Evaluation indices of sour flavor for apple fruit and grading standards

YAN Zhen, E-mail: yanzhen01@caas.cn; Correspondence NIE Ji-yun, Tel: +86-429-3598178, E-mail: jiyunnie@163.com

＊ These authors contributed equally to this study.

© 2018 CAAS. Publishing services by Elsevier B.V. All rights reserved.

(2) 该3-面为(3,4,7)-面,由R2.1和R3.5得3-面和面上的3-点最多从7-点拿走的权值为

1. lntroduction

Flavor is an important component of fruit quality (Nie and Dong 2014; Zheng et al. 2016). With social and economic developments and the improvement of living standards,fruit flavor is receiving greater attention from fruit breeders,producers, sellers, consumers, and processing industries(Carew et al. 2004; Zhang et al. 2008; Ma et al. 2016).Organic acids are the main flavor substances of fruit. Their composition and quantity are closely related to the quality of fruit, and directly affect the flavor of fruit (Mahmood et al.2012; Shangguan et al. 2015). In apples, flavor mainly depends on acid content, while sugar content has little effect on apple flavor (Guo et al. 2012; Berüter 2004).

没过一会儿，只听到噼噼啪啪的一阵声响，嘎绒跑了出来，他双手捂着头，悻悻然离开了，嘴里狠狠地嘀咕着：又不是金屁股！又不是银屁股！

Based on correlation analysis, five indices (Mal, ToA, AcV,TiA, and pH value) were chosen as the sour flavor evaluation indices for apples. For these indices, the correlation coefficients were all close to or above 0.85. According to the results of normality testing using DPS® Software, Mal,ToA, and AcV were all normally distributed with probability values of the Jarque-Bera statistic over 0.05, TiA was close to normally distributed, whereas pH value was not normally distributed (Table 3). The normal distribution curves of Mal,ToA, AcV, and TiA in fruits of 106 varieties were fitted using@Risk 5.5 for Excel (Fig. 4) .

However, few apple cultivars are used in these studies,and there is currently no report available on grading standards of evaluation indices for apple sour flavor and the quantitative relationships between these indices (Wu et al. 2007; Ma et al. 2015). Thus, the results of these studies can neither fully reflect the composition properties of organic acids in apple, nor provide scientific and quantitative standards for evaluating apple sour flavor (Zhang et al. 2010;Sadar et al. 2016). Given that, the present study selected the mature fruits of 106 apple cultivars and tested the following indices: malic acid (Mal), oxalic acid (Oxa), citric acid (Cit), lactic acid (Lac), succinic acid (Suc), fumaric acid(Fum), pH value, titratable acidity (TiA), acidity value (AcV),and total organic acids (ToA). The present study clarified the level of each index and the relationships between the indices, established the grading standard of evaluation indices for apple sour flavor, and provided a scientific basis for evaluating apple flavor and selecting apple cultivars.

2. Materials and methods

2.1. Sampling and preparation

The ranges of the 10 tested indices are in Fig. 1. The mean values of total organic acids, titratable acid, acidity value,and pH were 6.10 mg g−1, 0.47%, 8.10 mg g−1, and 3.60,respectively. Among the six organic acids, malic acid had the highest content with an average of 5.80 mg g−1, followed by oxalic acid with an average of 0.162 mg g−1. The other four organic acids (citric acid, lactic acid, succinic acid, and fumaric acid) were very low in content, with averages of 0.083, 0.035, 0.015, and 0.009 mg g−1, respectively. Among the cultivars studied, 9.4% were over 9 mg g−1 and 10.4%were below 3 mg g−1 in total organic acids; 6.6% were over 9 mg g−1 and 15.1% were below 3 mg g−1 in malic acid content; 8.5% were above 12 mg g−1 and 10.4% were under 4 mg g−1 in acidity value; 12.3% were above 4 and 11.3%were under 3.3 in pH value; 5.7% exceeded 0.8% and 9.4%were less than 0.2% in titratable acidity.

由图7仿真曲线可知:车辆横摆角速度为方波信号时,采用PID控制,响应时间为0.25 s,角速度跟踪误差最大值为0.08 rad/s;采用改进神经网络PID控制,响应时间为0.1 s,角速度跟踪误差最大值为0.02 rad/s.因此,在相同道路转弯条件下,车辆横摆角速度跟踪采用改进神经网络PID控制器,不仅响应时间短,而且控制精度高.

2.2. Reagents

Sodium hydroxide (GR, guaranteed reagent) was obtained from Tianjin Shengao Chemical Reagent Co., Ltd. (China).Phenolphthalein indicator (AR, analytical reagent) was purchased from Tianjin Damao Chemical Reagent Factory(China). Both were used for the determination of titratable acid content. 50% sodium hydroxide solution (AR) was produced by Merck KGaA (Germany). Heptafuorobutyric acid (≥99.5%) for ion chromatography was produced by Fluka (USA). Tetrabutylammonium hydroxide for ion chromatography (0.995 g cm–3) was produced by Sigma Aldrich (USA). These three reagents were used to prepare the mobile phase. Oxalic acid standard (99.5%)and lactic acid standard (90.5%) were purchased from Dr.Ehrenstorfer GmbH (Germany). Fumaric acid standard(99.5%) was obtained from Aladdin Chemistry Co., Ltd.(USA). Citric acid standard (98%), succinic acid standard(99%), and malic acid standard (99%) were purchased from Chem Service (USA).

2.3. Determination of titratable acid and pH

The titratable acid content was determined using indicator titration and the pH value was tested using a FE20K-type pH Meter (Mettler-Toledo, Switzerland) according to Nie (2009).

2.4. Determination of organic acid component

通信技术专业的培养目标与学校、学院培养目标是一脉相承的。如表1所示，专业培养目标1和目标2体现了学校目标“满足社会需求的技术技能型人才”，专业培养目标3体现了学校目标“健康发展的高素质人才”。学校、学院、专业目标的内在关联性如图1所示。

The correlation analysis of the 10 studied indices showed that 51.1% of the correlation coefficients were significant at α=0.01 (Table 2). There was a significant negative correlation between pH value and six indices (Mal, Cit, Suc,ToA, TiA, and AcV). Mal and five indices (Cit, Suc, ToA, TiA,and AcV) were significantly positively correlated. Similar trends were seen between Oxa and Lac; between Lac and Fum; between TiA and AcV; between Cit and four indices(Suc, ToA, TiA, and AcV); between Suc and three indices(ToA, TiA, and AcV); and between ToA and two indices(TiA and AcV). The correlation coefficients were close to or exceeded 0.85 (some were close to 1) for: Mal and four indices (ToA, TiA, AcV and pH value); ToA and three indices(TiA, AcV, and pH value); TiA and two indices (AcV and pH value); and AcV and the pH value.

For each treatment, a 200-g sample was collected and pulverized into a powder using a 6870-type Freezer Mill(SPEX Sample Prep, USA). A 5-g sample was accurately weighed and added to 25 mL of deionized water. The sample was then placed in a constant temperature water bath (HWS28, Shanghai Yiheng Instruments Co., Ltd.,China) set to 80°C and extracted for 30 min. The sample was cooled and diluted to 50 mL, after which it was filtered using absorbent cotton. A total of 1 mL of the filtrate was diluted to 10 mL with deionized water. The sample was cleaned up with an RP column (Dionex, USA) followed by filtration using a 0.22-μm pore size filter (Fine, Japan).

set at 30°C. The injection volume was 25 μL. Quantification was conducted using an external standard method.

Table 1 A list of apple cultivars studied

10 Malus domestica cv. Close America 63 Malus domestica cv. Mutsu Japan 11 Malus domestica cv. Cuihong China 64 Malus domestica cv. Nagafu 2 Japan 12 Malus domestica cv. Dalu 52 Unknown 65 Malus domestica cv. Nagafu 7 Japan 13 Malus domestica cv. Danxia China 66 Malus domestica cv. Nancheng Aijinguan China 14 Malus domestica cv. Dayao Duanzhi Hongxing China 67 Malus domestica cv. Nero 26 Japan 15 Malus domestica cv. Dounan Japan 68 Malus domestica cv. New Jonagold Japan 16 Malus domestica cv. Doyle Unknown 69 Malus domestica cv. Ningfeng China 17 Malus domestica cv. Drumbo Canada 70 Malus domestica cv. Ningguan China 18 Malus domestica cv. Early McIntosh America 71 Malus domestica cv. Orin Japan 19 Malus domestica cv. Fangming Japan 72 Malus domestica cv. Paci fic Rose New Zealand 20 Malus domestica cv. 2001 Fuji Japan 73 Malus domestica cv. Pingzhi Guoguang China 21 Malus domestica cv. Fujin China 74 Malus domestica cv. Qingguan China 22 Malus domestica cv. Gala New Zealand 75 Malus domestica cv. Qinguan China 23 Malus domestica cv. Giant Jeniton Japan 76 Malus domestica cv. Qingxiang China 24 Malus domestica cv. Gold Spur Delicious America 77 Malus domestica cv. Qiuxiang Japan 25 Malus domestica cv. Golden Delicious America 78 Malus domestica cv. Ralls America 26 Malus domestica cv. Granny Smith Australia 79 Malus domestica cv. Red Spur Delicious America 27 Malus domestica cv. Guoqing China 80 Malus domestica cv. Sansa Japan 28 Malus domestica cv. Hac 9 Japan 81 Malus domestica cv. Shengnong 2 China 29 Malus domestica cv. Hanfu China 82 Malus domestica cv. Shuanghong China 30 Malus domestica cv. Hatsuaki Japan 83 Malus domestica cv. Smith Cider America 31 Malus domestica cv. Helasang Unknown 84 Malus domestica cv. Stark Jumbo America 32 Malus domestica cv. Himekami Japan 85 Malus domestica cv. Starkrimson America 33 Malus domestica cv. Hirosaki Fuji Japan 86 Malus domestica cv. Starkrimson Netherlands 34 Malus domestica cv. Huafu China 87 Malus domestica cv. Stark Spur Gold Delicious America 35 Malus domestica cv. Huahong China 88 Malus domestica cv. Starkspur Ultra Red Delicious America 36 Malus domestica cv. Huajin China 89 Malus domestica cv. Summerland Canada 37 Malus domestica cv. Huamei China 90 Malus domestica cv. Tezaohong China 38 Malus domestica cv. Huanong 1 China 91 Malus domestica cv. Tianhongyu Japan 39 Malus domestica cv. Huayue China 92 Malus domestica cv. Tianhuangkui China 40 Malus domestica cv. Husveti Rosmaring Unknown 93 Malus domestica cv. Tsugaru Japan 41 Malus domestica cv. Ingram America 94 Malus domestica cv. Vista Bella America 42 Malus domestica cv. Jiguan China 95 Malus domestica cv. Wellspur Delicious America 43 Malus domestica cv. Jinhong China 96 Malus domestica cv. Whitney America 44 Malus domestica cv. Jonagold America 97 Malus domestica cv. Xindong Britain 45 Malus domestica cv. Jonared America 98 Malus domestica cv. Xinguoguang China 46 Malus domestica cv. Judain France 99 Malus domestica cv. Xinhua China 47 Malus domestica cv. Judeline France 100Malus domestica cv. Yanshanhong China 48 Malus domestica cv. Kitanosach Japan 101 Malus domestica cv. Yellow Transparent Former Soviet Union 49 Malus domestica cv. Kogetsu Japan 102 Malus domestica cv. Yingqiu China 50 Malus domestica cv. Koihime Japan 103 Malus domestica cv. Yuehong China 51 Malus domestica cv. Kuliesa Unknown 104 Malus domestica cv. Zaojinguan China 52 Malus domestica cv. Lobo Canada 105 Malus domestica cv. Zhanhanxiang China 53 Malus domestica cv. Longfeng China 106 Malus domestica cv. Zhongqiu China

2.5. Calculation of acidity

The acidity value of each sample was calculated according to eq. (1):

Where, AcV is the acidity value; Ci (mg g−1) is the content of Cit, Mal, Lac, Fum, Suc, or Oxa; and Ai is the acidity intensity of Cit, Mal, Lac, Fum, Suc, or Oxa, with the values of 100, 76, 107, 55, 88, and 50, respectively (Ding 1997; Xia 2008). The intensity of oxalic acid was calculated based on the human saliva flow rate with an oxalic acid concentration of 0.1 mol L−1 (Ding 1997).

命题4：集中决策下系统的总利润、物流服务水平以及产品的销售量均大于分散决策下的相应取值， 即 Πc∗＞Πd∗、 Sc∗＞Sd∗、 Qc∗＞Qd∗。

2.6. Statistical analysis

Minitab 16 software (Minitab Statistical Software,https://it.minitab.com/en-us/support/answers/answer.aspx?log=0&id=2485) was used to draw boxplot graphs.DPS® software (ver. 13.5) (Tang 2010) was used for the normality test of indices; if the Jarque-Bera test statistical probability value was ＞0.05, then the index was normally distributed. @Risk 5.5 (Risk Analysis Software, http://www.palisade.com/about/about.asp) for Excel was used to fit the normal distribution (iterations=10 000) of the indices, and the 10th, 30th, 70th, and 90th percentiles of the normal distribution curve were taken as the grading node values of the index. Other statistical analyses were performed using Excel 2010 Software.

Regression analysis indicated that there were significant positive linear relationships between Mal and ToA (Fig. 3-A),Mal and AcV with average fitting errors of 1.0 and 1.3%,respectively (Fig. 3-B). There was also a significant linear relationship (Fig. 3-C) between ToA and AcV with an average fitting error of 0.4%. There were significant logarithmic relationships (Fig. 3-D, E, F, and G) between pH value and one of the four indices (TiA, Mal, ToA, and AcV) with average fitting errors of 2.1, 3.0, 3.1, and 3.1%, respectively.For all of these relationships, the equations had high fitting accuracy and can be used to accurately predict related indices. Significant linear relationships were also found between TiA and each of the three indices (Mal, ToA, and AcV) (Fig. 3-H, I, and J) with average fitting errors of 6.6,6.3, and 6.2%, respectively, indicating that these equations can be used to roughly estimate related indices.

3. Results

3.1. lndices of apple sour flavor

A total of 106 apple cultivars, as shown in Table 1, were collected from the National Repository of Apple Germplasm Resources (Xingcheng City, Liaoning Province, China). Tenyear-old trees on Malus baccata (L.) Borkh rootstock were planted in sandy loam soil. The orchard where they were planted is flat and is managed at a medium level. Fruits of each cultivar were not bagged during development. For each cultivar, three trees were selected. At the suitable maturity stage for harvest when the seeds began to turn brown (Wang et al. 2003), 30 fruits per cultivar were randomly picked from the middle of the canopy. From these fruits, 10 fruits that were consistent in shape, size, and color were chosen and sampled by quartering, the edible part was chopped and immediately frozen in liquid nitrogen, and then stored at –20°C in a refrigerator. Each sample was repeated three times for testing.

The studied indices showed different degrees of dispersion. Cit and Fum had the highest variation (with coefficients of variation up to 50.7 and 65.8%, respectively),followed by Oxa, Suc, Mal, Lac, AcV, ToA, and TiA with coefficients of variation between 31 and 44%. The variation of pH value was the smallest with a coefficient of variation of only 8.2%. The content order of the six organic acids was not the same in each cultivar: 85.8% cultivars were in the order of Mal＞Oxa＞Cit＞Lac＞Suc＞Fum; 6.6% cultivars were in the order of Mal＞Oxa＞Cit＞Lac＞Fum＞Suc; 2.8% cultivars followed the order of Mal＞Oxa＞Cit＞Suc＞Lac＞Fum; and 1.9%cultivars followed the order of Mal＞Oxa＞Lac＞Cit＞Suc＞Fum.Among the organic acids tested, Mal was predominant with average content accounting for 94.5% of ToA, followed by Oxa with average content accounting for 3.1% of ToA (Fig. 2).Cit was the third most common with average content accounting for 1.4% of ToA. Lac, Suc, and Fum accounted for 0.65, 0.28, and 0.17% of ToA, respectively.

Fig. 1 Ranges of 10 sour flavor indices in fruits of apple cultivars tested. Mal, malic acid; Oxa, oxalic acid; Cit, citric acid; Lac,lactic acid; Suc, succinic acid; Fum, fumaric acid; ToA, total organic acids; AcV, acidity value; TiA, titratable acidity. Mal,Oxa, Cit, Lac, Suc, Fum, ToA, and AcV are in mg g–1; TiA is in percentage.

Fig. 2 Content distribution of six acids in fruits of apple cultivars tested. Mal, malic acid; Oxa, oxalic acid; Cit, citric acid; Lac,lactic acid; Suc, succinic acid; Fum, fumaric acid.

3.2. Relationships between indices of apple sour flavor

The filtrate was tested for content of the six organic acids using an ion chromatograph (ICS-5000, Dionex, USA)with a suppressor (AMMS-ICE 300, Dionex, USA). The eluent was 0.4 mmol L−1 heptafluorobutyric acid and the regeneration solution was 5 mmol L−1 tetrabutylammonium hydroxide. The flow rate was 1.0 mL min−1. The column(9 mm×250 mm, ICE-AS6, Dionex, USA) temperature was

讲武堂的师资力量很受学者关注，以辛亥革命前的三期为例，已知担任教官的40人中，日本各学堂毕业者有28人，其余的人，有4位出自国内最高学府北京京师大学堂，2位出自越南法国人办的巴维学校，还有6人情况不明。其中，担任军事教学的23人中，有21位毕业于日本陆军士官学校，另外2人毕业于日本陆军测量学校。军事课程，基本上被从日本归国的留学者包揽。

3.3. Grading standards of sour flavor indices for apples

China is the world’s largest apple producer and consumer(Wu et al. 2007). Its apple production in 2014 reached 40.923 million tons (NBSC 2015a), accounting for 24.67%of its fruit output and 47.31% of the world’s apple output(86.5 million tons) (NBSC 2015b). Apples have become an important part of the Chinese diet, and they have many components that are beneficial to human health (Zhang et al. 2010). Currently, there are many studies on organic acid in apples. These studies cover the changes in organic acids in leaves of ‘Honey crisp’ apple (Wang et al. 2010),organic acid comparison between different cultivars (Hecke et al. 2006), as well as the effects of fruit bagging (Liu et al.2013), and the effects of location within the tree canopy on organic acids in the fruit peel and flesh (Feng et al. 2014).

On the basis of the theoretical probability of a normal distribution, grade medium accounts for 40%, grade low and grade high both account for 20%, both grade lower and grade higher account for 10% (Liu 1996). Thus, each of the four indices (Mal, ToA, AcV, and TiA) were divided into five grades (lower, low, medium, high, and higher) by the 10th,30th, 70th, and 90th percentiles of their normal distribution curve (Table 3). As mentioned above, pH value was not normally distributed. Mal was normally distributed, and there was logarithmic relationship between Mal (x) and pH value (y), namely y=−0.619ln(x)+4.64. The corresponding grading node values of pH value were obtained using this equation and the 10th, 30th, 70th, and 90th percentiles of the normal distribution curve of Mal (Table 3).

调查结果显示天水市蔬菜主栽区海拔大部分在1 050～1 800 m，主要以井水、地下水、河水进行灌溉，种植品种主要为黄瓜、辣椒、西红柿、韭菜、大蒜、甘蓝、叶菜（油麦菜、生菜、菠菜、油菜、茼蒿、红叶菜）、芹菜。农药使用存在不合理的现象，每个生育周期喷药次数3～8次，黄瓜、辣椒、西红柿的用药次数较多，秦州、甘谷、武山均存在喷药次数偏多的现象；个别县（区）仍然存在使用毒死蜱现象，毒死蜱为中等毒农药，即使合理使用，也可能会出现农残超标；还存在用药浓度过高、盲目混用农药、采收前三四天再用杀菌剂和杀虫剂的现象。

As shown in Table 3, the four indices of Mal, ToA, AcV,and TiA had the same trend that the higher the index value and the grade, the stronger the sour flavor of apple. The index of pH value showed the reverse trend that the lower the index value and the grade, the stronger the sour flavor of apple.

4. Discussion

Differences in the level and proportion of organic acidscharacterize the distinctive flavor of each type of fruit (Gil et al. 2000; Sadka et al. 2000; Róth et al. 2007; Chen et al.2009). Apples contain a variety of organic acids including oxalic acid (Oxa), fumaric acid (Fum), succinic acid (Suc),tartaric acid, quinic acid, shikimic acid, citric acid (Cit), malic acid (Mal), and acetic acid (Wu et al. 2007; Liang et al. 2011;Rodríguez et al. 2017). Among these acids, the content of malic acid in apples is significantly higher than other organic acids with a value usually close to or more than 90% of ToA(Jing et al. 2016). In this paper, average malic acid content was 94.5% of ToA in 106 apple cultivars. Therefore, apples can be considered a typical fruit that is dominated by malic acid compared to other organic acids (Berüter et al. 2004;Ma et al. 2015). In apples, the content of other organic acids is often very low and almost negligible compared to malic acid (Liu et al. 2016). However, not all organic acids found in apples are consistently being monitored. In particular, fumaric acid, shikimic acid, and maleic acid are seldom reported (Wu et al. 2007; Wang et al. 2010). These differences might be due to different conditions of growth and cultivation and different biological time (Petkovsek et al.2007; Sadara et al. 2016).

Table 2 Correlation coefficients between 10 fruit indices of tested apple cultivars1)

1) Mal, malic acid; Oxa, oxalic acid; Cit, citric acid; Lac, lactic acid; Suc, succinic acid; Fum, fumaric acid; ToA, total organic acids; TiA,titratable acidity; AcV, acidity value. ＊ and ＊＊, significant at 0.05 and 0.01, respectively.

Indice Mal Oxa Cit Lac Suc Fum ToA TiA AcV Oxa 0.1193 Cit 0.7957＊＊ 0.1930＊Lac 0.2106＊ 0.3294＊＊ 0.0892 Suc 0.5402＊＊ 0.0559 0.4494＊＊ 0.2425＊Fum 0.0915 –0.0929 0.0220 0.4140＊＊ 0.0227 ToA 0.9996＊＊ 0.1442 0.8037＊＊ 0.2232＊ 0.5426＊＊ 0.0934 TiA 0.9808＊＊ 0.0993 0.7957＊＊ 0.1756 0.5288＊＊ 0.0949 0.9802＊＊AcV 0.9993＊＊ 0.1542 0.8030＊＊ 0.2254＊ 0.5418＊＊ 0.0926 0.9999＊＊ 0.9797＊＊pH value –0.8499＊＊ –0.0456 –0.6003＊＊ –0.1294 –0.4601＊＊ –0.1394 –0.8469＊＊ –0.8783＊＊ –0.8464＊＊

Fig. 3 Relationship between five sour flavor indices of different tested apple cultivars (A–J). ToA, total organic acids; Mal, malic acid; AcV, acidity value;TiA, titratable acidity.

Table 3 Grading of five acidity evaluation indices of tested apple cultivars

1) Mal, malic acid; ToA, total organic acids; AcV, acidity value; TiA, titratable acidity.

Indice1) Jarque-Bera statistic P-value Lower Low Medium High Higher Mal (mg g–1) 1.7606 0.4147 ＜2.9 2.9–4.5 4.6–6.9 7.0–8.6 ≥8.7 ToA (mg g–1) 1.8609 0.3944 ＜3.2 3.2–4.8 4.9–7.2 7.3–8.9 ≥9.0 AcV (mg g–1) 1.8723 0.3921 ＜4.2 4.2–6.4 6.5–9.6 9.7–11.9 ≥12.0 TiA (%) 6.2293 0.0444 ＜0.21 0.21–0.35 0.36–0.57 0.58–0.73 ≥0.74 pH value 8.2777 0.0159 ＜3.20 3.20–3.43 3.44–3.69 3.70–3.97 ≥3.98

Fig. 4 Simulated normal distribution curves of four fruit sour flavor indices of different tested apple cultivars. TiA, titratable acidity;ToA, total organic acids; Mal, malic acid; AcV, acidity value.

Regression analysis is a method to study the change in relationship between the dependent and independent variables, and its final result is generally an empirical regression equation (Tang 2006). This method has been effective in food quality studies including: characteristic analysis of cherry fruit (Khub 2014); correlations between orange quality indices (Rosa et al. 2016); and differences in organic acids between wine varieties (Geana et al. 2016).In the present study, a large sample of apples (106 cultivars)and regression analysis were used to discover significant linear or logarithmic relationships between five apple sour flavor indices, namely Mal, ToA, AcV, TiA, and pH value.The average fitting error of each equation was less than 5%,and these equations can therefore be used to accurately predict related indices. Significant correlations between indices are the basis for linear regression or nonlinear regression. The present study showed that there were significant (at α=0.01) correlations between five apple sour flavor evaluation indices (Mal, ToA, TiA, AcV, and pH value),and the correlation coefficients were all close to or more than 0.85, with some close to 1. This is consistent with the finding of a previous report (Feng et al. 2013).

1.2.3 土地利用的模拟与预测 进行城市土地利用的模拟预测时，根据粗集方法自动获取的转换规则，来对2011年武汉市光谷区域的土地利用类型进行模拟预测，该过程在matlab中编程实现.由于模拟时间与实际时间不同，需要一个迭代次数，迭代200次，每次迭代后，领域元胞数和土地类型都会发生变化，所以要每次都需要更新.之后获取得到新的矩阵，这个矩阵是模拟的2011年城市土地与非城市土地的矩阵，将这个矩阵再转换成tif输出，在ARCGIS软件中进行浏览查看.

Most of the variables of biological phenomena follow a normal distribution, and thus the normal distribution is the most common distribution in fruit science experiments(Huazhong Agricultural College 1979; Palacios et al. 2015).This study showed that Mal, ToA, and AcV of apples were normally distributed; TiA was close to normally distributed;and pH value had a skewed distribution. Compared to traditional experience grading, probability grading has the advantage of objective, unified standards and comparable results, and therefore, has more guidance value. However,a large sample is needed to represent the normal population(Avila et al. 2015; Malegoria et al. 2017). In this study, a large sample of 106 apple cultivars were used, covering early-, medium-, and late-maturing groups.

We have ever studied the flavor evaluation indices for fresh apple juice based on 159 cultivars (Nie et al. 2012),and the results showed that there were significant positive correlation between the sour flavor and the TiA of fresh apple juice, that is the higher the TiA, the stronger the sour flavor, and vice versa. In that paper, the sensory evaluation of the sour flavor of fresh apple juice was carried out by nine experts using oral taste. It is known that fresh apple juice was produced from apple without modification, and its sour flavor is the same as that of raw apple. In this article,as there were significant positive linear relationships or significant logarithmic relationships between TiA and the other four indices (Mal, ToA, AcV, and pH value) of apple(see Fig. 3), the latter four indices (Mal, ToA, AcV, and pH value) were also recommended as the suitable indices for the sensory evaluation of apple sour flavor.

At present, the evaluation indices of sour flavor for apple are generally expressed in the absolute value of titratable acid content (Wang et al. 2005), and grading standards of apple sour flavor evaluation indices have not been reported.In the present study, the grading standards were established.Using the theoretical probability of a normal distribution (Liu 1996), the four evaluation indices of apple sour flavor (Mal,ToA, AcV, and TiA) were divided into five grades (lower, low,medium, high, and higher). These four indices all followed,or nearly followed, a normal distribution. Although pH value did not follow a normal distribution, its grading node values were obtained using the logarithmic relationship between pH value and Mal. Therefore, the grading standards of the above mentioned five apple sour flavor evaluation indices were established and can be used for future apple sour flavor evaluation (Table 3). All of these indices are stable,quantitative, and can be detected accurately.

5. Conclusion

Apple is a typical fruit that is dominated by malic acid content among all organic acids. The average content of malic acid in apples in the present study accounted for 94.5% of ToA, and the content order of organic acids in most apples was Mal＞Oxa＞Cit＞Lac＞Suc＞Fum. There were significant linear or logarithmic relationships between apple sour flavor indices (Mal, ToA, AcV, TiA, and pH value),and most of the equations had high- fitting precision and can be used to accurately predict related indices. Mal,ToA, and AcV were normally distributed; TiA was close to a normal distribution; but pH value had a skewed distribution.The grading standards of Mal, TiA, ToA, and AcV were established based on their normal distribution curves, while the grading standards of the pH value were established using its logarithmic relationship with Mal. For the index of pH value, higher index values and grades meant weaker sour flavor of apple. Conversely, for the other four indices,higher index values and grades meant stronger sour flavor of apple. The grading standards of all five indices can be used to evaluate the sour flavor of apple.

Acknowledgements

This work was financially supported by the earmarked fund for the China Agriculture Research System (CARS-27), the National Program for Quality and Safety Risk Assessment of Agricultural Products of China (GJFP2017003) and the Scientific and Technological Innovation Project of the Chinese Academy of Agricultural Sciences (CAAS-ASTIP) .

References

Avila F, Mora M, Oyarce M, Zuñiga A, Fredes C. 2015. A method to construct fruit maturity color scales based on support machines for regression: Application to olives and grape seeds. Journal of Food Engineering, 162, 9–17.

Berüter J. 2004. Carbohydrate metabolism in two apple genotypes that differ in malate accumulation. Journal of Plant Physiology, 161, 1011–1029.

Carew R, Smith E G. 2004. The value of apple characteristics to wholesalers in western Canada: A hedonic approach.Canadian Journal of Plant Science, 84, 829–835.

Chen F X, Liu X H, Chen L S. 2009. Developmental changes in pulp organic acid concentration and activities of acidmetabolising enzymes during the fruit development of two loquat (Eriobotrya japonica Lindl.) cultivars differing in fruit acidity. Food Chemistry, 114, 657–664.

Ding N K. 1997. Flavor Chemistry of Food. China Light Industry Press, Beijing. (in Chinese)

Feng F J, Li M J, Ma F W, Cheng L L. 2014. Effects of location within the tree canopy on carbohydrates, organic acids,amino acids and phenolic compounds in the fruit peel and flesh from three apple (Malus×domestica) cultivars.Horticulture Research, 1, doi: 10.1038/hortres.2014.19

Feng J, Ren X L, Tian J W. 2013. Comparative contents of polyphenols, soluble sugars and organic acids in ‘Fuji’apples from different growing regions. Food Science, 34,125–130.

Geana E I, Popescu R, Costinel D, Dinca O R, Ionete R E,Stefanescu I, Artem V, Bala C. 2016. Classification of red wines using suitable markers coupled with multivariate statistic analysis. Food Chemistry, 192, 1015–1024.

Gil A M, Duarte I F, Delgadillo I, Colquhoun I J, Casuscelli F,Humpfer E, Spraul M. 2000. Study of the compositional changes of mango during ripening by use of nuclear magnetic resonance spectroscopy. Journal of Agricultural& Food Chemistry, 48, 1524–1536.

Guo Yan, Liang J, Li M M, Zhao Z Y. 2012. Determination of organic acids in apple fruits by HPLC. Food Science, 33,227–230.

Hecke K, Herbinger K, Veberič R, Trobec M, Toplak H, Štampar F, Keppel H, Grill D. 2006. Sugar-, acid- and phenol contents in apple cultivars from organic and integrated fruit cultivation. European Journal of Clinical Nutrition, 60,1136–1140.

Huazhong Agricultural College. 1979. Research Methods for Fruit Tree. Agricultural Press, Beijing. (in Chinese)

Jing C J, Ma C Q, Zhang J, Jing S J, Jiang X B, Yang Y Z, Zhao Z Y. 2016. Effect of debagging time on pigment patterns in the peel and sugar and organic acid contents in the pulp of ‘Golden Delicious’ and ‘Qinguan’ apple fruit at mid and late stages of development. PLoS ONE, 11, doi: 10.1371/journal.pone.0165050

Khub A K. 2014. Regression association analysis of fruit traits with molecular markers in cherries. Plant Systematics and Evolution, 300, 1163–1173.

Liang J, Guo Y, Liu Y L, Li M M, Zhao Z Y. 2011. Analysis of contents and constituents of sugar and organic acid in different apple cultivars. Journal of Northwest A&F University (Natural Science Edition), 39, 163–170. (in Chinese)

Liu M J. 1996. Studies on the variation and probability grading of major quantitative characters of Chinese jujube. Acta Horticulturae Sinica, 23, 105–109. (in Chinese)

Liu R L, Wang Y Y, Qin G Z, Tian S P. 2016. Molecular basis of 1-methylcyclopropene regulating organic acid metabolism in apple fruit during storage. Postharvest Biology and Technology, 117, 57–63.

Liu Y L, Zhang X J, Zhao Z Y. 2013. Effects of fruit bagging on anthocyanins, sugars, organic acids, and color properties of ‘Granny Smith’ and ‘Golden Delicious’ during fruit maturation. European Food Research Technology, 236,329–339.

Ma B Q, Chen J, Zheng H Y, Fang T, Ogutu C, Li S H, Han Y P, Wu B H. 2015. Comparative assessment of sugar and malic acid composition in cultivated and wild apples. Food Chemistry, 172, 86–91.

Ma B Q, Zhao S, Wu B H, Wang D M, Peng Q, Owiti A,Ting F, Liao L, Collins O, Korban S S, Li S H, Han Y P.2016. Construction of a high density linkage map and its application in the identification of QTLs for soluble sugar and organic acid components in apple. Tree Genetics &Genomes, 12, 1–10.

Mahmood T, Anwar F, Abbas M, Boyce M C, Saari N. 2012.Compositional variation in sugars and organic acids at different maturity stages in selected small fruits from Pakistan. International Journal of Molecular Sciences, 13,1380–1392.

Malegoria C, Marquesb E J N, Freitasc S T, Pimenteld M F,Pasquinie C, Casiraghia E. 2017. Comparing the analytical performances of Micro-NIR and FT-NIR spectrometers in the evaluation of acerola fruit quality, using PLS and SVM regression algorithms. Talanta, 165, 112–116.

NBSC (National Bureau of Statistics of China). 2015a.Agriculture. [2016-8-8]. http://data.stats.gov.cn/easyquery.htm?cn=C01 (in Chinese)

NBSC (National Bureau of Statistics of China). 2015b. Foreign economic and trade. [2016-8-8]. http://data.stats.gov.cn/easyquery.htm?cn=C01 (in Chinese)

Nie J Y. 2009. Analytical Techniques of Fruit Quality and Safety.Chemical Industry Press, Beijing. (in Chinese)

Nie J Y, Dong Y F. 2014. Standards and Evaluation Indices for Fruit Quality and Safety. China Agriculture Press, Beijing.(in Chinese)

Nie J Y, Li H F, Li J, Wang K, Li Z X, Wu Y L. 2012. Studies on taste evaluation indices for fresh apple juice based on 159 cultivars. Acta Horticulturae Sinica, 39, 1999–2008.(in Chinese)

Palacios C L, Valdivia C P, Agüero J A R, Rivera J R A, Tobίas H M R, Hernández R M S, Bremont J F J. 2015. Inter- and intra-specific variation in fruit biomass, number of seeds,and physical characteristics of seeds in Opuntia spp.,Cactaceae. Genetic Resources and Crop Evolution, 62,1205–1223.

Petkovsek M M, Stampar F, Veberic R. 2007. Parameters of inner quality of the apple scab resistant and susceptible apple cultivars (Malus domestica Borkh.). Scientia Horticulturae, 114, 37–44.

Rodríguez Ó, Gomes W, Rodrigues S, Fernandes F A N. 2017.Effect of acoustically assisted treatments on vitamins,antioxidant activity, organic acids and drying kinetics of pineapple. Ultrasonics Sonochemistry, 35, 92–102.

Rosa C I L F R, Clemente E, Oliveira D M, Todisco K M, Costa J M C. 2016. Effects of 1-MCP onthe post-harvest quality of the orange cv. Perastored under refrigeration. Revista Ciência Agronômica, 47, 624–632.

Róth E, Berna A, Beullens K, Yarramraju S, Lammertyn J,Schenk A, NicolaÏ B. 2007. Postharvest quality of integrated and organically produced apple fruit. Postharvest Biology and Technology, 45, 11–19.

Sadara N, Krajnca A U, Tojnkoa S, Tijskensb L M M, Schoutenb R E, Unuk T. 2016. Development and distribution of quality related compounds in apples during growth. Scientia Horticulturae, 213, 222–231.

Sadka A, Dahan E, Cohen L, Marsh K B. 2000. Aconitase activity and expression during the development of lemon fruit. Physiologia Plantarum, 108, 255–262.

Shangguan L F, Sun X, Zhang C Q, Mu Q, Leng X P, Fang J G.2015. Genome identification and analysis of genes encoding the key enzymes involved in organic acid biosynthesis pathway in apple, grape, and sweet orange. Scientia Horticulturae, 185, 22–28.

Tang Q Y. 2010. DPS© Data Processing System - Experimental Design, Statistical Analysis and Data Mining. Science Press,Beijing. (in Chinese)

Wang H C, Ma F F, Cheng L L. 2010. Metabolism of organic acids, nitrogen and amino acids in chlorotic leaves of‘Honeycrisp’ apple (Malus domestica Borkh) with excessive accumulation of carbohydrates. Planta, 232, 511–522.

Wang K, Liu F Z, Cao Y F. 2005. Descriptors and Data Standard for Apple (Malus spp. Mill.). China Agriculture Press, Beijing.(in Chinese)

Wang W H, Xu B Q. 2003. Postharvest Treatment and Keep Freshing During Storage of Fruits. Jindun Publishing House,Beijing. (in Chinese)

Wu J H, Gao H Y, Zhao L, Liao X J, Chen F, Wang Z F, Hu X S. 2007. Chemical compositional characterization of some apple cultivars. Food Chemistry, 103, 88–93.

Xia Y B. 2008. Flavor Chemistry of Food. Chemical Industry Press, Beijing. (in Chinese)

Zhang H, Zhou F, Ji B P, Nout R M J, Fang Q, Yang Z W.2008. Determination of organic acids evolution during apple cider fermentation using an improved HPLC analysis method. European Food Research and Technology, 227,1183–1190.

Zhang Y Z, Li P M, Cheng L L. 2010. Developmental changes of carbohydrates, organic acids, amino acids, and phenolic compounds in ‘Honeycrisp’ apple flesh. Food Chemistry,123, 1013–1018.

Zheng H, Zhang Q, Quan J, Zheng Q, Xi W. 2016. Determination of sugars, organic acids, aroma components, and carotenoids in grapefruit pulps. Food Chemistry, 205,112–121. (in Chinese)