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ORIGINAL ARTICLE / ORIGINALBEITRAG
https://doi.org/10.1007/s10341-023-00855-2
Erwerbs-Obstbau (2023) 65:423–434
Quantitative Analysis of Relationship Between Fruit Quality of ‘Fuji’
Apple and Environmental Factors: A Case Study of the Loess Plateau
Production Region
Qiang Zhang1,2,3 ·MinjiLi
1,2,3 ·BeibeiZhou
1,2,3 ·JunkeZhang
1,2,3 ·QinpingWei
1,2,3
Received: 28 June 2021 / Accepted: 21 December 2022 / Published online: 26 April 2023
© The Author(s) 2023
Abstract
The objective of this study was to investigate the effect of environmental factors (soil nutrition and meteorological factors)
on fruit quality traits of ‘Fuji’ apples. ‘Fuji’ apple fruits, soil samples, and meteorological data were investigated from
66 commercial orchards covering 22 counties of the Loess Plateau region in China. Partial least squares regression (PLSR)
and linear programming were combined to analyze the quantitative relationship between fruit quality and environmen-
tal factors. The effect of meteorological factors (55.99%) on fruit quality was greater than that of soil nutrition factors
(44.01%) in the Loess Plateau apple-producing region of China. Optimum environmental factors for high-quality ‘Fuji’
apples in the Loess Plateau region were: soil organic matter (13.94–17.93 g kg–1), total N (0.77–1.03 g kg–1), available
N (68.39–115.87 mg kg–1), P (62.39–124.67 mg kg–1), K (324.41–468.62 mg kg–1), Ca (6.54 mg kg–1), Fe (14.97 mg kg–1),
Zn (1.55–2.72 mg kg–1), B (0.37 mg kg–1), and soil pH (7.98–8.20); mean annual temperature (18 °C), total annual precipi-
tation (431.2–713.8 mm), monthly mean temperature (19.9 °C), lowest temperature (8.03 °C), highest temperature (19.63 to
27.25 °C), temperature difference between day and night (12.41 °C), total precipitation (338.3–589.8 mm), relative humidity
(56.57–82.41%), and sunshine percentage (36.96–55.87%) during the growing period (April–October).
Keywords Fruit quality traits · Soil nutrition · Meteorological factors · Model effects · Quantitative relationship
Introduction
Fruit development and quality formation are mainly deter-
mined by meteorological conditions, soil nutrition, and cul-
tivation techniques (Mattheis and Fellman 1999). The effect
of environmental factors (soil nutrition and meteorological
factors) on fruit quality continues to attract much attention.
Previously, most of the related works focused on the quali-
tative effect of environmental factors on fruit quality (e.g.,
Duan et al. 2014; Gao et al. 2009; Lakatos et al. 2012;Li
Qinping Wei
qpwei@sina.com
1Institute of Forestry and Pomology, Beijing Academy of
Agriculture and Forestry Sciences, 100093 Beijing, China
2Beijing Engineering Research Center for Deciduous Fruit
Trees, 100093 Beijing, China
3Key Laboratory of Biology and Genetic Improvement of
Horticultural Crops (North China), Ministry of Agriculture
and Rural Affairs, 100093 Beijing, China
et al. 2000; Sugiura et al. 2013; Takashi and Hisashi 2007;
Weietal.2003; Zhang et al. 2021; Zhu et al. 2001). Some
researchers reported on the correlation between soil nutri-
tion and fruit quality in local apple orchards and optimiza-
tion schemes for the production of high-quality apples, and
multivariate statistical analysis was used (Xu et al. 2014;
Zhang et al. 2011b, 2017; Zhou et al. 2016). However, few
studies have been conducted on the quantitative relationship
between apple quality and soil nutrition and meteorological
factors.
The Loess Plateau in China, located at 34–40°N lati-
tude and 103–114°E longitude, has the largest loess deposit
area in the world of 630,000km2, where the average al-
titude is 1000–1500 m and the soil thickness is 50–80 m
(Gan 1989). This makes it the largest apple-producing re-
gion in the world (Zhang 2019), with the apple planting
area accounting for 27% of global production (Han 2015).
The climate of the Loess Plateau is favorable for apple
since the sunshine duration is long, the soil layer is deep
and fertile, and the temperature difference between day and
night is large (Ma 2006). The span of the production re-
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424 Q. Zhang et al.
gion is so large that orchard conditions vary significantly.
Zhang et al. (2018) found that the combination of partial
least squares regression (PLSR) and linear programming is
a feasible method for exploring the relationship between
comprehensive meteorological factors and ‘Fuji’ fruit qual-
ity, and they obtained optimum theoretical schemes. This
paper uses their method to study the effect of the spe-
cific soil–climate ecological environment on fruit quality of
‘Fuji’ apples in the Loess Plateau region. Our aim was to
screen the key environmental factors that affect fruit qual-
ity and to establish an optimum scheme of soil nutrition
and meteorological factors; subsequently, we aimed to ob-
tain restrictive environmental factors for high-quality fruit
production. These results will provide valuable information
for ‘Fuji’ apple production in the Loess Plateau region of
China.
Materials and Methods
Experiment Location and Orchard Selection
A total of 22 advantageous apple-production counties of
the Loess Plateau Production region were first chosen for
this study based on their geographical locations (Table 1),
and then three orchards per county were determined. Each
of the sampled orchards has an area of more than 0.6ha,
Tab le 1 Geographical location of the 22 sampling counties in the Loss Plateau production region of China (from Zhang et al. 2018)
Serial number Province County Longitude (E) Latitude (N) Altitude (m, a.s. l.)
1 Shaanxi Liquan 108°170–108°41034°200–34°500557
2 Shaanxi Luochuan 109°130–109°45035°260–36°0401148
3 Shaanxi Baishui 109°160–109°45035°40-35°270785
4 Shaanxi Xunyi 108°080–108°52034°570-35°330974
5 Shaanxi Fengxiang 107°100–107°38034°200–34°450782
6 Shaanxi Ansai 108°050–109°26036°300–37°1901110
7 Shaanxi Yichuan 109°410–110°32035°420–36°230836
8 Shaanxi Fufeng 107°450–108°03034°120–34°370581
9 Shanxi Wanrong 110°250–110°59035°130–35°310596
10 Shanxi Linyi 110°170–110°54034°580–35°180400
11 Shanxi Ruicheng 110°360–110°42034°360–34°480504
12 Shanxi Yicheng 111°340–112°03035°230–35°520583
13 Shanxi Raodu 111°050–111°49035°540–36°190470
14 Shanxi Qixian 112°120–112°39037°040–37°280766
15 Gansu Qin’an 105°200–106°20034°440–35°1101286
16 Gansu Jingning 105°20‘–106°05’ 35°01‘–35°45’ 1668
17 Gansu Jingchuan 107°150–107°45035°110-35°3101055
18 Gansu Lixian 104°370-105°36033°350–34°3101413
19 Gansu Qingcheng 107°160–108°05035°420–36°1701102
20 Gansu Qingshui 105°450–106°30034°320–34°5601376
21 Gansu Zhengning 107°560–108°38035°140–35°3601449
22 Gansu Maiji 105°250–106°43034°060–34°4801090
and the soil is loam or sandy loam type. The typical ap-
ple cultivar was ‘Fuji’ apple grafted on crabapple (Malus
pumila), 15–20 years old, and in free-growing spindle
shape or in small canopy shape. The apple yield reached
30,000–45,000 kg · ha–1 · year–1 in the last 5 years. During
production, the young fruits were covered by double-layer
paper bags, and flower thinning and fruit thinning were
carried out artificially.
Sampling and Testing
Six trees were chosen for testing in every orchard, and
the trees were almost of the same size. In August or
September of the two study years, the soil samples were
collected using a drill under the six trees. A soil layer of
0–40 cm was sampled at four cardinal directions around
the trunk of the tree, 50 cm inward from the canopy drip
line. The soils from one tree were mixed, air-dried, and
sifted with a 2-mm sieve. In the experiment, only half
of each soil sample was used for testing and the other
half was left as spare. The potassium dichromate vol-
umetric external heating method, Kjeldahl method, and
alkali diffusion method were employed to measure soil
organic matter (SOM), soil total nitrogen (N), and soil
available N, respectively; the NaHCO3extraction method,
ammonium molybdate-tartaric emetic-ascorbic acid col-
orimetry method, NH4OAc extraction-flame photometer
K
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Quantitative Analysis of Relationship Between Fruit Quality of ‘Fuji’ Apple and Environmental Factors: A Case Study of the Loess... 425
method, CH3COONa extraction-atomic absorption spec-
trometry method, and azomethine-H colorimetric method
were used to determine the soil available phosphorus (P),
soil available potassium (K), soil available calcium (Ca),
and soil available boron (B), respectively (Bao 2005). The
DTPA extraction-atomic absorption spectrometry method
was used to test soil available iron (Fe) and zinc (Zn), and
soil pH was determined using a potentiometer (Bao 2005).
The fruit samples were collected from the end of Oc-
tober to the beginning of November. At the fruit maturity
stage, 15 apples were picked from each of the sampled
trees in south–east and south–west directions, 1.5m above
the ground. There were 90 apples in total collected from
each experiment orchard. The sampled apples were pre-
served by plastic bags, stored in a fresh-keeping storehouse
or refrigerator at 4°C within 4 h, and later transferred to
our laboratory in Beijing using a refrigerator trunk. In total,
30 of the 90 apples were randomly chosen for testing. The
fruit length and diameter were measured using a Vernier
caliper (Harbin Measuring & Cutting Tool Group Co., Ltd.,
Haibin, China), and then length/diameter (L/D) was calcu-
lated. Fruit mass was weighted using a balance with a pre-
cision of 0.001g. Fruit firmness was assessed from the two
opposite sides of a fruit with a GY-1 fruit firmness tester
(Mudanjiang Machinery Research Institute, China). Solu-
ble solid content (SSC, °Brix) was measured with a digital
refractometer (Atago RS-5000, Japan). Acid concentration
(%) was measured by titrating the juice with 0.1 mol L–1
NaOH. Fruit skin color area was calculated based on a col-
oring index.
Meteorological Data Collection
The meteorological data of each sampled orchard were
obtained from the nearby meteorological stations (National
Meteorological Information Center, China) and in the study
a total of 132 meteorological stations were involved. Or-
dinary Kriging interpolation was employed to compute
the meteorological indexes at every orchard, including
the mean annual temperature, total annual precipitation,
monthly mean temperature from April to October, monthly
mean lowest temperature from April to October, monthly
mean highest temperature from April to October, monthly
mean temperature difference between day and night from
April to October, total precipitation from April to October,
monthly mean relative humidity from April to October, and
monthly mean sunshine percentage from April to October
in 2010 and 2011.
Data Analysis
The soil nutrition factors and meteorological data and the
fruit quality traits were taken as independent variables and
as objective function, respectively. The PLSR (SAS 9.4
software, SAS Institute Inc., Cary, NC) was used to analyze
the overall model effect weights on fruit quality, and the
variable importance for projection (VIP) was used for inde-
pendent variable selection. Linear regression models were
fitted to identify the relationship between the selected en-
vironmental factors and fruit quality traits. The restrictions
of each apple quality trait were established using the lin-
ear programming approach (LINGO 10.0 Software, Lindo
System Inc., Chicago, IL), to determine the optimum envi-
ronmental factors for high-quality ‘Fuji’ apples.
Results
Basic Information of Fruit Qualities and
Environmental Factors
There were significant differences in apple fruit quality, soil
nutrition, and meteorological factors for different apple-pro-
ducing counties in the Loess Plateau region (Table 2). The
differences in mean fruit weight (Y1), SSC (Y4), and TA
content (Y5) between different orchards were large, with
the maximum being 1.53-, 1.37-, and 2.07-fold greater than
the minimum values, respectively. The differences in fruit
shape index (Y2), fruit firmness (Y3), and skin color area
(Y6) between different orchards were not as large as the
difference in other factors, with the maximum being ap-
proximately 1.1-fold greater than the minimum values. The
maximum of soil available P (S4), K (S5),andZn(S8) con-
tent of orchards was over 5.6-fold greater than the minimum
values. The maximum of soil total N (S2), available N (S3),
Fe (S7), and B (S9) content was over 3.3-fold greater than
the minimum values, and the maximum of SOM (S1)and
available Ca (S6) content was, respectively, 2.47- and 1.36-
fold greater than the minimum values. The mean and the
highest and lowest values of soil pH (S10) were 8.20, 8.45,
and 7.98, respectively, which all exceeded the most suitable
pH range (6.5–7.5) for apple production. The mean and
the highest and lowest values of total annual precipitation
(M2) were 565.11 mm, 713.80 mm, and 431.20 mm, respec-
tively. The maximum of mean annual temperature (M1)and
monthly mean lowest temperature from April to October
(M4) in these orchards were, respectively, 3.27- and 2.12-
fold greater than the minimum values, and for other meteo-
rological factors (M3,andM5–M9) the maximum value was
more than 1.4-fold greater than the minimum values.
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426 Q. Zhang et al.
Tab le 2 Basic information of fruit qualities a, soil nutritional status b, and meteorological factors c
Measuring item Mean SD Maximum Minimum Difference between maximum and minimum
Y1(g) 252.75 27.07 323.27 211.27 112.00
Y20.86 0.03 0.92 0.79 0.13
Y3(kg cm–2) 8.81 0.71 10.29 7.44 2.85
Y4(SSC, %) 13.85 1.09 16.61 12.10 4.51
Y5(%) 0.21 0.04 0.29 0.14 0.15
Y6(%) 93.40 5.29 99.00 80.40 18.60
S1(g kg–1) 13.94 2.53 17.93 7.26 10.67
S2(g kg–1) 0.77 0.20 1.03 0.27 0.76
S3(mg kg–1) 68.39 24.10 115.87 30.73 85.14
S4(mg kg–1) 62.39 31.84 124.67 18.63 106.04
S5(mg kg–1) 324.41 105.68 534.67 95.07 439.60
S6(mg kg–1) 5.79 0.49 6.54 4.82 1.72
S7(mg kg–1) 9.27 2.65 14.97 4.44 10.53
S8(mg kg–1) 1.55 0.54 2.72 0.41 2.31
S9(mg kg–1) 0.37 0.16 0.90 0.20 0.70
S10 8.20 0.14 8.45 7.98 0.47
M1(°C) 11.64 3.02 18.00 5.50 12.50
M2(mm) 565.11 68.03 713.80 431.20 282.60
M3(°C) 17.60 2.73 19.90 13.30 6.60
M4(°C) 13.85 2.40 17.01 8.03 8.98
M5(°C) 24.37 2.24 27.25 19.63 7.62
M6(°C) 10.52 1.18 12.41 7.31 5.10
M7(mm) 480.68 64.51 589.80 338.30 251.50
M8(%) 67.54 6.85 82.41 56.07 26.34
M9(%) 44.74 5.92 55.87 32.91 22.96
aY1–Y6denote mean fruit weight, fruit shape index, fruit firmness, soluble solid content (SSC), titratable acid (TA) content, and skin color area,
respectively
bS1–S10 denote soil organic matter (SOM), total N, available N, available P, available K, available Ca, available Fe, available Zn, available B, and
pH, respectively
cM1–M9denote mean annual temperature, total annual precipitation, monthly mean temperature from April to October, monthly mean lowest
temperature from April to October, monthly mean highest temperature from April to October, monthly mean temperature difference between day
and night from April to October, total precipitation from April to October, monthly mean relative humidity from April to October, and monthly
mean sunshine percentage from April to October, respectively
SD standard deviation
Soil Nutrition and Meteorological Factor
Effect Weights in the Relationship Model of
“Environmental Factors–Fruit Quality Traits”
Model effect weights mainly reflect the proportion of dif-
ferent independent variables to overall potential effect of
dependent variables (Wang et al. 2000a). In this study, the
model effect weights reflected the importance of soil nutri-
tion and meteorological factors in the formation of overall
fruit quality traits in the Loess Plateau production region
(Fig. 1). Six factors, including M8,S1,M2,S7,S9,andS2,
had larger, positive effect weights on overall fruit qual-
ity traits, with their weight absolute values contributing
12.14%, 6.63%, 6.38%, 6.02%, 5.80%, and 5.79%, respec-
tively, to fruit quality, while the factors M9,M5,M4,and
S10 showed larger, negative effect weights on overall fruit
quality traits and their weight absolute values contributed
10.23%, 7.54%, 6.04%, and 5.31%, respectively, to fruit
quality. Among all the environmental factors, S10,M1,M2,
M3,M7,andM8had a negative effect on fruit quality traits,
while the others had a positive effect. The model effect
weights of soil nutrition and meteorological factors on over-
all fruit quality traits were accumulated. The meteorological
factors (M1–M9) accounted for 55.99% of the total weights,
and the soil nutrition factors (S1–S10) only accounted for
44.01%, which indicated that meteorological factors influ-
enced fruit quality more than soil nutrition factors did in
the Loess Plateau apple-producing region.
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Quantitative Analysis of Relationship Between Fruit Quality of ‘Fuji’ Apple and Environmental Factors: A Case Study of the Loess... 427
-0.5
-0.4
-0.3
-0.2
-0.1
0.0
0.1
0.2
0.3
0.4
0.5
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 M1 M2 M3 M4 M5 M6 M7 M8 M9
Model effect weights and percentage of
absolute weight
Model effect weights Percentage of absolute weight
Fig. 1 Model effect weights of soil nutrition and main meteorological factors affecting fruit qualities in the Loess Plateau production region of
China. S1–S10 denote soil organic matter (SOM), total nitrogen, available nitrogen, available phosphorus, available potassium, available calcium,
available iron, available zinc, available boron, and pH, respectively. M1–M9denote mean annual temperature, total annual precipitation, monthly
mean temperature from April to October, monthly mean lowest temperature from April to October, monthly mean highest temperature from April
to October, monthly mean temperature difference between day and night from April to October, total precipitation from April to October, monthly
mean relative humidity from April to October, and monthly mean sunshine percentage from April to October, respectively
Multivariate Analysis of the Relationship Between
Fruit Quality and Environmental Factors
The VIP of Environmental Factors
The VIP is a variable screening method, which mainly de-
scribes the explanatory ability of related independent vari-
ables to dependent variable, and selects independent vari-
ables according to the explanatory ability. The value of VIP
represents the importance of the independent variable to
the dependent variable (Zhang and Feng 2012; Zhou et al.
2016). In this study, the VIP values of environmental factors
on each characteristic factor of fruit quality were, respec-
tively, calculated by taking soil nutrition factors (S1–S10)
and meteorological factors (M1–M9) as independent vari-
ables (Table 3). The VIP value of 0.8 was set as thresh-
old to screen the main influencing environmental factors of
fruit quality traits in the Loess Plateau production region.
As shown in Table 3, all environmental factors had varying
degrees of influence on fruit quality traits of ‘Fuji’ apples,
and different fruit quality traits were affected by different
soil nutrition and meteorological factors. According to the
effects, the main influencing environmental factors of mean
fruit weight were sorted from large to small—M9>M8>
M4>M5>S7>S1—which indicated that sunshine, humid-
ity, the highest temperature and lowest temperature in the
growing period (April–October), and SOM had greater ef-
fects on fruit size than did other environmental factors. The
order of the main environmental factors that affected fruit
shape index was S5>M8>M1>S10 >S8>M2>S9>
M4>S1>M6, according to the effect from large to small.
This indicated that the soil available K, available Zn, pH,
mean annual temperature, and monthly mean relative hu-
midity during the apple growing period affected fruit shape
more than the other environmental factors did. The order
of the main factors affecting fruit firmness was S3>M3>
S2>M7>S5>S10 >S8>M1>M2>S1,sortedbyeffect.
This indicated that the soil available N, total N, available K,
monthly mean temperature from April to October, and to-
tal precipitation from April to October had greater effects
on fruit firmness. The order of the main factors affecting
SSC was M3>S7>S2>S5>M7>S10 >S4>S8>S3>S1.
This indicated that the monthly mean temperature of the
growing period was the foremost factor related to SSC; in
addition, the total precipitation in the apple growing period,
soil available Fe, total N, available K, and pH also played
key roles in SSC formation. The main factors affecting TA
content were ranked according to their effects, and the order
was M9>M8>S9>S1>S2>S10 >S8>M7. This indicated
that the sunshine and relative humidity in apple growing
period, and SOM, soil total N, available B, and soil pH
had greater effects on fruit acidity than the other factors.
Regarding the effect on apple skin color area, the order of
the main related factors was M4>M5>S4>S6>S8>
S5>M3>M8. This indicated that temperature (highest tem-
perature and lowest temperature) during the apple growing
period was the foremost factor associated with apple skin
color area, and in addition the soil available P, available K,
available Ca, and available Zn also played important roles
in fruit color development.
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428 Q. Zhang et al.
Tab le 3 The VIP of soil nutrition and meteorological factors affecting fruit quality traits a
Affecting factors bY1Y2Y3Y4Y5Y6
S10.84987 0.87201 0.81477 0.83023 0.90151 0.48522
S20.61138 0.76002 1.28227 0.91851 0.90044 0.74149
S30.63027 0.79264 1.70117 0.841 0.60375 0.71107
S40.58677 0.58672 0.55886 0.87273 0.40423 1.06272
S50.49318 1.12494 0.92137 0.91587 0.6068 0.94499
S60.4501 0.33825 0.45169 0.20141 0.72521 1.01526
S70.97217 0.6347 0.41638 0.99705 0.69971 0.308
S80.64859 1.01589 0.87764 0.86275 0.87454 0.96163
S90.72694 0.923 0.60965 0.51039 0.96641 0.21911
S10 0.43392 1.06169 0.88407 0.89269 0.8905 0.69924
M10.22584 1.06996 0.84108 0.60085 0.42575 0.67019
M20.60004 0.96959 0.88301 0.62063 0.7369 0.7117
M30.35751 0.48561 1.4265 1.61194 0.24628 0.8454
M41.15603 0.88848 0.25062 0.74501 0.06968 1.28204
M51.12459 0.67145 0.04152 0.47556 0.30103 1.25368
M60.48793 0.85893 0.53856 0.72272 0.60137 0.23189
M70.54925 0.79154 0.99613 0.91143 0.85533 0.50271
M81.18394 1.09903 0.6011 0.73998 1.24899 0.81782
M91.18347 0.57019 0.6278 0.70524 1.35646 0.20896
aY1–Y6denote mean fruit weight, fruit shape index, fruit firmness, soluble solid content (SSC), titratable acid (TA) content, and skin color area,
respectively
bS1–S10 denote soil organic matter (SOM), total N, available N, available P, available K, available Ca, available Fe, available Zn, available B, and
pH, respectively. M1–M9denote mean annual temperature, total annual precipitation, monthly mean temperature from April to October, monthly
mean lowest temperature from April to October, monthly mean highest temperature from April to October, monthly mean temperature difference
between day and night from April to October, total precipitation from April to October, monthly mean relative humidity from April to October,
and monthly mean sunshine percentage from April to October, respectively
Regression Equation of Environmental Factors Affecting
Fruit Quality Traits
The value of VIP can only indicate the importance of en-
vironmental factors to fruit quality but cannot reflect the
positive or negative direction of their influence. To further
demonstrate the positive or negative effect of environmental
factors on fruit quality, regression equations for predicting
the effects of these environmental factors on each charac-
teristic factor of fruit quality were established, with major
environmental factors (VIP ≥0.8) as independent variables
and fruit quality traits as dependent variables (Table 4).
The pvalues of these regression equations were all less
than 0.05, meaning that the established regression equations
were stable and reliable. The coefficients and symbols of
the regression equations indicated the importance and the
positive or negative direction, respectively, for the effects
of different environmental factors on fruit quality traits. Re-
sults showed that the mean fruit weight was significantly
positively affected by M5but negatively affected by M4,
which indicated that the decrease in monthly mean highest
temperature or the increase in monthly mean lowest temper-
ature during the apple growing period was not beneficial to
fruit development. The fruit shape index was significantly
positively affected by M1but negatively affected by S10,in-
dicating the decrease in mean annual temperature or the
increase in soil pH was not beneficial to fruit shape im-
provement. The SSC was significantly positively affected
by S2but negatively affected by S10, which indicated that
orchard soil with higher total N and lower pH was bene-
ficial to sugar accumulation in fruits. In contrast to SSC,
fruit firmness was significantly positively affected by S10
but negatively affected by S2. The TA content was signifi-
cantly positively affected by S10 but negatively affected by
S9, which indicated that orchard soil with higher available
B and lower pH was beneficial to the decrease of fruit acid-
ity. The skin color area of apples was significantly positively
affected by S6but negatively affected by S8, which indicated
that orchard soil with higher available Ca and lower avail-
able Zn was beneficial to fruit color development.
Optimum Schemes of Environmental Factors for Good Fruit
Quality
To quantitatively illustrate the effects of environmental fac-
tors on fruit quality traits, linear programming equations
were constructed using the regression analysis in Table 4.
When solving the maximum value (MaxYn) of a certain fruit
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Quantitative Analysis of Relationship Between Fruit Quality of ‘Fuji’ Apple and Environmental Factors: A Case Study of the Loess... 429
Tab le 4 Regression equation of soil nutrition and meteorological factors affecting fruit quality traits
Objective functions aAffecting factor bRegression equation pPr>F
Y1S1,S7,M4,M5,M8,M9Y1= 266.644 – 1.3329S1+ 3.3497S7– 6.3246M4+ 3.404M5+ 0.9796M8– 2.0759M922.96 < 0.0001
Y2S1,S5,S8,S9,S10,M1,M2,M4,
M6,M8
Y2= 1.7374 + 0.00209S1– 0.00001538S5– 0.00412S8– 0.02619S9– 0.1036S10 + 0.00333M1–
0.0001255M2– 0.00446M4+ 0.000412M6+ 0.0008363M8
7.06 < 0.0001
Y3S1,S2,S3,S5,S8,S10,M1,M2,M3,
M7
Y3=–13.6263 – 0.04432S1– 0.7778S2+ 0.01813S3– 0.00003064S5+ 0.1091S8+ 2.6405S10 +
0.00622M1+ 0.00245M2+ 0.00647M3– 0.00102M7
9.82 < 0.0001
Y4S1,S2,S3,S4,S5,S7,S8,S10,M3,
M7
Y4= 32.8812 – 0.1391S1+ 1.938S2– 0.00284S3-0.00969S4– 0.00522S5+ 0.1804S7– 0.1107S8–
1.9247S10 + 0.03243M3– 0.00551M7
4.76 0.0003
Y5S1,S2,S8,S9,S10,M7,M8,M9Y5= –0.9427 + 0.0001345S1+ 0.04186S2+ 0.00318S8– 0.08279S9+ 0.1309S10 +
0.00007616M7– 0.00174M8+ 0.00299M9
19.31 <0.0001
Y6S4,S5,S6,S8,M3,M4,M5,M8Y6= 63.3856 + 0.01536S4+ 0.0022S5+ 15.8314S6– 19.2775S8+ 0.2784M3– 3.3131M4–
0.8261M5+ 0.2782M8
8.91 < 0.0001
aY1–Y6denote mean fruit weight, fruit shape index, fruit firmness, soluble solid content (SSC), titratable acid (TA) content, and skin color area, respectively
bS1–S10 denote soil organic matter (SOM), total N, available N, available P, available K, available Ca, available Fe, available Zn, available B, and pH, respectively. M1–M9denote mean annual
temperature, total annual precipitation, monthly mean temperature from April to October, monthly mean lowest temperature from April to October, monthly mean highest temperature from April to
October, monthly mean temperature difference between day and night from April to October, total precipitation from April to October, monthly mean relative humidity from April to October, and
monthly mean sunshine percentage from April to October, respectively
quality trait, the other fruit quality traits should be greater
than the mean values of 66 orchards to ensure high-qual-
ity fruits, and the environmental factors should be limited
to a certain constraint range. Due to the alkaline soil in
the Loess Plateau apple-production region, the soil pH was
restricted to be between 7.98 (the minimum in the 66 or-
chards) and 8.20 (the mean of the 66 orchards). The other
soil nutrition factors (S2–S10) were limited to the range from
the mean to the maximum values measured from 66 or-
chards, because they could be improved by some agricul-
tural practices, such as fertilization. The restraint ranges of
meteorological factors were the maximum and minimum
values measured from 66 orchards, because they could rep-
resent the real climate conditions in the Loess Plateau apple-
production region.
For example, the linear programming equations on the
maximum mean fruit weight (MaxY1) were as follows:
Max Y1= 266.644 − 1.3329S1+ 3.3497S7− 6.3246M4
+ 3.404M5+ 0.9796M8− 2.0759M9I
Y2= 1.7374 + 0.00209S1− 0.00001538S5− 0.00412S8
− 0.02619S9− 0.1036S10 + 0.00333M1
− 0.0001255M2− 0.00446M4+ 0.000412M6
+ 0.0008363M80.86I
Y3= − 13.6263 − 0.04432S1− 0.7778S2+ 0.01813S3
− 0.00003064S5+ 0.1091S8+ 2.6405S10 + 0.00622M1
+ 0.00245M2+ 0.00647M3− 0.00102M78.81I
Y4= 32.8812 − 0.1391S1+ 1.938S2− 0.00284S3
− 0.00969S4− 0.00522S5+ 0.1804S7− 0.1107S8
− 1.9247S10 + 0.03243M3− 0.00551M713.85I
Y5= − 0.9427 + 0.0001345S1+ 0.04186S2+ 0.00318S8
− 0.08279S9+ 0.1309S10 + 0.00007616M7
− 0.00174M8+ 0.00299M90.21I
Y6= 63.3856 + 0.01536S4+ 0.0022S5+ 15.8314S6
− 19.2775S8+ 0.2784M3− 3.3131M4− 0.8261M5
+ 0.2782M893.40I
Where, 13.94 ≤S1≤17.93, 0.77 ≤S2≤1.03, 68.39 ≤
S3≤115.87, 62.39 ≤S4≤124.67, 324.41 ≤S5≤534.67,
5.79 ≤S6≤6.54, 9.27 ≤S7≤14.97, 1.55 ≤S8≤2.72,
0.37 ≤S9≤0.90, 7.98 ≤S10 ≤8.2; 5.50 ≤M1≤18.00,
431.20 ≤M2≤713.80, 13.30 ≤M3≤19.90, 8.03 ≤M4≤
17.01, 19.63 ≤M5≤27.25, 7.31 ≤M6≤12.41, 338.30 ≤
M7≤589.80, 56.07 ≤M8≤82.41, 32.91 ≤M9≤55.87.
K
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430 Q. Zhang et al.
Tab le 5 Optimum schemes of soil nutrition and meteorological factors for good quality a
Affecting factor bY1
(g)
Y2Y3
(kg cm–2)
Y4
(%)
Y5
(%)
Y6
(%)
Range of optimum affecting
factors
S1(g kg–1) 13.94 17.93 13.94 17.93 13.94 13.94 13.94–17.93
S2(g kg–1) 1.03 1.03 0.77 1.03 1.03 1.03 0.77–1.03
S3(mg kg–1) 68.39 115.87 115.87 68.39 68.39 68.39 68.39–115.87
S4(mg kg–1) 124.67 62.39 62.39 62.39 62.39 124.67 62.39–124.67
S5(mg kg–1) 329.91 324.41 324.41 324.41 324.41 468.62 324.41–468.62
S6(mg kg–1) 6.54 6.54 6.54 6.54 6.54 6.54 6.54
S7(mg kg–1) 14.97 14.97 14.97 14.97 14.97 14.97 14.97
S8(mg kg–1) 2.51 1.55 2.72 1.55 2.72 1.55 1.55–2.72
S9(mg kg–1) 0.37 0.37 0.37 0.37 0.37 0.37 0.37
S10 8.2 7.98 8.2 7.98 8.2 8.2 7.98–8.2
M1(°C) 18 18 18 18 18 18 18
M2(mm) 713.8 431.2 713.8 713.8 713.8 713.8 431.2–713.8
M3(°C) 19.9 19.9 19.9 19.9 19.9 19.9 19.9
M4(°C) 8.03 8.03 8.03 8.03 8.03 8.03 8.03
M5(°C) 27.25 19.63 19.63 19.63 20.92 19.63 19.63–27.25
M6(°C) 12.41 12.41 12.41 12.41 12.41 12.41 12.41
M7(mm) 589.8 589.8 338.3 338.3 589.8 477.61 338.3–589.8
M8(%) 56.57 71.23 56.57 56.57 56.57 82.41 56.57–82.41
M9(%) 36.96 55.87 46.78 54.01 55.87 55.87 36.96–55.87
Objective value of fruit quali-
ties (Yn)
318.88 0.96 10.84 16.40 0.27 125.64 –
aY1–Y6denote mean fruit weight, fruit shape index, fruit firmness, soluble solid content (SSC), titratable acid (TA) content, and skin color area,
respectively
bS1–S10 denote soil organic matter (SOM), total N, available N, available P, available K, available Ca, available Fe, available Zn, available B, and
pH, respectively; M1–M9denote mean annual temperature, total annual precipitation, monthly mean temperature from April to October, monthly
mean lowest temperature from April to October, monthly mean highest temperature from April to October, monthly mean temperature difference
between day and night from April to October, total precipitation from April to October, monthly mean relative humidity from April to October,
and monthly mean sunshine percentage from April to October, respectively
The same method was performed to obtain the max-
imum of other fruit quality traits (Y2–Y6) when mean Y1
was ≥252.75 g, and then optimum schemes of environ-
mental factors for the largest value of fruit quality factor
were achieved (Table 5). According to theoretical optimum
schemes, the proposed optimum values of S6,S7,M1,M3,
and M6were the maximum of constraints, while those of
S9,andM4were the minimum of constraints. Furthermore,
the upper limit of the proposed optimum value of S10 was
the average value of measurement (8.2); the upper limit
of the proposed optimum S5was lower than the maximum
value of measurement; the lower limit of the proposed op-
timum value of M9was higher than the minimum value of
measurement.
The optimum environmental factors for high-quality
‘Fuji’ apples in the Loess Plateau production region were:
SOM, from 13.94 to 17.93 g kg–1; total N, from 0.77 to
1.03 g kg–1; available N, from 68.39 to 115.87 mg kg–1;
available P, from 62.39 to 124.67 mg kg–1; available K,
from 324.41 to 468.62 mg kg–1; available Ca, 6.54 mg kg–1;
available Fe, 14.97 mg kg–1; available Zn, from 1.55 to
2.72 mg kg–1; available B, 0.37 mg kg–1; soil pH, from
7.98 to 8.20; mean annual temperature, 18°C; total an-
nual precipitation, from 431.2 to 713.8 mm; monthly mean
temperature from April to October, 19.9°C; monthly mean
lowest temperature from April to October, 8.03 °C; monthly
mean highest temperature from April to October, from
19.63 to 27.25 °C; monthly mean temperature difference
between day and night from April to October, 12.41°C;
total precipitation from April to October, from 338.3 to
589.8 mm; monthly mean relative humidity from April to
October, from 56.57 to 82.41%; and monthly mean sun-
shine percentage from April to October, from 36.96 to
55.87%.
Discussion
Relationship Between Fruit Quality of ‘Fuji’ Apple
and Environmental Factors in the Loess Plateau
Production Region
The growth and development of apple trees and quality
formation of apple fruits are mainly determined by mete-
K
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Quantitative Analysis of Relationship Between Fruit Quality of ‘Fuji’ Apple and Environmental Factors: A Case Study of the Loess... 431
orological conditions, soil nutrition, cultivation techniques,
etc. In this study, the model effect weights of environmental
factors on overall fruit quality were obtained by analyzing
the relationship between 19 independent variable parame-
ters (S1–S10,andM1–M9) and six fruit quality factors (Y1–Y6).
According to the results, we proposed for the first time that
the effect of soil nutrition factors (55.99%) on fruit quality
was greater than that of meteorological factors (44.01%) in
the Loess Plateau production region of China. Thus, un-
der similar landform types and soil textures, the difference
in ‘Fuji’ fruit quality of vigorous apples was due to the
varying meteorological factors in the Loess Plateau apple-
producing region.
This study found that the mean fruit weight of vigor-
ous apple was significantly affected by sunshine, humidity,
temperature (the highest temperature and the lowest tem-
perature), and SOM content during the growing period, and
it was significantly positively affected by M5and negatively
affected by M4. We found that the lower maximum temper-
ature and the higher minimum temperature in the apple-
growing period were not good for fruit development, which
was consistent with the results reported by Forshey (1990).
A possible reason is that the temperature at the early grow-
ing stage of apples directly affected the growth of the apple
tree, and then influenced the numbers of fruit cells and the
distribution of photosynthetic products to fruit (Austin et al.
1999). The fruit shape index was remarkably affected by S5,
S8,S10,M1,andM8,ofwhichM1had the largest positive ef-
fect, but this was different from the results of Warrington
et al. (1999). Fruit shape index is affected by cell divi-
sion at the early stage of fruit development (Goffinet et al.
1995), thus the effect of monthly or 10-day temperature
factors on fruit development should be further studied. The
fruit firmness was significantly affected by S2,S3,S5,M2,
and M3, with S2having the largest negative effect among
them, from which we can speculated that the decrease in
fruit firmness was due to high soil nitrogen and reduced
calcium content in fruit (John et al. 2007), or was due to
insufficient soil nitrogen that inhibited fruit expansion. In
addition, fruit firmness was also negatively affected by soil
available K, which was consistent with the results of Fal-
lahi et al. (2010), who used integrated fertilizer and wa-
ter technology to study the effect of potassium on apple
fruit firmness. The factor M3was the most important mete-
orological factor related to SSC and influenced SSC posi-
tively, which was consistent with the results of Sugiura et al.
(2013) and Warrington et al. (1999). This might be because
the increased temperature during the apple-growing period
promoted apple trees to flower and ripen early. The factor
S2had the greatest positive effect on SSC, which might be
due to the low total N content (0.77g kg–1)oforchardsoil
in the Loess Plateau production region. But this result was
contrary to the results of John et al. (2007), who based their
conclusion on the long-term and large-scale application of
nitrogen fertilizer on fruit quality of ‘Golden Delicious’ ap-
ple. The factor S10 had the greatest negative effect on SSC,
while S7had the larger positive effect on SSC. In alkaline
soil, soluble ferric iron is converted into insoluble ferric
iron and precipitated, so that the iron cannot be utilized
by the roots of fruit trees, thereby affecting tree growth
and fruit quality improvement. The TA content was signif-
icantly positively affected by S10 but negatively affected by
S9, which indicated that the soil with high boron content
and low pH was beneficial for decreasing fruit acidity in
the Loess Plateau production region. This might be due to
the fact that soil available boron was negatively correlated
with soil pH, and the boron activity of the soil solution in-
creased as soil pH decreased (Keren et al. 1985). In other
words, the soil available boron that could be absorbed by
apple trees was increased, thereby increasing fruit acidity.
The temperature factors (the highest temperature and the
lowest temperature) during the apple-growing period were
particularly important for fruit color development, showing
that there was a close relationship between apple fruit color
and the day and night temperature of different months dur-
ing the growing period. This result was consistent with the
results reported by Lakatos et al. (2012). Besides, the fruit
skin color area was significantly positively affected by S4,
S5and S6, which was consistent with the results of Siddique
et al. (2009), Fallahi et al. (2010), and Bizjak et al. (2013).
In our study, we found that S10 had the greatest positive ef-
fect on fruit firmness, but it had the greatest negative effect
on fruit shape index and SSC, which has not been reported
to date.
Schemes of Optimum Environmental Factors for
Good-Quality ‘Fuji’ Apple in the Loess Plateau
Production Region
The combination of PLSR analysis and linear programming
was used to optimize environmental factors for high-qual-
ity ‘Fuji’ apples in the Loess Plateau production region.
The optimum SOM content (13.94–17.93g kg–1) for good
fruit quality production of vigorous apples was basically
consistent with a previous study (Liu et al. 2006)inwhich
SOM content in good-quality and high-yield apple orchards
was above 1.5%. The lower limit value (13.94g kg–1)of
optimum SOM was close to the value (14.15g kg–1)of
well-managed apple orchards in the Circum-Bohai region
(Zhang et al. 2017), but it was higher than values reported
in Weibei, Shaanxi Province (Wang et al. 2007; Zhang
2012), in the Loess Plateau production region (Zhang D.
et al. 2016), and in Jiaodong, Shandong Province (Wang
et al. 2008). The upper limit value (17.93 g kg–1)waslower
than the value (20.41 g kg–1) of well-managed orchards in
Changping County of Beijing (Zhang et al. 2011a, b), and
K
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432 Q. Zhang et al.
also lower than the values (3.1%, 2.0%) of apple orchards
under comprehensive (IFP) and organic (OFP) management
in New York State (Peck et al. 2011). The lower limit
value of optimum soil total N content (0.77 g kg–1)inthis
study was higher than previous survey data in the Loess
Plateau production region (Zhang et al. 2013, Zhang D.
et al. 2016); the upper limit value (1.03g · kg–1)waslower
than the survey data (2.1 g · kg–1) in the apple orchards of
Punjab region of Pakistan (Khattak and Hussain 2007),
and was also lower than the average value (1.53g · kg–1)
of a well-managed apple orchard in Changping County of
Beijing (Zhang et al. 2011a, b). The soil available N con-
tent measured in the study was basically consistent with
previous survey results (Wang et al. 2008; Zhang et al.
2013; Zhang D. et al. 2016), while the lower limits of
soil available P and K contents were higher than previ-
ous survey results (Siddique et al. 2009;Wangetal.2008;
Zhang et al. 2013; Zhang D. et al. 2016). The optimum
soil available Ca content (6.54 mg kg–1) was higher than
previous survey results (Siddique et al. 2009; Zhang et al.
2011a, b; Zhang D. et al. 2016). The optimum soil avail-
able Fe content (14.97mg kg–1) and available Zn content
(1.55–2.72 mg kg–1) were higher than the values of 108
‘Fuji’ orchards in 12 dominant apple-producing counties
in the Loess Plateau production region (Zhang D. et al.
2016) but were lower than the survey results of well-man-
aged apple orchards in Changping county of Beijing (Zhang
et al. 2011a, b). The optimum soil available B content
(0.37mg·kg
–1) was lower than the value (0.734mg · kg–1)
of well-managed apple orchards of Changping county in
Beijing (Zhang et al. 2011a, b).
In the present study, the optimum value (18°C) of mean
annual temperature for the production of good-quality vig-
orous apples in the Loess Plateau production region was
higher than the values (7–14°C) reported previously, such
as those by Lu (1980), Huang (1990), Wang and Yin (1992),
Zhang (1994), and Duan et al. (2014). The optimum value
(19.9 °C) of monthly mean temperature from April to Oc-
tober was close to the upper limit of monthly mean temper-
ature (15.5–19.7 °C) in Weibei of Loess Plateau (Qu et al.
2008) but was higher than that in other regions. For exam-
ple, the mean temperature during the apple-growing period
in Aksu prefecture, Xinjiang (Liu and Mao 2001) was in the
range of 12–18 °C, and the monthly mean temperature from
April to October in the dominant apple-producing regions
of northeast China, north China, and northeast China (Qu
et al. 2008), and for good fruit quality of ‘Pink Lady’ apple
in Weibei of Loess Plateau (Gao et al. 2009)thevalueswere
16.2–18.7 °C and 15.5 °C respectively. The optimum value
(8.03 °C) of the monthly mean lowest temperature from
April to October was higher than the monthly mean lowest
temperature during the growing period (7.2°C) for high-
quality ‘Fuji’ apple production in Hebei Province, China
(Li et al. 2009). The optimum value (12.41 °C) of monthly
mean temperature difference between day and night from
April to October met the criterion (≥10 °C) o f h igh-quality
apple ecological regions (Zhang 1994) but was higher than
the results of other studies (e.g., Wei et al. 2003; Zhu et al.
2001). Compared with previous studies (Liu and Mao 2001;
Wang et al. 2000b), this study obtained a broader range of
total annual precipitation for high-quality ‘Fuji’ apple pro-
duction in the Loess Plateau production region. However,
the lower limit (431.2 mm) and the upper limit (713.8 mm)
were, respectively, lower than the lower and upper limits of
the total annual precipitation (501–800 mm) proposed by
Li et al. (1985). The range of optimal total annual precipi-
tation from April to October (338.3–589.8 mm) was larger
than the results of Zhang (1994) and Wang et al. (2000b).
The optimal monthly mean relative humidity from April to
October was 56.1–82.4%. The range was wider than the op-
timal relative humidity of 60–70% and 65.1–73.3% reported
by Zhu et al. (2001) and Duan et al. (2014), respectively,
for ‘Fuji’ apple, and the upper limit was higher than the
results (≤70%) reported by Li et al. (2000).
Restrictive Environmental Factors and
Countermeasures for High-Quality Apple Production
in the Loess Plateau Production Region
The difference between the measured value and theoreti-
cal value indicated that the lower monthly mean tempera-
ture difference between day and night, lower mean annual
temperature and monthly mean temperature, and higher
monthly mean lowest temperature during the apple-growing
period, together with the low contents of soil available Ca
and Fe, the high content of soil available B, and serious soil
alkalization were the restrictive environmental factors for
apple production in the Loess Plateau production region.
In addition, suitable sunshine percentage (36.96–55.87%)
during the apple-growing period and suitable soil available
K content (324.41–468.62 mg kg–1) also had an important
effect on ‘Fuji’ fruit quality.
In view of the large differences of soil nutrition, meteo-
rological factors, and apple fruit quality traits in the Loess
Plateau production region, and taking into account the ef-
fect weights of soil nutrition and meteorological factors on
fruit quality, as well as the restrictive soil nutrition and me-
teorological factors for high-quality apple through optimum
schemes, ‘Fuji’ apple is recommended to be popularized in
regions with higher mean annual temperature, and higher
monthly mean temperature, larger monthly mean tempera-
ture difference between day and night, lower monthly mean
lowest temperature and suitable sunshine percentage during
the growing period. For orchard in non-eugenic regions,
the micro-climate could be improved by certain agricul-
tural measures to respond to restrictive meteorological fac-
K
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Quantitative Analysis of Relationship Between Fruit Quality of ‘Fuji’ Apple and Environmental Factors: A Case Study of the Loess... 433
tors in the Loess Plateau production region. For instance,
black fabric mulching along tree rows can increase ground
temperature; micro-spray mist can reduce the temperature
of the orchards at night, expand the temperature difference
between day and night, and weaken the respiration of fruit
trees, which are beneficial to fruit organic matter accumu-
lation and sugar conversion; reflective film mulching in the
fruit-ripening stage can be used to increase the daytime tem-
perature, reduce the nighttime temperature, and expand the
temperature difference between the day and night, which
is beneficial to fruit organic matter accumulation and color
development. In addition, soil management measures are
necessary for the production of high-quality ‘Fuji’ apples,
such as reducing soil pH and available B content, increas-
ing the content of soil available Ca and Fe, and adjusting
soil available K content.
It should be pointed out that apple quality is the result of
multiple factors such as apple lines, climate–soil ecological
environment, cultivation and management measures, among
others (Yu et al. 1988). This study only focused on the ma-
jor environmental factors associated with ‘Fuji’ fruit qual-
ity of vigorous apples, and the obtained optimum schemes
are only theoretical; thus, the other environmental factors
and the theoretical schemes obtained need to be further ex-
plored, in particular the optimum values of soil nutrition
need to be verified or adjusted in practice. And finally, we
should achieve a reasonable formula fertilization.
Conclusion
The effect of meteorological factors (55.99%) on fruit qual-
ity was greater than that of soil nutrition factors (44.01%) in
the Loess Plateau apple-producing region of China. ‘Fuji’
apple should be cultivated in regions with higher mean an-
nual temperature and higher monthly mean temperature,
larger monthly mean temperature difference between day
and night, lower monthly mean temperature, and suitable
sunshine percentage during the growing period. The restric-
tive factors of high-quality ‘Fuji’ apples in the Loess Plateau
production region were the lower content of soil available
Ca and Fe, higher content of soil available B, and serious
soil alkalization in some orchards.
Funding National Key R&D Program of China (2019YFD1001401);
China Agriculture Research System (CARS-27).
Conflict of interest Q. Zhang, M. Li, B. Zhou, J. Zhang and Q. Wei
declare that they have no competing interests.
Open Access This article is licensed under a Creative Commons At-
tribution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long as
you give appropriate credit to the original author(s) and the source, pro-
vide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included
in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view
a copy of this licence, visit http://creativecommons.org/licenses/by/4.
0/.
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