.38^ef	22.14 ± 1.50^a
Longshu7	60.4 ± 1.26^ab	−4.15 ± 0.08^c	18.38 ± 0.24^ab	50.73 ± 0.47^a	−6.25 ± 0.48^d	14.91 ± 0.88^b	10.2 ± 1.28^bcd
Qingshu10	55.09 ± 1.85^c	−2.32 ± 0.7^bc	11.52 ± 0.38^ab	65.2 ± 0.68^a	−6.14 ± 0.31^d	18.68 ± 0.38^a	12.8 ± 1.09^bc
Gannong5	58.38 ± 4.3^bc	−3.59 ± 0.26^bc	17.47 ± 4.32^a	53.05 ± 0.86^a	−7.4 ± 0.24^e	10.75 ± 1.02^c	10.2 ± 2.95^bcd
Favorita	58.12 ± 1.8^bc	−2.48 ± 0.06^bc	10.25 ± 0.61^b	47.36 ± 0.34^a	−5.07 ± 0.28^b	4.68 ± 0.52^de	12.4 ± 1.34^bc
Qingshu9	63.41 ± 0.48^a	−2.67 ± 3.44^b	20.94 ± 0.45^ab	63.26 ± 0.16^a	−6.1 ± 0.03^d	18.73 ± 0.06^a	6.74 ± 4.05^d
Heijingang	18.93 ± 0.48^d	5.26 ± 0.05^a	−0.72 ± 2.31^c	27.6 ± 0.24^b	7.81 ± 0.43^a	−3.61 ± 0.67^h	9.20 ± 0.55^cd

^a-dValues in the same column with different letters showed statistically significant differences (p < .05) according to the Duncan test (n = 3); SD – standard deviation.

3.3 Texture characteristics of potatoes

The texture of potatoes after cooking is considered an important driver of consumer purchases. Therefore, evaluating the hardness of different potato cultivars before and after processing is crucial for evaluating their processing suitability. The hardness of the 10 potatoes before and after cooking was determined (Figure 1), and the change in this value was expressed in terms of softening. Qingshu9’s hardness before and after cooking was the highest, while its softening rate was 88.7%. There was no significant difference in the hardness of Ningshu16, Jizhang12, Qingshu10, and Gannong5 before cooking, and the hardness of Qingshu10 after cooking was significantly higher than that of the other three cultivars. Their softening rates were 91.16%, 91.7%, 90.92% and 91.69%. There were significant differences in the hardness of Longshu10 and Favorita before and after cooking, and the softening rate was 85.43% and 89.93%, respectively. Longshu10 had the lowest softening rate among the 10 cultivars. Longshu11 had the highest softening rate, indicating that its texture characteristics were the most affected by cooking. Different softening rates are suitable for different processed products; for example, Longshu10 and Qingshu9 with a low softening rate, can be used for frozen products with a high degree of solidification, while cultivars with high softening rates, such as Longshu11, Jizhang12 and Qingshu10, can be used for processed products with a higher degree of semi-solidification.

Figure 1. Determination of hardness and softening of different cultivars of potato before and after cooking.

Note: Different upper and lower letters indicate significant differences (p < .05)

3.4 Correlation analysis of nutrient composition with colour and texture characteristics

The basic nutrients found in potatoes reflect their nutritional value, and their colour and softening also affect people’s subjective evaluation of potatoes. Correlations between the basal nutrient content and total colour difference and softening of different potato varieties were analysed (Figure 2) (p < .05). Calcium was significantly positively correlated with ΔE, while protein content was significantly negatively correlated This indicates that cooked potatoes with a higher calcium and lower protein content will be darker and less yellow. It is speculated that the metal element calcium can react with chlorogenic acid in potatoes to generate stable compounds that cause the tubers to turn black (Leriche et al., 2009; Wurster & Smith, 1963). In addition, metal ions can combine with ascorbic acid which breakdown when heated to generate stable metal salts, giving cooked potatoes variable degrees of yellow (Andre et al., 2007; Del Mar Verde Méndez et al., 2004). A possible reason for this is that the metabolite amino acids of protein react with reducing sugars during cooking to generate substances such as melanoidin-like compounds (Wang-Pruski & Nowak, 2004), which have an impact on the colour. The contents of dietary fibre, iron, and phosphorus were significantly correlated with softening. Dietary fibre was significantly positively correlated with softening, while iron and phosphorus contents were significantly negatively correlated. Analysis of these results may indicate that potato cultivars with higher dietary fibre, and lower iron and phosphorus contents soften more after cooking. Studies have shown that changes in potato firmness after cooking are related to starch gelatinization, pectin degradation, cell wall fragmentation, and cell degradation in tubers (Van Dijk et al., 2002).

Figure 2. Correlation analysis of nutrient content and colour difference and softening in different cultivars of potato.

3.5 Free amino acid content of potatoes after cooking

Free amino acid concentration is an important quality determinant of potato tubers because they react with reducing sugars at high temperatures during the Maillard reaction. This reaction produces melanoidin pigments and a host of aroma and flavour volatiles (Muttucumaru et al., 2014). As precursors of such compounds, they play an essential role in the organoleptic properties of potatoes. Free amino acids are not only an essential nutrient in determining the quality of a potato, but also influence its flavour after being cooked. Since we mainly analysed cooked potatoes, their free amino acids contents were measured for the taste evaluation (Table 4). Sixteen amino acids, except for the absence of threonine in Longshu11, were characterized in all cooked potatoes. According to the description of Tseng et al. (2005), the taste characteristics of free amino acids were divided into umami amino acids (glutamic acid, aspartic acid, lysine, glycine, alanine), sweet amino acids (threonine, histidine, proline, serine), bitter amino acids (methionine, arginine, valine, leucine, isoleucine, methionine), and aromatic amino acids (phenylalanine, tyrosine, cystine). The content of free amino acid in cooked potatoes from high to low was umami, bitter, sweet and aromatic amino acids. The content of umami amino acids was 2.96–4.84 mg/g, with Heijingang having the highest. The content of bitter amino acids was 1.34–5.29 mg/g, with Heijingang having the highest, and Longshu7 the lowest. Compared with the other two types of taste amino acids, the contents of sweet and aromatic amino acids in all potatoes were lower at 0.59–1.69 mg/g and 0.21–1.41 mg/g, respectively. The 10 potatoes had more bitter amino acids than the other types. Still, the content of umami amino acids was higher than that of bitter and sweet amino acids. The umami characteristics were apparent, which is in line with the sensory evaluation of cooked potatoes.

Table 4. Results of free amino acid content of different cultivars of cooked potato (mg/g).

Taste characteristics	Free amino acids	Ningshu16	Longshu11	Longshu10	Jizhang12	Longshu7	Qingshu10	Gannong5	Favorita	Qingshu9	Heijingang
Umami	Glu	0.66 ± 0.01^f	0.60 ± 0^g	0.59 ± 0^g	0.71 ± 0^e	0.84 ± 0.01^c	0.87 ± 0^b	0.67 ± 0^f	0.68 ± 0.01^f	0.79 ± 0.01^d	0.90 ± 0.03^a
	Asp	0.62 ± 0.01^b	1.18 ± 0.01^a	0.42 ± 0.01^d	0.41 ± 0.01^d	0.47 ± 0^c	0.41 ± 0.04^d	0.43 ± 0.01^d	0.37 ± 0.01^e	0.43 ± 0.01^d	0.49 ± 0.01^c
	Lys	0.17 ± 0.01^e	0.11 ± 0.01^f	0.20 ± 0.01^d	0.38 ± 0^b	0.12 ± 0.01^f	0.11 ± 0^f	0.18 ± 0.02^e	0.31 ± 0.01^c	0.21 ± 0.01^d	0.53 ± 0.01^a
	Gly	0.02 ± 0^e	0.01 ± 0^g	0.03 ± 0^d	0.06 ± 0^b	0.01 ± 0^f	0.032 ± 0^d	0.02 ± 0^e	0.07 ± 0^a	0.02 ± 0^e	0.05 ± 0^c
	Ala	0.06 ± 0.01^d	0.04 ± 0^e	0.09 ± 0^c	0.31 ± 0.02^a	0.01 ± 0^f	0.08 ± 0^c	0.01 ± 0^f	0.15 ± 0.01^b	0.01 ± 0^f	0.15 ± 0.01^b
Bitter	Met	0.11 ± 0.01^e	0.05 ± 0^f	0.18 ± 0.01^cd	0.31 ± 0.01^a	0.1 ± 0.01^e	0.17 ± 0.01^d	0.16 ± 0.01^d	0.20 ± 0.01^b	0.16 ± 0.01^d	0.19 ± 0.01^bc
	Arg	0.42 ± 0.01^g	0.15 ± 0.01^j	0.47 ± 0.01^f	0.78 ± 0.03^c	0.30 ± 0.03^i	0.93 ± 0.01^b	0.60 ± 0.02^d	0.38 ± 0.01^h	0.50 ± 0.01^e	1.33 ± 0.01^a
	Val	0.2 ± 0.01^g	0.11 ± 0^i	0.43 ± 0^c	0.59 ± 0.01^b	0.14 ± 0.01^h	0.22 ± 0.01^f	0.28 ± 0.02^e	0.4 ± 0^d	0.29 ± 0.02^e	0.65 ± 0^a
	Leu	0.07 ± 0^c	0.04 ± 0^fg	0.06 ± 0^d	0.10 ± 0^b	0.03 ± 0^g	0.04 ± 0^fg	0.04 ± 0^ef	0.09 ± 0.01^b	0.05 ± 0^.de	0.17 ± 0.02^a
	Ile	0.10 ± 0.01^e	0.05 ± 0^g	0.14 ± 0^d	0.25 ± 0.01^b	0.04 ± 0^g	0.07 ± 0.01^f	0.09 ± 0.01^e	0.17 ± 0^c	0.10 ± 0.01^e	0.31 ± 0^a
Sweet	Ser	0.09 ± 0.01^f	0.02 ± 0^i	0.10 ± 0^e	0.26 ± 0^b	0.05 ± 0^h	0.15 ± 0.01^d	0.08 ± 0.01^g	0.22 ± 0.01^c	0.083 ± 0^fg	0.29 ± 0.01^a
	His	0.12 ± 0^de	0.08 ± 0^f	0.13 ± 0.01^cd	0.20 ± 0.01^b	0.07 ± 0.01^g	0.19 ± 0^b	0.11 ± 0.01^e	0.13 ± 0.01^c	0.13 ± 0^cd	0.23 ± 0.02^a
	Pro	0.24 ± 0.02^a	0.09 ± 0.01^d	0.19 ± 0.01^b	0.13 ± 0.09^c	0.13 ± 0.01^c	0.06 ± 0^e	0.11 ± 0^c	0.12 ± 0.01^c	0.11 ± 0.01^c	0.19 ± 0.01^b
	Thr	1.18±+0.01^b	-	0.87 ± 0^c	0.81 ± 0^d	0.5 ± 0^g	1.18 ± 0^a	0.77 ± 0^e	0.57 ± 0.01^f	0.47 ± 0^h	0.86 ± 0.01^c
Aromatic	Phe	0.15 ± 0.02^ef	0.14 ± 0^efg	0.31 ± 0.015^ab	0.32 ± 0^a	0.16 ± 0.01^de	0.12 ± 0.01^ef	0.13 ± 0.01^ef	0.18 ± 0.02^d	0.12 ± 0.01^f	0.30 ± 0.03^c
	Tyr	0.13 ± 0.01^g	0.13 ± 0^g	0.21 ± 0.01^d	0.37 ± 0.01^b	0.12 ± 0^g	0.20 ± 0.01^d	0.16 ± 0.02^f	0.23 ± 0.01^c	0.17 ± 0^e	0.48 ± 0.02^a

^a-fValues in the same column with different letters showed statistically significant differences (p < .05) according to the Duncan test (n = 3); SD – standard deviation.

3.6 Sensory evaluation of potatoes after cooking

Tsantili et al. (2010) concluded that sensory characteristics are significantly influenced by the cultivar of the measured samples. Nutrition, safety and sensory properties are the three main elements considered when evaluating food quality, and one of the most essential attributes of sensory quality is taste. As shown in the sensory evaluation radar chart in Figure 3, potatoes’ taste category after cooking was mainly umami and kokumi, followed by bitterness and sweetness. The umami and kokumi taste of Heijingang had the highest score, with sweetness and bitterness having the lowest score, which may be due to the prevalent umami taste neutralizing the bitterness of the potatoes. Qingshu9 had the highest bitterness and lowest sweetness score. Longshu7 had the lowest bitterness score. Longshu10 and Jizhang12 had higher umami and sweetness scores, as well as a lower bitterness score. So, the overall taste was better. The differences in the taste of cooked potatoes may be caused by the differences in the content of free amino acids and free fatty acids. The cooked potatoes largely fell into the umami taste category.

Figure 3. Radar chart of taste sensory scores of different cultivars potato of after cooking.

3.7 Correlation analysis of sensory properties and free amino acids

To explore the contribution of free amino acids to the taste of cooked potatoes, the correlation between taste sensory properties and free amino acids was analysed (Figure 4). It could be seen that umami taste showed a highly significant correlation with isoleucine and tyrosine, and a significant correlation with lysine, alanine, serine and leucine. Since potatoes have a relatively high protein content, umami and bitter amino acids may primarily derive from protein catabolism during cooking, which accelerates the rate of protein decomposition, so the umami taste of potatoes is enhanced. Bitter amino acids may result in a specific umami taste at low concentrations. Kokumi refers to the after-taste of a food after swallowing. Kokumi was highly significantly correlated with lysine, leucine and isoleucine, and had a significant correlation with serine and tyrosine. Lysine is an umami amino acid, whereas leucine and isoleucine are bitter amino acids; therefore umami and bitter tastes will remain in the mouth for longer. The lysine, isoleucine and alanine threshold was relatively low, and they play a significant role in the taste of potatoes. By comparison, the threshold of other free amino acids was higher, and they can effectively enhance the flavour of potatoes. The free amino acids associated with the sweetness and bitterness of cooked potatoes need to be further explored. Niu et al. (2012) have proved that the bitterness of cherry wine is related to aspartic acid, serine, glycine, threonine, phenylalanine and leucine. The results show that free amino acids contributed to taste. Additionally, taste substances also include free fatty acids, reducing sugars, glycosine bases and nucleotides (Tseng et al., 2005), which play an essential role in the taste of cooked potatoes.

Figure 4. Correlation analysis of sensory characteristics and free amino acids in different cultivars of potato.

4. Conclusion

Since many of the basic nutritional indicators of potatoes have been tested, this study further explored the correlation between the nutritional content of raw potatoes and cooking quality to enable the use of the existing nutritional indicators to directly evaluate the cooking quality of potatoes (Zang et al., 2022). The results show significant correlations between some nutritional components of raw potatoes and cooking quality. The ΔE had a significant correlation with calcium and protein content. Softening had a significant correlation with dietary fibre, iron and phosphorus contents. Umami had a highly significant correlation with isoleucine and tyrosine (p < .01). Kokumi showed a highly significant correlation with lysine, leucine, and isoleucine content (p < .01). Other free amino acids played a role in taste. Qingshu10 and Gannon5 had a small colour difference; and a larger L* and b* in the tubers after cooking and are thus suitable for potato products with high colour requirements after cooking; Longshu11 had the highest dietary fiber content, the lowest iron and phosphorus content and the highest softening rate and is suitable for mashed potato products; Jizhang12, Longshu10 and Heijingang had strong umami and sweet flavours, so they are suitable for fresh-cut as well as flavour products. These results are of great significance for the selection and breeding of suitable potato cultivars for cooking and processing, as well as the production of potato as a staple food products.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was funded the major projects of Beijing Science and Technology Commission [research grant numbers: D17110500190000]; Quality training of talents and first-class specialties in food science and engineering (municipal) program.