This study examined the effects of dry cultivation and rice cultivar on starch synthesis and grain quality traits in different parts of the rice panicle. Three rice cultivars - a high-quality cultivar (Huanghuazhan), a drought-resistant cultivar (IRAT109), and a drought-susceptible cultivar (Zhenshan97) - were grown under both flooding irrigation and dry cultivation. Under dry cultivation, the drought-resistant and susceptible cultivars showed lower rice quality, especially in appearance and cooking quality. The upper panicle of Huanghuazhan under dry cultivation had the highest appearance, nutritional and cooking quality among all cultivars and treatments, due to its synthesis of more short

1. Carbohydrate Polymers 269 (2021) 118336
Available online 16 June 2021
0144-8617/© 2021 Elsevier Ltd. All rights reserved.
Dry cultivation and cultivar affect starch synthesis and traits to define rice
grain quality in various panicle parts
Zongkui Chen, Ping Li, Yunfeng Du, Yang Jiang, Mingli Cai, Cougui Cao *
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
A R T I C L E I N F O
Keywords:
Head rice
Chalkiness
Starch granules
Amorphous regions
Retrogradation
A B S T R A C T
A pot experiment was conducted to explore the effects of high-quality (Huanghuazhan, HH), drought-resistant
(IR, IRAT109) and drought-susceptible cultivars (ZS, Zhenshan97) under flooding irrigation and dry cultiva­
tion (D) on the starch accumulation and synthesis, physicochemical traits of starch granules and rice grain
quality at the upper (U) and lower panicle. Under D treatment, IR and ZS had lower rice quality, especially the
appearance and cooking quality. DHH-U had the highest appearance, nutritional and cooking quality among all
cultivars under D treatment, which could be ascribed to the synthesis of more short-branch chain amylopectin
and correspondingly higher starch granule tightness. DHH-U also maintained ordered carbohydrate structure,
crystalline regions, and many hydrophilic and hydrophobic functional groups in starch granules before pasting. It
could prevent the polymerization of small molecules to avoid the formation of macromolecules after pasting.
Overall, these findings may facilitate the improvement of grain quality in rice dry cultivation.
1. Introduction
Rice (Oryza sativa L.) provides about 20% of the daily calorie intake
for over half of the world's population (Zheng et al., 2018). In the
Yangtze River Basin of China, rice planting area and production
accounted for 9.4% and 14.1% of the world total, respectively (FAO­
STAT, 2018; National Bureau of Statistics of China, 2018). In this region,
about 50% of freshwater is consumed for flooding irrigation (Ye et al.,
2013). Frequent regional or seasonal droughts, underdeveloped agri­
cultural mechanization and decreases in agricultural labor force have
posed great challenges to the development of rice production in this
region (Chen et al., 2021). Rice dry cultivation was introduced to
address these challenges (Chen et al., 2021). However, under this
cultivation mode, the grain quality (processing, appearance and nutri­
tional quality) is usually compromised.
Rice quality traits comprise processing, appearance, cooking and
nutritional quality (Gong et al., 2017; Zhou et al., 2018). Yields of whole
brown and head rice are important indicators of the processing quality.
Whole brown and head rice grains also have higher market values than
broken rice grains in milling industry (Zhou et al., 2015). Chalkiness and
chalky grain rate indicate the appearance quality, which can affect the
processing properties and appearance of rice grains (Gong et al., 2017;
Zhou et al., 2018). Cooking quality is mainly reflected by the pasting
viscosity (including breakdown, setback and retrogradation value). A
higher breakdown value and lower setback value mean hard rice grains
after cooking, which possibly contribute to good taste (Varavinit et al.,
2003). Amylose and proteins are the main determinants of nutritional
quality (Rana et al., 2020). Rice quality traits are largely determined by
the starch, which accounts for 80% of the total mass of rice grains
(Syahariza et al., 2013). Starch in rice grains mainly exists in the form of
starch granules (Syahariza et al., 2013; Zhu et al., 2017). The internal
molecular structure and physicochemical properties of starch granules
are strongly influenced by the accumulation form of amylose and
amylopectin (Goldstein et al., 2017; Vamadevan & Bertoft, 2020).
The synthesis and conversion of amylose and amylopectin are
determined by many key enzymes. For example, sucrose synthase
(SuSase) regulates the synthesis of UDP-glucose from sucrose for the
initiation of starch synthesis. UDP-glucose pyrophosphorylase (UDP­
Gase) and ADP-glucose pyrophosphorylase (ADPGase) support the
accumulation of key substrates for starch synthesis. Granule-bound
Abbreviations: ADPGase, ADP-glucose pyrophosphorylase; D, rice dry cultivation; DBE, starch debranching enzyme; F, flooding irrigation; GBSSase, granule-
bound starch synthase; GT, gelatinization temperature; HH, Huanghuazhan cultivar; IR, IRAT109 cultivar; L, lower panicle; SBE, starch branching enzyme; SSSase,
soluble starch synthase; SuSase, sucrose synthase; U, upper panicle; UDPGase, UDP-glucose pyrophosphorylase; ZS, Zhenshan97 cultivar.
* Corresponding author.
E-mail address: ccgui@mail.hzau.edu.cn (C. Cao).
Contents lists available at ScienceDirect
Carbohydrate Polymers
journal homepage: www.elsevier.com/locate/carbpol
https://doi.org/10.1016/j.carbpol.2021.118336
Received 29 November 2020; Received in revised form 30 May 2021; Accepted 9 June 2021

2. Carbohydrate Polymers 269 (2021) 118336
2
starch synthase (GBSSase) starts the synthesis and extension of long
chains in amylose, while soluble starch synthase (SSSase) dominates the
synthesis and extension of amylopectin. Starch branching enzyme (SBE)
acts on the branching and separation of GBSSase from the chain. Starch
debranching enzyme (DBE) removes the improper branch of amylo­
pectin or collaborates with GBSSase to synthesize amylose (Ball &
Morell, 2003; Tian et al., 2009).
Soil moisture conditions affect the activities of these key enzymes.
For instance, intermittent drought stress could increase GBSSase and
SBE to facilitate the synthesis of starch in the grains and accelerate grain
filling (Dong et al., 2014; Rose et al., 2020). The activities of these key
enzymes are also associated with the position of the grains in the
panicle. For example, the activities of ADPGase, SuSase and SBE in
inferior spikelets are lower than those in superior spikelets under
drought stress, which correspondingly leads to a lower grain filling rate
(Dong et al., 2014). Hence, it is important to define the relationship of
amylose/amylopectin synthesis and the physicochemical properties of
starch granules with rice quality traits in different panicle positions. The
findings may help to further improve rice quality under dry cultivation.
In recent years, high-yield rice cultivars have been gradually used to
replace drought-resistant rice cultivars to further improve the grain
yield in regions with inadequate rainfall (Chen, Yang, & Song, 2020;
Luo, 2010). Some high-yield rice cultivars (such as Huanghuazhan) also
produce grains with high processing and appearance quality under
drought stress (Chen et al., 2013; Chen, Chen, et al., 2020). Hence, it is
imperative to dissect the physiological mechanism of rice quality traits
in high-yield and high-quality rice cultivars under dry cultivation, so as
to relieve the conflict between grain quality and water utilization. In this
study, by taking high-yield, drought-resistant and drought-susceptible
rice cultivars as the subjects, we dissected the physiological mecha­
nism of rice quality traits under dry cultivation by analyzing the activ­
ities of amylose and amylopectin biosynthesis enzymes, as well as the
physicochemical traits of starch granules at different panicle positions.
2. Materials and methods
2.1. Study site
From May to November in 2018, a pot experiment was carried out in
a greenhouse (temperature: 27–33 ◦
C) at Huazhong Agricultural Uni­
versity (E114◦
29′
, N30◦
29′
), Hubei Province, China. The soil of the plot
(30 cm in height and 40 cm in diameter; filled with 21 kg dry soil per
pot) was paddy soil, with pH = 7.40, 11.3 g kg− 1
organic matter, 107.9
mg g− 1
total N, 72.5 mg g− 1
total P, 11.7 mg g− 1
total K, 31.32 mg kg− 1
available P and 163.5 mg kg− 1
available K.
2.2. Experimental design
A randomized block design with 60 replicates per treatment was
employed. Two water treatments were assigned: 1) conventional
flooding irrigation (F), in which seedlings were raised under shallow
water (<1 cm) for 20 days, and then a 3–5 cm water layer was main­
tained from transplanting to a week before harvest; and 2) rice dry
cultivation (D), in which manual direct seeding was carried out in the
soil at − 10 ± 5 kPa of soil water potential, and then the soil water po­
tential was maintained at − 30 ± 5 kPa until the mature stage. Each
water treatment was assigned with three cultivars: 1) high-yield and
high-quality conventional indica rice Huanghuazhan (HH); 2) drought-
resistant conventional indica rice IRAT109 (IR); and 3) drought sus­
ceptible indica rice Zhenshan 97 (ZS) (China Rice Data Center, 2014).
2.3. Field management and plant cultivation
In the F treatment, on the 25th in May, 20-day-old rice seedlings
were transplanted. In the D treatment, manual direct seeding was con­
ducted on the 29th of May. In each treatment, two hills (double
seedlings per hill) were maintained for each pot with a spacing of 10 cm
between hills. Nitrogen was applied for three times with the following
schedule: 50% as a basal application, 20% at the tillering stage, and 30%
at the panicle initiation stage. All the P and K fertilizers were only
applied as a basal application. The basal dose of compound fertilizer
(16% N, 16% P, 16% K) provided 0.14 g N, P and K per kg dry soil. Urea
(46.7% N) provided 0.056 g N and 0.084 g N kg− 1
dry soil as tillering
and panicle fertilizer, respectively. The pots were regularly hand wee­
ded, and insecticides were applied to control insect pests.
2.4. Experimental conditions and procedures
2.4.1. Preparation for determination
There were two hills per pot: one for the collection of dry grains and
the other for the collection of fresh grains, and six repetitions were
carried out. The panicle was first equally divided into the upper (U) and
lower part (L), and dry or fresh grains were collected from the upper and
lower parts, respectively (Zhai et al., 2020) at 2, 7, 12, 17 and 27 days
after anthesis (DAA). Dry grain sample was oven dried at 80 ◦
C (BPZ-
6020 LC, Shanghai Huanjing Test Equipment Factory, China) to a con­
stant weight. Then, the dry grains were shelled and ground to fine
powder using a mixer mill (MM 400, Retsch, USA) with a zirconia bead
for 1.5 min at 30 Hz and passed through a 0.15 mm sieve for the
determination of sucrose, soluble sugar and starch contents. Fresh grain
samples were immediately frozen in liquid nitrogen and then stored at
− 80 ◦
C for enzyme assays after shelling. After the grains were mature
(about 30–35 DAA), grains from 20 to 30 plants (about 50 g of grains)
were collected in each treatment. The collected grains were equilibrated
in paper bags at room temperature (25 ± 5 ◦
C) for about three months
and the water content (determined using a MJ33 Moisture Analyser
(Mettler-Toledo, Switzerland)) was controlled at 12–14% for measure­
ment of the processing and appearance quality traits. Then, a Tornado
Crush Mill (JFS-13 A, Qingdao Joyjun Medical Products, China) was
used to produce rice flour from head rice, which was then passed
through a 0.15 mm sieve for the measurement of viscosity property,
amylose content, proteins and total flavonoids, X-ray diffraction anal­
ysis, and the FTIR spectral analysis of rice flour before cooking. In
addition, rice flour after cooking (high viscous starch colloid, about
30–40 ◦
C) was also examined with FTIR.
2.4.2. Sucrose, soluble sugar and starch contents
The contents of sucrose, soluble sugar and starch (mg g− 1
of dry
brown rice weight) were quantified by the anthrone colorimetric
method reported by Gao (2006), as presented in the Supplementary
material. In brief, 0.1 g rice flour sample was extracted by 5.0 mL 80%
ethanol at 80 ◦
C for 30 min. After repeated extraction and centrifugation
(6000 ×g for 5 min) for three times, the supernatant (testing solution)
was combined and the volume was adjusted to 100 mL. Aliquots (2 mL)
of the extract were analyzed for sucrose and soluble sugar content. The
remaining precipitate was used for the determination of starch content.
For the measurement of starch content, the precipitate after extrac­
tion of sucrose and soluble sugar was added with 2.0 mL water, and the
starch was gelatinized at 100 ◦
C for 15 min. Then, the sample was mixed
with 2.0 mL 9.2 M perchloric acid and 2.0 mL distilled water and
centrifuged (6000 ×g for 5 min). To the supernatant, 2.0 mL 4.6 M
perchloric acid was added. After the volume was adjusted to 100 mL
with distilled water, 1.0 mL solution was mixed with 2.0 mL distilled
water and 5.0 mL chromogenic reagent. Absorbance was then measured
at 620 nm.
For the determination of sucrose content, 2.0 mL of the testing so­
lution was mixed with 2.0 mL of distilled water and 2.0 mL of 2.0 M
KOH. After preincubation at 100 ◦
C for 5 min, 1.0 mL of the solution was
mixed with 2.0 mL of distilled water and 5.0 mL of chromogenic reagent.
The absorbance was then determined at 620 nm.
For the measurement of soluble sugar content, 1.0 mL of the testing
solution was mixed with 2.0 mL of distilled water and 5.0 mL of
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3. Carbohydrate Polymers 269 (2021) 118336
3
chromogenic reagent. After 2 min, the absorbance was determined at
620 nm.
2.4.3. Activities of starch synthesis enzymes
The activities of sucrose synthase (SuSase), UDP-glucose pyrophos­
phorylase (UDPGase) and ADP-glucose pyrophosphorylase (ADPGase)
were measured according to Schaffer and Petreikov (1997) and Sun­
dukova et al. (2000). The activities of soluble starch synthase (SSSase),
granule-bound starch synthase (GBSSase), starch branching enzyme
(SBE) and starch debranching enzyme (DBE) were determined according
to Nakamura et al. (1989) and Zhang et al. (2007). One unit of enzyme
activity was defined as the amount that causes one unit absorbance
increment per g of fresh weight per min, except for DBE, whose activity
was measured with the production of 1.0 mg reducing sugar per min as
the unit. The brief procedures are provided below and the detailed
procedures are presented in the Supplementary material.
Fresh grain sample (0.1 g) was homogenized, to which 1.0 mL
extraction solution (4 ◦
C, the extracting solution for each enzyme was
different) was added. After centrifugation (50,000 ×g for 5 min at 4 ◦
C),
the supernatant was used as the crude enzyme extract to determine the
activities of SuSase, UDPGase, ADPGase, SSSase, SBE and DBE. The
precipitate after the extraction of crude enzyme of SSSase was resus­
pended with 1.0 mL extraction solution. The resuspension was then used
for the determination of GBSSase activity.
For the determination of SuSase activity, to 1.0 mL reaction mixture
containing 100 mM Hepes-NaOH (pH 7.5), 2.0 mM Mg (CH3COO)2, 5.0
mM DTT, 0.02 mM glucose 1, 6-diphosphate, 0.5 mM NADH, 2.0 U
phosphoglucomutase and 2.0 U glucose 6-phosphate dehydrogenase, 50
μL crude enzyme extract was added. After preincubation at 30 ◦
C, the
reaction was initiated by the addition of 50 mM sucrose, 1.0 mM UDP
and 1.0 mM PPi. Then, the absorbance was monitored at 340 nm for 5
min.
For the determination of UDPGase activity, to 1.0 mL reaction
mixture containing 100 mM Hepes-NaOH (pH 7.5), 2.0 mM MgCl2, 5.0
mM DTT, 0.02 mM glucose 1, 6-diphosphate, 0.5 mM NADH, 1.0 mM
UDPG, 2.0 U phosphoglucomutase, and 2.0 U glucose 6-phosphate de­
hydrogenase, 50 μL crude enzyme extract was added. After pre­
incubation at 30 ◦
C, 1.0 mM PPi was added to initiate the reaction. The
absorbance was measured at 340 nm for 1 min.
For the measurement of ADPGase activity, to 1.0 mL reaction
mixture containing 100 mM Hepes-NaOH (pH 7.5), 2.0 mM MgCl2, 5.0
mM DTT, 0.02 mM glucose 1, 6-diphosphate, 0.5 mM NAD, 1.0 mM
ADPG, 2.0 U phosphoglucomutase, 2.0 U glucose 6-phosphate dehy­
drogenase, 50 μL of crude enzyme extract was added. After pre­
incubation at 30 ◦
C, the reaction was initiated by the addition of 1.0 mM
PPi. The absorbance was monitored at 340 nm for 5 min.
For the measurement of SSSase and GBSSase activities, to 280 μL
reaction mixture containing 50 mM Hepes-NaOH (pH 7.4), 1.6 mM ADP
and 0.7 mg amylopectin, 15 mM DTT and 50 μL crude enzyme extract
(the re-suspended precipitate for GBSSase) were added. The enzyme was
inactivated by boiling in a water bath for 0.5 min, followed by the
addition of 100 μL solution containing 50 mM Hepes-NaOH (pH 7.4),
4.0 mM PEP, 200 mM KCl, 10 mM MgCl2 and 1.2 U pyruvate kinase, and
incubation for 30 min at 30 ◦
C. After incubation in boiling-water bath
for 5 min and centrifugation (10,000 ×g), 300 μL supernatant was mixed
with 300 μL reaction solution of 50 mM Hepes-NaOH (pH 7.4), 10 mM
glucose, 20 mM MgCl2, and 2.0 mM NADP. Then, the absorbance at 340
nm was measured after the addition of hexokinase and 0.35 U glucose 6-
phosphate dehydrogenase.
To determine the SBE activity, to 200 μL reaction mixture containing
50 mM Hepes-NaOH (pH 7.4), 5.0 mM glucose 1-phosphate, 1.25 mM
AMP and phosphorylase (54 U), 50 μL crude enzyme extract was added.
The reaction was terminated by the addition of 50 μL 1.0 M HCl. Then,
the solution was mixed with 300 μL of dimethylsulfoxide and 700 μL of
0.1% I2 and 1.0% KI, followed by absorbance determination at 540 nm.
For the measurement of the DBE activity, 100 μL crude enzyme
extract was added into 1.0 mL reaction mixture containing 100 mM
Hepes-NaOH (pH 7.5) and 2.0 mg pullulan, followed by incubation at
30 ◦
C for 20 min. The reaction was terminated by boiling water bath for
1.5 min. Then, 0.825 mL 3,5-dinitrosalicylic acid was added and the
mixture was incubated in a boiling-water bath for 5 min. The absorbance
at 540 nm was measured after the addition of 3.713 mL deionized water.
2.4.4. Determination of whole brown and head rice, chalkiness and chalky
grain rate
Grains with moisture contents of approximately 12–14% were first
dehulled using a Yamamoto Impeller Type Husker (FC-2 K, Yamamoto,
Japan) to produce brown rice. The whole brown rice was the percentage
of whole brown rice weight in the total grain weight. The whole brown
rice grains were further processed about 60 s by a Yamamoto Whitener
(VP-32 T, Yamamoto, Japan) to obtain head rice grains. The whole head
rice rate refers to the percentage of whole head rice weight in the total
grain weight. Chalkiness is the percentage of chalky area in a projected
area of rice grains, and chalky grain rate is the percentage of chalky
grain number in total head rice grains, which were both determined
using a Rice Inspector (ES-1000, Shizuoka, Japan).
2.4.5. Rice flour viscosity properties
Rice flour viscosity properties were determined using a Rapid Visco-
Analyser (RVA-4, Newport Scientific, Australia). The viscosity values
were recorded as rapid viscosity units (cP), including peak paste vis­
cosity, hot paste viscosity, cold paste viscosity and gelatinization tem­
perature (GT). The breakdown value was calculated by subtracting the
hot paste viscosity from the peak paste viscosity. The setback value was
obtained by subtracting the peak paste viscosity from the cold paste
viscosity. The retrogradation value was determined by subtracting the
hot paste viscosity from the cold paste viscosity (Chen, Chen, et al.,
2020; Han et al., 2004).
2.4.6. FTIR spectral analysis of rice flour
To analyze the FTIR spectra of the rice flour, samples from head rice
were analyzed using the Fourier Transform Infrared Spectrometer (PIKE
Technologies, Pikeville, USA). There were three replicates in each
treatment, and each sample in each treatment was repeated for three
times. The scanning range was 400–4000 cm− 1
with resolution of 4
cm− 1
, and 64 spectra were averaged (Duan et al., 2020). The bands at
1045 cm− 1
, 1022 cm− 1
and 995 cm− 1
were sensitive to the crystalline
regions, the amorphous regions and the bonding in hydrated carbohy­
drate helices in starch granules, respectively. The ratios of 1045/1022,
1022/995 and 1045/995 were respectively used to determine the degree
of order, as well as the proportions of amorphous regions to carbohy­
drate structure and crystalline regions to carbohydrate structure (Sev­
enou et al., 2002; Zhu et al., 2017). Besides, FTIR spectra were also used
to identify the functional groups in rice flour samples before or after
pasting according to their specific reflection peaks at different bands as
described by Widjanarko et al. (2011), Falade and Christopher (2015)
and Fumoto et al. (2020). The specific reflection peaks of the functional
groups are shown in Supplementary material.
2.4.7. Amylose and total flavonoid contents
The amylose content in rice flour was analyzed by using the iodine
reagent method (Chen, Chen, et al., 2020; Kong et al., 2015). The
amylose content (g) per g of dry rice flour weight was used to represent
the amylose content (%). Total flavonoid content was determined using
a colorimetric method according to Chlopicka et al. (2012), and the
results were expressed as total flavonoid (g) per g of dry rice flour
weight. The detailed procedures for the measurement of amylose and
total flavonoid contents are presented in the Supplementary material,
and the brief determination steps are as follows.
For the measurement of amylose content, 10 mL 0.5 M KOH was
added to 1.0 g rice flour sample, followed by the addition of 5.0 mL 1.0
M HCl and 0.5 mL iodine reagent. After adjustment to 100 mL with
Z. Chen et al.

4. Carbohydrate Polymers 269 (2021) 118336
4
distilled water, the absorbance was measured at 620 nm after 20 min.
For the measurement of total flavonoid content, 0.1 g rice flour was
added with 0.25 mL 80% methanol, and then mixed with 1.25 mL
distilled water. After the addition of 0.075 mL 0.05 g L− 1
NaNO2 and
0.15 mL 0.10 g mL− 1
AlCl3 solution, the solution was mixed with 0.5 mL
1.0 M NaOH and distilled water. The absorbance of the mixture was
immediately measured at 510 nm.
2.4.8. Extraction of rice storage proteins
The albumin, globulin, glutelin and prolamin in the flour of head rice
were extracted according to the method of Agboola et al. (2005), and
then the contents were determined with the Coomasie Blue G250
method (Bradford, 1976). The detailed procedures are presented in the
Supplementary material. The results were expressed as weight per­
centage of protein in dry rice flour.
For the measurement of albumin, 1.0 g of rice flour sample was
repeatedly extracted with 10 mL, 8.0 mL and 5.0 mL distilled water
respectively for 1 h. After three times of extraction and centrifugation
(10,000 ×g for 5 min), the supernatant was combined and used to
determine the albumin content after fixing of the volume (25 mL).
The precipitate after the extraction of albumin was then repeatedly
extracted with 10 mL, 8.0 mL and 5.0 mL 0.5 M NaCl respectively for 1 h.
After extraction and centrifugation (10,000 ×g for 5 min) for three
times, the supernatants were combined to fix the volume (25 mL) for the
measurement of globulin content.
The precipitate after the extraction of globulin was repeatedly
extracted with 10 mL, 8.0 mL and 5.0 mL 0.1 M NaOH respectively for 1
h, and then subjected to three times of extraction and centrifugation
(10,000 ×g for 5 min). The resulting supernatants were combined to fix
the volume (25 mL) for the determination of glutelin content.
The precipitate after the extraction of glutelin was repeatedly
extracted with 10 mL, 8.0 mL and 5.0 mL 70% ethanol respectively for 1
h. The mixture was extracted and centrifuged (10,000 ×g for 5 min) for
three times. After the combination and fixing the volume (25 mL) of the
supernatants, the prolamin content in the supernatants was determined.
0.1 mL of the extraction solution of albumin, globulin, prolamin or
glutelin was added with 5.0 mL Coomassie Blue G250 reagent. Then, the
absorbance was determined at 595 nm.
2.5. Statistical analysis
The data of functional groups that based on FTIR spectra were log10-
transformed for statistical analysis to improve their normality. Func­
tional groups in the figures were combined to be displayed, and the
detailed information of the functional groups is shown in Supplementary
material. OH bond means free OH, OH bond in alcohols, carboxylic acids
(chain and cyclic hydrocarbon and aromatic hydrocarbons) and phe­
nols; intramolecular or intermolecular OH respectively indicated intra­
molecular or intermolecular OH (single and polyassociation); C–O
bond included C–O bond in alcohols, carboxylic acids (chain and cyclic
hydrocarbon and aromatic hydrocarbons), ethers (chain and cyclic hy­
drocarbon and aromatic hydrocarbons), acid anhydride and esters; C–
–O
included carboxylic acids (chain and cyclic hydrocarbon and aromatic
hydrocarbons), ketones (chain and cyclic hydrocarbon and aromatic
hydrocarbons), aldehydes (chain and cyclic hydrocarbon and aromatic
hydrocarbons), acid anhydride and esters; Ar–O indicated the Ar–O in
phenols; NH or C–N bonds respectively means NH or in C–N (chain and
cyclic hydrocarbon and aromatic hydrocarbons) in amines. ANOVA was
performed by using SPSS Statistics 19.0 (SPSS Inc., Chicago, IL, USA)
and differences among treatments were defined at P < 0.01 and P <
0.05. Association analysis was performed with the Omicshare Analysis
System (https://www.omicshare.com). The Sigma Plot software version
10.0 (Systat Software Inc., San Jose, CA, USA) was used to plot the
figures.
3. Results
3.1. Grain quality traits
High processing quality means higher whole brown and head rice
rate; high appearance quality indicates lower chalkiness and chalky
grain rate; a higher breakdown value, lower setback and retrogradation
value after cooking possibly contribute to good taste; higher nutritional
quality refers to the 14–24% of amylose, high total flavonoids and less
than 7% protein. F/DHH-U had higher (P < 0.05) processing quality, as
shown by the higher whole brown and head rice rate than F/DIR-U/L
(Table 1; Fig. 1). The appearance quality of F/DHH-U was higher (P
< 0.05), as indicated by the lower chalkiness and chalky grain rate
compared with other treatments. F/DHH-U also had higher (P < 0.05)
nutritional quality, as suggested by the higher total flavonoids and
suitable amylose (18.5–19.9%) and protein (4.08–4.22%) than those of
F/DIR-U/L and F/DZS-U/L. Besides, the cooking quality of F/DHH-U
was higher, as indicated by the higher breakdown value and lower
GT, setback and retrogradation value (except for DZS) than those of F/
DIR-U/L and F/DZS-U/L. DHH-U had lower (P < 0.05) chalkiness,
chalky grain rate, retrogradation (except for DZS), GT and setback
values, but higher (P < 0.05) values of other parameters relative to DIR-
U/L and DZS-U/L.
3.2. Accumulation of assimilates and their relationship with grain quality
Compared with other treatments (Fig. 2), FHH had lower (P < 0.05)
soluble sugars during 2–27 DAA but the higher (P < 0.05) starch content
after 12 DAA, especially in the upper panicle. DHH had a higher (P <
0.05) soluble sugar content before 12 DAA than F/DIR and F/DZS, while
a lower (P < 0.05) level of soluble sugar and a higher (P < 0.05) level of
starch after 12 DAA, especially in the upper panicle.
The relationships between rice quality traits and the accumulation of
assimilates are presented in Fig. 3. With respect to nutritional quality,
glutelin had a negative (P < 0.05) relation with starch in the lower (after
12 DAA) or upper (after 17 DAA) panicle, and prolamine was positively
(P < 0.05) correlated with soluble sugar after 17 DAA in the upper
panicle. As for the appearance quality, chalkiness and chalky grain rate
exhibited positive (P < 0.05) correlation with soluble sugar and negative
(P < 0.05) correlation with starch in the upper (after 17 DAA) and lower
(after 12 DAA) panicle. In addition, chalkiness and chalky grain rate
were also positively (P < 0.01) related to glutelin and prolamine. With
respect to processing quality, whole brown and head rice rate were
positively (P < 0.05) associated with starch after 12 DAA in both the
upper and lower panicles. In addition, they were negatively correlated
(P < 0.05) with protein contents (glutelin and prolamine). As for the
cooking quality, the breakdown value positively correlated (P < 0.01)
with prolamine in the upper panicle, and with glutelin in the lower
panicle. GT showed negative (P < 0.01) correlations with glutelin,
prolamine and total flavonoid content in the upper panicle. These results
indicated that the accumulation of assimilates and proteins in the grains
have obvious impacts on rice quality traits and the relationship among
rice quality traits.
3.3. Activities of some key enzymes and their effects on grain quality
The cooperation among starch synthesis enzymes had different in­
fluence on amylose and amylopectin synthesis and rice quality traits
(Figs. 4 and 5). Compared with other treatments, FHH-U tended to
synthesize more short-branched chain amylopectin (SSSase, ADPGase
and SuSase) before 12 DAA and the branching (SBE) of amylose during
2–27 DAA, which led to a lower chalky grain rate and chalkiness. FHH-U
had the synthesis of more amylose (GBSSase, UDPGase and SuSase) and
long-branched chain amylopectin (SuSase, ADPGase, GBSSase and SBE)
during 2–27 DAA, resulting in higher breakdown value, whole brown
and head rice rate (except for DZS) and lower setback and
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Table 1
Whole brown and head rice rate, chalky grain rate, chalkiness, albumin, globulin, glutelin, prolamine, amylose and total flavonoid content in the upper or lower
panicle of Huanghuazhan (HH), IRAT109 (IR) and Zhenshan97 (ZS) under flooding irrigation (F) and dry cultivation (D).
I V P Whole
brown rice
rate (%)
Whole head
rice rate
(%)
Chalky
grain rate
(%)
Chalkiness
(%)
Albumin
content (%)
Globulin
content (%)
Glutelin
content (%)
Prolamine
content (%)
Amylose
content (%)
Total
flavonoid
content (%)
F HH U 83.0 ± 0.68
b
62.9 ± 0.51
c
10.5 ±
1.35 h
3.38 ± 0.16
g
0.021 ±
0.007 e
0.004 ±
0.001 h
2.88 ±
0.069 e
1.17 ± 0.002
c
19.9 ± 1.52
c
0.065 ± 0.007
b
L 81.5 ± 0.34
d
62.2 ± 0.29
c
13.0 ±
0.82 i
4.93 ± 0.15
g
0.034 ±
0.004 c
0.002 ±
0.000 i
3.24 ±
0.200 c
1.22 ± 0.012
b
16.8 ± 1.89
d
0.052 ± 0.005
d
IR U 82.4 ± 0.07
c
56.3 ± 1.64
f
77.0 ±
0.73 e
34.9 ± 0.05
d
0.033 ±
0.000 c
0.029 ±
0.007 f
3.00 ±
0.280 d
0.98 ± 0.016
e
11.4 ± 1.53
g
0.053 ± 0.001
d
L 81.8 ± 0.63
d
45.5 ±
1.03 g
81.0 ±
1.67d
34.7 ± 0.94
d
0.049 ±
0.006 b
0.048 ±
0.014 d
3.04 ±
0.069 d
1.04 ± 0.027
d
9.24 ± 0.97
h
0.056 ± 0.002
c
ZS U 81.4 ± 2.43
d
57.5 ± 4.14
e
87.5 ±
0.21 c
45.0 ± 0.26
c
0.035 ±
0.008 c
0.035 ±
0.013 e
5.63 ±
0.042 a
1.35 ± 0.043
a
24.5 ± 1.39
b
0.060 ± 0.001
b
L 78.5 ± 4.16
f
57.8 ± 3.59
e
88.5 ±
0.45 c
45.3 ± 0.45
c
0.058 ±
0.013 a
0.031 ±
0.004 f
5.82 ±
0.125 a
1.25 ± 0.038
b
24.5 ± 4.69
b
0.041 ± 0.004
e
D HH U 81.3 ± 0.40
d
62.8 ± 0.24
c
35.4 ±
2.09 g
14.5 ± 0.55
f
0.029 ±
0.001 d
0.004 ±
0.000 h
3.21 ±
0.220 c
0.98 ± 0.010
e
18.5 ± 0.16
c
0.074 ± 0.005
a
L 80.5 ± 0.37
e
59.4 ± 1.51
d
43.4 ±
2.57 f
20.8 ± 1.17
e
0.019 ±
0.001 e
0.011 ±
0.016 g
3.43 ±
0.092 c
0.95 ± 0.026
e
12.9 ± 2.50
f
0.057 ± 0.003
c
IR U 82.7 ± 0.19
c
59.8 ± 0.41
d
88.1 ±
1.04 c
49.7 ± 1.80
b
0.057 ±
0.005 a
0.076 ±
0.004 b
3.24 ±
0.040 c
0.81 ± 0.014
f
11.2 ± 1.90
g
0.056 ± 0.003
c
L 82.8 ± 0.49
c
60.4 ± 0.68
d
91.6 ±
1.21 b
52.0 ± 1.27
a
0.063 ±
0.021 a
0.100 ±
0.002 a
3.10 ±
0.021 d
0.81 ± 0.024
f
13.7 ± 0.90
e
0.053 ± 0.002
d
ZS U 84.1 ± 0.84
a
67.7 ± 1.97
a
94.2 ±
0.05 a
49.8 ± 2.50
b
0.005 ±
0.000 g
0.059 ±
0.008 c
5.35 ±
0.162 b
1.05 ± 0.056
d
29.9 ± 1.75
a
0.035 ± 0.004
e
L 83.4 ± 0.62
b
65.3 ± 0.06
b
95.7 ±
0.79 a
51.6 ± 1.51
a
0.015 ±
0.004 f
0.003 ±
0.001 i
5.32 ±
0.040 b
1.34 ± 0.028
a
29.4 ± 2.85
a
0.041 ± 0.002
e
I * ** ** ** * ** ns ** * ns
V ns ** ** ** ** ** ** ** ** **
P * ** ** ** ** ns * ns * **
I × V ** ** ** ** ** ** ** ns ** **
I × P ns ns * ** * ns * ns ns ns
V × P ns ns ** ** ns ** * ns * *
Values are mean ± SD (n = 3). “I” means the irrigation way (F and D); “V” stands for the cultivar (HH, IR and ZS); P means the position of panicle; U and L respectively
represent the upper and lower panicle. I × V, I × P and V × P represent the interaction between irrigation and cultivar, irrigation and position, and cultivar and
position, respectively. Values within columns followed by different letters indicate statistical differences at the 0.05 level. * and ** indicate significant differences at the
0.05 and 0.01 level, respectively.
Fig. 1. Gelatinization temperature (GT), breakdown, setback and retrogradation values in the upper or lower panicle of Huanghuazhan (HH), IRAT109 (IR) and
Zhenshan97 (ZS) under flooding irrigation (F) and dry cultivation (D). Different lowercase letters denote statistical differences between treatments at the 0.05 level
according to the LSD test.
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6. Carbohydrate Polymers 269 (2021) 118336
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retrogradation (except for DZS) values. Compared with other treat­
ments, DHH-U maintained higher synthesis of amylose (GBSSase,
ADPGase and UDPGase) before 12 DAA and removed the improper
branch (DBE) of amylopectin to accumulate amylopectin after 12 DAA,
leading to lower amylose and GT and higher whole brown rice rate.
Besides, DHH-U exhibited higher synthesis of short-branched chain
amylopectin (SSSase, ADPGase and SuSase) during 2–27 DAA, leading
to higher whole head rice rate and breakdown value while lower
chalkiness, chalky grain rate, setback and retrogradation values
compared with other cultivars under D treatment.
3.4. Traits of functional groups before and after pasting
The traits of the starch granules and the functional groups in starch
were evaluated based on FTIR spectra (Figs. 6 and 7), and the results are
shown as follows. The relative contents of all functional groups before
pasting were significantly higher than those after pasting. Before
pasting, FHH-U had lower amorphous regions (a ratio of 1022/995) than
other cultivars in F, and DHH-U also had lower amorphous regions than
IR under D treatment. F/DHH-U resulted in higher crystalline regions (a
ratio of 1045/995) and order degree of carbohydrate structure (a ratio of
1045/1022) (except for DZS) compared with other treatments. Intra­
molecular and intermolecular OH, OH bond, C–O bond, C–N bond, NH
bond, C–
–O bond, Ar–O and hydrocarbons (carbon skeleton) in F/DHH-
U had higher values compared with those under other treatments,
particularly FHH-U.
After pasting, FHH-U had lower order degree of carbohydrate
structure and values of C–
–O bonds, C–N and NH bond in amines
compared with other treatments in the upper panicle. DHH-U had higher
values of intramolecular and intermolecular OH bond, OH bond, C–O
Fig. 2. Sucrose, soluble sugar and starch content in the upper (A, C and E) or lower (B, D and F) panicle of Huanghuazhan (HH), IRAT109 (IR) and Zhenshan (ZS)
under flood irrigation (F) and dry cultivation (D) at 2, 7, 12, 17 and 27 days after anthesis (DAA). Different lowercase letters denote statistical differences between
treatments at the 0.05 level according to LSD test in a column for (top to bottom) FHH, DHH, FIR, DIR, FZS and DZS.
Fig. 3. Analysis of the relationship of STA (starch), SUC (sucrose) and SOL (soluble sugar) with WBR (whole brown rice rate) and WHR (whole head rice rate), CGR
(chalky grain rate), CHA (chalkiness), ALC (albumin content), GLO (globulin content), GLU (glutelin content), PRO (prolamine content), AMY (amylose content), TFC
(total flavonoid content), GT (gelatinization temperature), BRK (breakdown value), SET (setback value) and REV (retrogradation value) at 2, 7, 12, 17 and 27 days
after anthesis (DAA). On the arrows, the stars indicate the association analysis, and the bars show the combination of the association analysis and correlation analysis.
* and ** indicate significant correlations at the 0.05 and 0.01 level, respectively.
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Fig. 4. SuSase (Sucrose synthase), UDPGase (UDP-glucose pyrophosphorylase), ADPGase (ADP-glucose pyrophosphorylase), GBSSase (granule-bound starch syn­
thase), SSSase (soluble starch synthase), SBE (starch branching enzyme) and DBE (starch debranching enzyme) in the lower (B, D, F, H, J, L and N) or upper (A, C, E,
G, I, K and M) panicle of Huanghuazhan (HH), IRAT109 (IR) and Zhenshan (ZS) under flood irrigation (F) and dry cultivation (D) at 2, 7, 12, 17 and 27 days after
anthesis. Different lowercase letters denote statistical differences between treatments at the 0.05 level according to LSD test in a column for (top to bottom) FHH, FIR,
FZS, DHH, DIR and DZS.
Fig. 5. Association analysis of SuSase (sucrose synthase), UDPGase (UDP-glucose pyrophosphorylase), ADPGase (ADP-glucose pyrophosphorylase), GBSSase
(granule-bound starch synthase), SSSase (soluble starch synthase), SBE (starch branching enzyme) and DBE (starch debranching enzyme) with WBR (whole brown
rice rate), WHR (whole head rice rate), CGR (chalky grain rate), CHA (chalkiness), AMY (amylose), GT (gelatinization temperature), BRK (breakdown value), SET
(setback value) and REV (retrogradation value) in the lower or upper panicle of Huanghuazhan (HH), IRAT109 (IR) and Zhenshan (ZS) under flood irrigation (F) and
dry cultivation (D) at 2, 7, 12, 17 and 27 days after anthesis.
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8. Carbohydrate Polymers 269 (2021) 118336
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bond, C–
–O bond as well as hydrocarbons (carbon skeleton) compared
with FHH-U, DIR-U and DZS-U, but lower amorphous and crystalline
regions and order degree of carbohydrate structure than other treat­
ments in upper panicle, except for FIR-U.
3.5. Relationship between functional groups and grain quality
The functional groups tended to affect the peak, hot and cold paste
viscosity during pasting (Fig. 8), which influenced the GT, breakdown,
setback and retrogradation values. The contributions of these functional
groups to the high rice quality under DHH, especially DHH-U, were
characterized by the following traits relative to other treatments. GT was
mainly affected by intermolecular OH, Ar–O bond, hydrocarbon,
amorphous and crystalline regions, intramolecular OH, OH bond, NH
bond, C–N bond, C–O bond and C–
–O bond before pasting. These
functional groups negatively (P < 0.05) influenced the GT.
Compared with that in other treatments, the breakdown value in
DHH-U was influenced by the intramolecular and intermolecular OH,
hydrocarbon, crystallinity, OH bond, NH bond, C–N bond, C–O bond,
C–
–O bond, Ar–O bond, amorphous and crystalline regions before
pasting. Among these functional groups, intermolecular OH, OH bond,
NH bond, C–N bond, C–O bond, C–
–O bond, hydrocarbon, crystalline
regions and crystallinity were positively (P < 0.05) related to the
breakdown value. Compared with that in other treatments, the break­
down value in DHH-U was also related to intramolecular OH, C–N
bond, C–O bond, hydrocarbon, intermolecular OH, OH bond, NH bond,
C–
–O bond, Ar–O bond, amorphous and crystalline regions after
pasting. Among them, intermolecular OH, C–N bond, C–O bond, C–
–O
bond, hydrocarbon and crystalline regions were negatively (P < 0.05)
related to the breakdown value, while amorphous regions had positive
(P < 0.05) relationships.
The amorphous and crystalline regions, intermolecular OH, the order
degree of carbohydrate structure, Ar–O bond, intramolecular OH, OH
bond, NH bond, C–N bond, C–O bond, C–
–O bond and hydrocarbon
before pasting had higher contributions to the setback value in DHH-U
compared with other treatments. Among these, C–
–O bond, hydrocar­
bon and amorphous regions were not related to setback, while others
had positive (P < 0.05) influence on the setback value before pasting.
Compared with that in other treatments, the setback value in DHH-U
was also related to amorphous and crystalline regions, hydrocarbon,
C–
–O bond, C–O bond, C–N bond, intramolecular OH, intermolecular
OH, OH bond, NH bond and Ar–O bond after pasting. Among these,
intramolecular OH, intermolecular OH, OH bond, and C–
–O bond were
positively (P < 0.05) related to the setback value, while crystalline re­
gions had a negative (P < 0.05) relationship with the setback value.
The retrogradation value in DHH-U was mainly influenced by Ar–O
bond, intermolecular and intramolecular OH, OH bond, NH bond, C–N
bond, C–O bond, C–
–O bond, hydrocarbon, amorphous and crystalline
regions and the order degree of carbohydrate structure before pasting
compared with that in other treatments. Among them, C–O bond and
hydrocarbon negatively (P < 0.05) influenced the retrogradation value,
while the order degree of carbohydrate structure had positive (P < 0.05)
contributions. Compared with that in other treatments, the retrograda­
tion value in DHH-U was mainly related to Ar–O bond, C–N bond,
intramolecular OH, C–O bond, hydrocarbon, intermolecular OH, OH
bond, NH bond C–
–O bond, amorphous and crystalline regions after
pasting. Among these functional groups, intermolecular OH, OH bond,
NH bond, C–O bond, hydrocarbon and crystalline regions were posi­
tively (P < 0.05) related to retrogradation value.
Fig. 6. Order degree of carbohydrate structure (1045/1022 cm− 1
ratio), amorphous regions (1022/995 cm− 1
ratio) and crystalline regions (1045/995 cm− 1
ratio)
obtained from FTIR spectra of rice starch before (A, B, C, D, E and F) and after (G, H, I, J, K and L) pasting in the upper (A, C, E, G, I and K) and lower (B, D, F, H, J and
L) panicle of Huanghuazhan (HH), IRAT109 (IR) and Zhenshan (ZS) under flood irrigation (F) and dry cultivation (D). Different lowercase letters denote statistical
differences between treatments at the 0.05 level according to the LSD test.
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9. Carbohydrate Polymers 269 (2021) 118336
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4. Discussion
4.1. Accumulation forms of assimilates affected the relationship among
rice quality traits (Fig. 9)
Starch, proteins and other forms of assimilate (such as soluble
sugars) as well as their relationship in the grain have great impact on
rice quality traits (Leethanapanich et al., 2016; Wada et al., 2019; Yu
et al., 2016). Under normal development of starch granules, storage
proteins can fill the space between starch granules, contributing to a
more compact arrangement of the granules and reducing the chalkiness
(Wada et al., 2019). However, when the development of starch granules
is abnormal, the accumulation of storage proteins in the grains will lead
to a loose arrangement of starch granules, resulting in significant
random reflection of light, which increases chalkiness (Leethanapanich
et al., 2016). The accumulation of soluble sugars in mature grains
possibly helps the formation of high polymers between protein, lipid and
starch. Thus, high polymers reduce the tightness of rice grains, resulting
in a decline in the processing and appearance quality (Wada et al., 2019;
Yu et al., 2016). A higher level of soluble sugars in the grain also in­
creases the tightness of protein subunits or protein bodies, which easily
supports the accumulation of storage proteins and then reduces the
tightness degree of rice grains (Wada et al., 2019; Yu et al., 2016).
In this study, IR-U/L and ZS-U/L under D treatment maintained a
higher soluble sugar level and a lower starch level after 12 DAA. On the
contrary, DHH-U had a higher ability of starch synthesis and promoted
the conversion of soluble sugars (including sucrose) to starch, leading to
a lower soluble sugar level and a higher starch level during 12–27 DAA.
This might limit the polymerization between starch, proteins and lipids,
improving the intensity and morphology of starch granules, which can
reduce the space among starch granules to decrease chalkiness. DHH-U
also had a lower protein content (especially the glutelin protein)
compared with FZS-U/L and DZS-U/L and a more normal development
of starch granules than FIR-U/L and DIR-U/L. These traits of DHH-U
could help glutelin and prolamine to fill the space among starch gran­
ules, so as to increase the tightness of grains and then contribute to
higher whole head rice rate and lower chalkiness. During pasting, the
tight structure of starch granules or grains in DHH-U could facilitate the
close adhesion among starch granules to form longer chain structures
when the granules absorb water and swell, which easily elevates the
peak paste viscosity. Therefore, DHH-U had lower chalkiness and chalky
grain rate and higher whole brown, head rice rate and breakdown value.
The water absorption and swelling of amylose in the amorphous
regions would lead to the swelling of starch granules, which is the start
of pasting process and defined as the GT (Li et al., 2020). GT is depen­
dent not only on the type and amount of starch granules, but also on the
Fig. 7. Functional groups of rice starch before and after pasting in the lower (L) or upper (U) panicle of Huanghuazhan (HH), IRAT109 (IR) and Zhenshan (ZS) under
flood irrigation (F) and dry cultivation (D).
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10. Carbohydrate Polymers 269 (2021) 118336
10
composition of storage proteins, because the hydrophilic group of stor­
age proteins is outside the molecule. The hydrophilic group could
immobilize water to limit the water absorption and swelling of starch
granules (Copeland et al., 2009). DHH-U reduced the accumulation of
amylose in the amorphous regions and the content of glutelin, which
could increase the water absorption rate of starch granules, resulting in
lower GT.
Compared with FHH-U/L, DHH-U still maintained a lower starch
content during 12–27 DAA and a higher soluble sugar content during
12–17 DAA. Rice dry cultivation creates an environment of long-term
moderate drought stress. Hence, soluble sugars accumulate in the
grains to participate in osmotic protection for resistance against drought
stress and removal of reactive oxygen (Liu et al., 2017), which supports
the development of starch granules and the accumulation of starch.
Drought stress could also increase the content of lysine and proline for
resistance to drought stress (Obata & Fernie, 2012). The accumulation of
lysine restrains the degradation of aspartic acid by a feedback inhibitory
effect (Galili et al., 2016) to support the synthesis of glutelin (Amagliani
et al., 2017). Drought stress induces protein tyrosine phosphatase to
reduce the tryptophane content (Liu et al., 2012), which is not condu­
cive to the synthesis of prolamine that includes a large amount of
glutamate and tryptophane (Amagliani et al., 2017). Hence, DHH-U led
to lower soluble sugars and higher starch and glutelin to maintain better
rice quality traits.
4.2. Enzyme activities of starch synthesis alter the relationship among rice
quality traits (Fig. 9)
Amylopectin occupies a larger proportion in the grain than amylose.
The amylose and amylopectin with different branches fill different re­
gions of starch granules to affect the quality traits. The concentric
growth rings in starch granules contain higher density of crystalline
regions and lower density of amorphous regions. The crystalline regions
contain crystalline lamella (mainly short-branched amylopectin) and
amorphous lamella (mainly long-branched of amylopectin) in an or­
dered conformation (Copeland et al., 2009). Compared with other
treatments, F/DHH-U maintained better rice quality traits, especially
FHH-U, possibly because FHH-U tended to enhance the synthesis of long
Fig. 8. Association analysis of the functional groups of rice starch before (A, B, C, D, E, F, G and H) and after (a, b, c, d, e, f, g and h) pasting with GT (gelatinization
temperature), breakdown value, setback value and retrogradation value in the upper (A, C, E, G, a, c, e and G) or lower (B, D, F, H, b, d, f and h) panicle of
Huanghuazhan (HH), IRAT109 (IR) and Zhenshan (ZS) under flood irrigation (F) and dry cultivation (D). The correlation (* or –) shown in the figure is at the
0.05 level.
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11. Carbohydrate Polymers 269 (2021) 118336
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branch-chain amylopectin, and also maintain the formation of amylose
after 12 DAA. A higher level of long branch-chain amylopectin results in
the formation of denser crystalline regions or pack of amylopectin into
an amorphous lamella of crystalline regions in starch granules. The
accumulated amylose fills the amorphous regions. These factors
together improve the tightness of starch granules and the grains, and as a
result enhance the whole brown and head rice rate and breakdown
value, while reduce the chalkiness, chalky grain rate, setback value and
GT.
DHH-U also maintained better rice quality traits than other cultivars
in D treatment, possibly through different physiological pathways. DHH-
U mainly increased the synthesis of short-branched chain amylopectin
before 12 DAA and the branching of amylose during 2–27 DAA to form
amylopectin with short-branched chains. The higher accumulation of
short-branched chain amylopectin in DHH-U would support the for­
mation of the crystalline lamella in the crystalline regions. It could
improve the shape and support the normal development of starch
granules to enhance the plumpness of starch granules and grains, which
can improve the processing quality, appearance quality and the rela­
tionship among rice quality traits. Besides, new branched chains would
be introduced into the amylose after 12 DAA. This would enhance the
competitiveness of amylopectin synthesis over amylose synthesis and
further reduce the amylose content in DHH-U. The decrease in amylose
would reduce the water absorption of starch granules to decrease GT.
Thus, it was suggested that the rice quality traits of DHH-U were better
than those of other cultivars under dry cultivation because of the higher
synthesis of short-branched chain amylopectin.
4.3. Rice cooking quality is affected by some functional groups and starch
granule crystallinity (Fig. 9)
The physicochemical characteristics of starch granules tend to in­
fluence the peak and hot paste viscosity as well as the hot and cold paste
viscosity during pasting (Chen et al., 2019). F/DHH-U, especially FHH-
U, had higher crystalline regions and order degree of carbohydrate
structure of starch granules, intermolecular (intramolecular OH) and
intramolecular (intermolecular OH) forces, as well as more hydrophobic
(hydrocarbons (carbon skeleton)) and hydrophilic (OH bond, C–O
bond, C–N bond, NH bond, C–
–O bond, Ar–O) functional groups before
pasting compared with other treatments. After pasting, F/DHH-U had
more hydrophobic functional groups, and FHH-U had fewer while DHH-
U had more hydrophilic functional groups than other treatments.
Before pasting, F/DHH-U maintained the ordered carbohydrate
structure and higher crystalline regions in starch granules, which might
limit water absorption and swelling of starch granules and accelerate the
initiation of gelatinization to decrease the GT (Copeland et al., 2009). In
addition, a higher crystallinity would promote the adhesion among
starch granules upon starch granule swelling with water during pasting,
which elevates the peak paste viscosity. In addition, many hydrophilic
functional groups were maintained in F/DHH-U, which tend to form
intramolecular and intermolecular hydrogen bonds with water mole­
cules (Fumoto et al., 2020; Wang et al., 2018). This could also strengthen
the inter- and intra-molecular forces to delay the breaking of chemical
bonds with rising temperature during pasting, resulting in higher peak
paste viscosity.
Hydrophobic functional groups in DHH-U had higher contributions
to cooking quality traits, and DHH-U also increased these hydrophobic
functional groups before pasting. Hydrophobic functional groups could
provide hydrophobic forces to protect the molecular structure of pro­
teins or starch chains (Fumoto et al., 2020; Wang et al., 2018). Upon the
initiation of starch granule pasting, the hydrophobic functional groups
tend to limit the water absorbing capacity of starch granules to decrease
the GT. The hydrophobic force is weakened with rising temperature
during pasting, and the molecular structure of proteins or starch is
changed into a disordered state (Wang et al., 2018; Xu et al., 2015),
which could lead to the higher peak paste viscosity in DHH-U. Under
continuous high temperature, the intramolecular and intermolecular
hydrogen bonds and the hydrophobic force could be disrupted, but co­
valent bonds are destroyed at a slower rate at high temperature (Saleh &
Meullenet, 2015; Wang et al., 2018). DHH-U had stronger covalent
bonds to help the maintenance of starch granule and starch chain
structures during pasting to result in higher peak viscosity. Hence, DHH-
U could maintain high levels of carbohydrate chain structures, covalent
bonds, hydrophobic forces, inter- and intra-molecular forces, resulting
in a higher breakdown value and lower GT and setback values relative to
other cultivars under dry cultivation.
The changes in functional groups after pasting are closely related to
hot and cold paste viscosity (Chen et al., 2019). There were fewer
functional groups after pasting than before pasting, indicating that
pasting seriously damages the starch granule structure. Many covalent
bonds were also severely destroyed by the high temperature, and the
relative content of macromolecular substances was significantly
reduced. DHH-U had fewer covalent bonds than FHH-U before pasting,
which could reduce the intramolecular force to maintain the structure of
Fig. 9. Mechanisms by which assimilate accumulation forms, starch synthesis enzymes and starch granule physicochemical properties influence the processing,
appearance, nutritional and cooking quality. The circles represent enzymes; light red represents the upper panicle and light blue represents the lower panicle.
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12. Carbohydrate Polymers 269 (2021) 118336
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macromolecular substances. The smaller number of covalent bonds
might easily lead to the production of many small molecule substances
during pasting, which tends to decrease the viscosity of starch colloids to
result in lower hot paste viscosity. DHH also had lower intermolecular
forces after pasting in starch colloids, indicating the transformation of
macromolecular substances into many small molecules, and corre­
spondingly a lower hot paste viscosity during pasting compared with
FHH. During the process of retrogradation, the intermolecular force also
plays a critical role in the viscosity of starch colloids. DHH-U maintained
a higher ratio of hydrophilic functional groups and relatively stronger
hydrogen bonds in starch colloids compared with other treatment. The
formation of macromolecules is still limited. As a consequence, the paste
viscosity of starch colloids during retrogradation was lower, due to the
presence of too many small molecules, high hydrophobic force and
inadequate energy supply in the colloid. Thus, the relatively higher peak
viscosity and lower hot and cold paste viscosity during pasting led to
higher breakdown values and lower setback and retrogradation values
in DHH-U.
5. Conclusion
In general, drought-resistant (IR) and drought-susceptible cultivar
(ZS) under rice dry cultivation (D) had lower rice grain quality; while
the high-quality (HH) cultivar under dry cultivation, especially in the
upper panicle (U), maintained higher processing, appearance, nutri­
tional and cooking quality. DHH-U synthesized more short-branched
chain amylopectin to fill the crystalline lamella of crystalline regions,
which could contribute to higher processing, appearance, nutritional
and cooking quality. Besides, DHH-U could maintain ordered carbohy­
drate structure and higher crystalline regions in starch granules, as well
as strengthen the intermolecular and intramolecular forces of starch
colloids before or after pasting. These factors together could enhance the
peak paste viscosity and reduce the hot and cold paste viscosity to
contribute to greater rice cooking quality.
CRediT authorship contribution statement
All the authors have approved the manuscript and agree with sub­
mission to the journal. There are no conflicts of interest to declare.
All the authors ensure the accuracy or integrity of all aspects of the
manuscript.
Acknowledgements
This study was funded by the National Natural Science Foundation of
China (31801291), Special Funds for Fundamental Scientific Research
Operation Fees of Central Universities (2662020ZKPY014) and State
Key Special Program (2017YFD0301400). Cougui Cao, Ping Li, Yang
Jiang and Mingli Cai initiated and designed the experiment. Zongkui
Chen, and YunFeng Du performed the experiments and collected the
data. Zongkui Chen analyzed the data and wrote the manuscript. Ping Li
and Zongkui Chen revised the manuscript. All the authors have no
conflicts of interest to declare.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.carbpol.2021.118336.
References
Agboola, S., Ng, D., & Mills, D. (2005). Characterisation and functional properties of
Australian rice protein isolates. Journal of Cereal Science, 41, 283–290. https://doi.
org/10.1016/J.JCS.2004.10.007.
Amagliani, L., O’Regan, J., Kelly, A. L., & O’Mahony, J. A. (2017). The composition,
extraction, functionality and applications of rice proteins: A review. Trends in Food
Science and Technology, 64, 1–12. https://doi.org/10.1016/J.TIFS.2017.01.008.
Ball, S. G., & Morell, M. K. (2003). From bacterial glycogen to starch: Understanding the
biogenesis of the plant starch granule. Annual Review of Plant Biology, 54, 207–233.
https://doi.org/10.1146/annurev.arplant.54.031902.134927.
Bradford, M. (1976). A rapid and sensitive method for the quantitation of microgram
quantities of protein utilizing the principles of protein-dye binding. Analytical
Biochemistry, 71, 248–254. https://doi.org/10.1016/0003-2697(76)90527-3.
Chen, C., Huang, J., Zhu, L., Shah, F., Nie, L., Cui, K., & Peng, S. (2013). Varietal
difference in the response of rice chalkiness to temperature during ripening phase
across different sowing dates. Field Crops Research, 151, 85–91. https://doi.
org/10.1016/j.fcr.2013.07.016.
Chen, X., Chen, M., Lin, G., Yang, Y., Yu, X., Wu, Y., & Xiong, F. (2019). Structural
development and physicochemical properties of starch in caryopsis of super rice with
different types of panicle. BMC Plant Biology, 19, 1–15. https://doi.org/10.118
6/s12870-019-2101-7.
Chen, Z., Chen, H., Jiang, Y., Wang, J., Khan, A., Li, P., & Cao, C. (2020). Metabolomic
analysis reveals metabolites and pathways involved in grain quality traits of high-
quality rice cultivars under a dry cultivation system. Food Chemistry, 326, 126845.
https://doi.org/10.1016/J.FOODCHEM.2020.126845.
Chen, Z., Li, P., Jiang, S., Chen, H., Wang, J., & Cao, C. (2021). Evaluation of resource
and energy utilization, environmental and economic benefits of rice water-saving
irrigation technologies in a rice-wheat rotation system. Science of the Total
Environment, 757, Article 143748. https://doi.org/10.1016/j.scitotenv.2020
.143748.
Chen, Z., Yang, X., & Song, W. (2020). Water-saving cultivation plus super rice hybrid
genotype improves water productivity and yield. Agronomy Journal, 112,
1764–1777. https://doi.org/10.1002/agj2.20121.
China Rice Data Center. (2014). China Rice Data Center. Retrieved from http://www.rice
data.cn/variety/varis/612155.htm. (Accessed 22 July 2019).
Chlopicka, J., Pasko, P., Gorinstein, S., Jedryas, A., & Zagrodzki, P. (2012). Total
phenolic and total flavonoid content, antioxidant activity and sensory evaluation of
pseudocereal breads. LWT - Food Science and Technology, 46, 548–555. https://doi.
org/10.1016/j.lwt.2011.11.009.
Copeland, L., Blazek, J., Salman, H., & Tang, M. C. (2009). Form and functionality of
starch. Food Hydrocolloids, 23, 1527–1534. https://doi.org/10.1016/j.foodhyd.200
8.09.016.
Dong, M., Gu, J., & Zhang, L. (2014). Comparative proteomics analysis of superior and
inferior spikelets in hybrid rice during grain filling and response of inferior spikelets
to drought stress using isobaric tags for relative and absolute quantification. Journal
of Proteomics, 1, 51–55. https://doi.org/10.1016/j.dib.2014.08.001.
Duan, H., Tong, H., & Zhu, A. (2020). Effects of heat, drought and their combined effects
on morphological structure and physicochemical properties of rice (Oryza sativa L.)
starch. Journal of Cereal Science, 95, Article 103059. https://doi.org/10.1016/j.jcs.
2020.103059.
Falade, K. O., & Christopher, A. S. (2015). Physical, functional, pasting and thermal
properties of flours and starches of six Nigerian rice cultivars. Food Hydrocolloids, 44,
478–490. https://doi.org/10.1016/j.foodhyd.2014.10.005.
FAOSTAT. (2018). FAO statistical databases. Retrieved from http://www.fao.org.
(Accessed 6 October 2020).
Fumoto, E., Sato, S., & Takanohashi, T. (2020). Determination of carbonyl functional
groups in heavy oil using infrared spectroscopy. Energy & Fuels, 34, 5231–5235.
https://doi.org/10.1021/acs.energyfuels.9b02703.
Galili, G., Amir, R., & Fernie, A. R. (2016). The regulation of essential amino acid
synthesis and accumulation in plants. Annual Review of Plant Biology, 67, 153–178.
https://doi.org/10.1146/annurev-arplant-043015-112213.
Gao, J. F. (2006). Experimental guide of plant physiology. In Determination of sugar,
starch and cellulose content in plant tissue (1st ed., pp. 144–148) (Chapter 6).
Goldstein, A. G., Annor, V., Vamadevan, I., Tetlow, J. J. K., & Kirkensgaard, K. M. (2017).
Influence of diurnal photosynthetic activity on the morphology, structure, and
thermal properties of normal and waxy barley starch. International Journal of
Biological Macromolecules, 98, 188–200. https://doi.org/10.1016/j.ijbiomac.2017.01
.118.
Gong, J., Miao, J., Zhao, Y., Zhao, Q., Feng, Q., Zhan, Q., & Yang, S. (2017). Dissecting
the genetic basis of grain shape and chalkiness traits in hybrid rice using multiple
collaborative populations. Molecular Plant, 10, 1353–1356. https://doi.org/10.1016
/j.molp.2017.07.014.
Han, Y., Xu, M., Liu, X., Yan, C., Korban, S. S., Chen, X., & Gu, M. (2004). Genes coding
for starch branching enzymes are major contributors to starch viscosity
characteristics in waxy rice (Oryza sativa L.). Plant Science, 166, 357–364. https://
doi.org/10.1016/j.plantsci.2003.09.023.
Kong, X., Zhu, P., Sui, Z., & Bao, J. (2015). Physicochemical properties of starches from
diverse rice cultivars varying in apparent amylose content and gelatinisation
temperature combinations. Food Chemistry, 172, 433–440. https://doi.org/10.1016/
j.foodchem.2014.09.085.
Leethanapanich, K., Mauromoustakos, A., & Wang, Y. J. (2016). Impact of soaking and
drying conditions on rice chalkiness as revealed by scanning electron microscopy.
Cereal Chemistry, 93, 478–481. https://doi.org/10.1094/CCHEM-12-15-0248-N.
Li, C., Dhital, S., Gilbert, R. G., & Gidley, M. J. (2020). High-amylose wheat starch:
Structural basis for water absorption and pasting properties. Carbohydrate Polymers,
245, Article 116557. https://doi.org/10.1016/j.carbpol.2020.116557.
Liu, B., Fan, J., Zhang, Y., Mu, P., Wang, P., & Su, J. (2012). OsPFA-DSP1, a rice protein
tyrosine phosphatase, negatively regulates drought stress responses in transgenic
tobacco and rice plants. Plant Cell Reports, 31, 1021–1032. https://doi.org/10.100
7/s00299-011-1220-x.
Liu, S., Waqas, M. A., Wang, S., Xiong, X., & Wan, Y. (2017). Effects of increased levels of
atmospheric CO2 and high temperatures on rice growth and quality. PLoS ONE, 12,
Article e0187724. https://doi.org/10.1371/journal.pone.0187724.
Z. Chen et al.

13. Carbohydrate Polymers 269 (2021) 118336
13
Luo, L. J. (2010). Breeding for water-saving and drought-resistance rice (WDR) in China.
Journal of Experimental Botany, 61, 3509–3517. https://doi.org/10.1093/j
xb/erq185.
Nakamura, Y., Yuki, K., Park, S. Y., & Ohya, T. (1989). Carbohydrate metabolism in the
developing endosperm of rice grains. Plant and Cell Physiology, 30, 833–839. https://
doi.org/10.1094/Phyto-79-999.
National Bureau of Statistics of China. (2018). National Statistical databases. Retrieved
from http://www.stats.gov.cn/tjsj/. (Accessed 6 October 2020).
Obata, T., & Fernie, A. R. (2012). The use of metabolomics to dissect plant responses to
abiotic stresses. Cellular and Molecular Life Sciences, 69, 3225–3243. https://doi.
org/10.1007/s00018-012-1091-5.
Rana, N., Rahim, M. S., Kaur, G., Bansal, R., Kumawat, S., Roy, J., & Sharma, T. R.
(2020). Applications and challenges for efficient exploration of omics interventions
for the enhancement of nutritional quality in rice (Oryza sativa L.). Critical Reviews in
Food Science and Nutrition, 60, 3304–3320. https://doi.org/10.1080/10408398.201
9.1685454.
Rose, T. J., Welling, M. T., Julia, C. C., Jeong, K., Tong, C., Waters, D. L. E., & Liu, L.
(2020). Accumulation of phytate and starch lysophospholipids in rice grains and
responses to alterations in P supply or source-sink relations. Journal of Cereal Science,
91, Article 102896. https://doi.org/10.1016/j.jcs.2019.102896.
Saleh, M., & Meullenet, J. F. (2015). Cooked rice texture and rice flour pasting
properties; impacted by rice temperature during milling. Journal of Food Science and
Technology-Mysore, 52, 1602–1609. https://doi.org/10.1007/s13197-013-1180-y.
Schaffer, A. A., & Petreikov, M. (1997). Sucrose-to-starch metabolism in tomato fruit
undergoing transient starch accumulation. Plant Physiology, 113, 739–746. https://
doi.org/10.1104/pp.113.3.739.
Sevenou, O., Hill, S. E., & Farhat, I. A. (2002). Organization of the external region of the
starch granule as determined by infrared spectroscopy. International Journal of
Biological Macromolecules, 31, 79–85. https://doi.org/10.1016/S0141-8130(02)
00067-3.
Sundukova, Y. V., Lee, M. J., & Park, H. (2000). Sucrose synthase, UDP-glucose
pyrophosphorylase and ADP-glucose pyrophosphorylase in Korea ginseng roots.
Journal of Ginseng Research, 24, 83–88.
Syahariza, Z. A., Sar, S., Hasjim, J., Tizzotti, M. J., & Gilbert, R. G. (2013). The
importance of amylose and amylopectin fine structures for starch digestibility in
cooked rice grains. Food Chemistry, 136, 742–749. https://doi.org/10.1016/j.foodch
em.2012.08.053.
Tian, Z., Qian, Q., Liu, Q., Yan, M., Liu, X., Yan, C., & Zeng, D. (2009). Allelic diversities
in rice starch biosynthesis lead to a diverse array of rice eating and cooking qualities.
Proceedings of the National Academy of Sciences of the United States of America, 106,
21760–21765. https://doi.org/10.1073/pnas.0912396106.
Vamadevan, V., & Bertoft, E. (2020). Observations on the impact of amylopectin and
amylose structure on the swelling of starch granules. Food Hydrocolloids, 103, Article
105663. https://doi.org/10.1016/j.foodhyd.2020.105663.
Varavinit, S., Shobsngob, S., Varanyanond, W., Chinachoti, P., & Naivikul, O. (2003).
Effect of amylose content on gelatinization, retrogradation and pasting properties of
flours from different cultivars of Thai rice. Starch-Starke, 55, 410–415. https://doi.
org/10.1002/STAR.200300185.
Wada, H., Hatakeyama, Y., Onda, Y., Nonami, H., Nakashima, T., Erra-Balsells, R., &
Nakano, H. (2019). Multiple strategies for heat adaptation to prevent chalkiness in
the rice endosperm. Journal of Experimental Botany, 70, 1299–1311. https://doi.org
/10.1093/jxb/ery427.
Wang, R., Xu, P., Chen, Z., Zhou, X., & Wang, T. (2018). Complexation of rice proteins
and whey protein isolates by structural interactions to prepare soluble protein
composites. LWT - Food Science and Technology, 101, 207–213. https://doi.org/
10.1016/j.lwt.2018.11.006
Widjanarko, S. B., Nugroho, A., & Estiasih, T. (2011). Functional interaction components
of protein isolates and glucomannan in food bars by FTIR and SEM studies. African
Journal of Food Science, 5, 12–21 (https://doi.org/D7EB1E62520).
Xu, X., Liu, W., Zhong, J., Luo, L., Liu, C., Luo, S., & Chen, L. (2015). Binding interaction
between rice glutelin and amylose: Hydrophobic interaction and conformational
changes. International Journal of Biological Macromolecules, 81, 942–950 (https://doi.
org/10.1016/J.IJBIOMAC.2015.09.041).
Ye, Y., Liang, X., Chen, Y., Liu, J., Gu, J., Guo, R., & Li, L. (2013). Alternate wetting and
drying irrigation and controlled-release nitrogen fertilizer in late-season rice. Effects
on dry matter accumulation, yield, water and nitrogen use. Field Crops Research, 144,
212–224. https://doi.org/10.1016/j.fcr.2012.12.003.
Yu, X., Yuan, F., Fu, X., & Zhu, D. (2016). Profiling and relationship of water-soluble
sugar and protein compositions in soybean seeds. Food Chemistry, 196, 776–782.
https://doi.org/10.1016/j.foodchem.2015.09.092.
Zhai, L., Wang, F., Yan, A., Liang, C., Wang, S., Wang, Y., & Xu, J. (2020). Pleiotropic
effect of GNP1 underlying grain number per panicle on sink, source and flow in rice.
Frontiers in Plant Science, 11, 933. https://doi.org/10.3389/FPLS.2020.00933.
Zhang, H. Y., Dong, S. T., Gao, R. Q., & Li, Y. Q. (2007). Comparison of starch synthesis
and related enzyme activities in developing grains among different types of maize.
Journal of Plant Physiology and Molecular Biology, 33, 25–32. https://doi.org/10.1360
/aps07042.
Zheng, J., Chen, T., Wu, Q., Yu, J., & Chen, W. (2018). Effect of zeolite application on
phenology, grain yield and grain quality in rice under water stress. Agricultural Water
Management, 206, 241–251. https://doi.org/10.1016/j.agwat.2018.05.008.
Zhou, C., Huang, Y., Jia, B., Wang, Y., Wang, Y., Xu, Q., & Dou, F. (2018). Effects of
cultivar, nitrogen rate, and planting density on rice-grain quality. Agronomy, 8, 246.
https://doi.org/10.3390/AGRONOMY8110246.
Zhou, L., Liang, S., Ponce, K., Marundon, S., Ye, G., & Zhao, X. (2015). Factors affecting
head rice yield and chalkiness in indica rice. Field Crops Research, 172, 1–10. htt
ps://doi.org/10.1016/j.fcr.2014.12.004.
Zhu, D., Zhang, H., & Guo, B. (2017). Effects of nitrogen level on structure and
physicochemical properties of rice starch. Food Hydrocolloids, 63, 525–532. https://
doi.org/10.1016/j.foodhyd.2016.09.042.
Z. Chen et al.