1. Introduction
Lipids are one of the three main important nutritional components of rice (Oryza sativa L.), with brown rice and milled rice having 3% and 0.8% lipid contents, respectively [1,2]. Although the lipid content in rice is low, most of the fatty acid constituents are high-quality UFAs that have high nutritional value and health-promoting functions in the human body [3,4,5]. With increasing economic development and improvements in people’s standards of living, the demand for rice of higher quality is also increasing. Studies have shown that most high-quality rice cultivars share the same characteristics in terms of a high lipid content [6,7]. The lipid content in rice has a positive correlation with rice cooking and eating quality, and fatty acids also have a certain effect on rice taste [8,9]. We can significantly improve the eating quality of rice by increasing the content of UFAs [8,10]. Furthermore, lipids have a greater influence on rice eating quality than do other quality indicators [11,12] and only have a certain correlation with the amylose content of rice [13], which suggests that increasing the lipid content is one of the most effective ways to improve rice quality.
Nitrogen (N), P and potassium (K) are essential nutritional elements that play important roles in the process of rice growth and the formation of yield and quality. The lipid content and fatty acid components in rice are affected not only by genetics but also by environmental factors, cultivation methods and storage conditions [14,15]. Compared to other methods, the application of fertilizers is more controllable in field production. Thus, modifying fertilizer applications could be a better way to regulate lipid synthesis in rice. Previous studies have shown that fertilizer has a great effect on crop plant lipid content [15,16]. Applying fertilizers can improve the activities of key enzymes involved in lipid synthesis, such as acetyl-CoA carboxylase (ACCase), fatty acid synthase (FAS), glycerol 3-phosphate dehydrogenase (3-GPD), phosphatidyl phosphatase (PPase), glycerol 3-phosphate acyhransferase (GPAT) and the lipid content, all of which tend to increase first and then decrease with an increase in fertilizer [12,17]. The above findings indicate that the amount of fertilizer application has a positive regulatory effect on the activities of key enzymes of lipid metabolism in crop plants, and thus, has a significant effect on lipid synthesis and accumulation. P plays an integral role in energy metabolism, is a constituent of nucleic acids and membranes and is involved in many physiological and biochemical processes in plants [18]. Studies have shown that P can enhance the synthesis and transport of carbohydrates, promote N metabolism and lipid synthesis and improve the quality of tobacco [19]. Moreover, applying P fertilizer can improve the nutritional quality of rice [20]. Studies have also shown that P fertilizer has a greater effect on crop lipid content than does N or K application [21]. However, studies on the effects of fertilizer on the dynamic change regulation of lipid accumulation and lipid synthesis-related enzyme activities have mostly focused on oil crop species. In addition, there are limited studies on the effects of fertilizer on lipid synthesis compared with starch and proteins in rice, especially in response to P levels [11,12]. Thus, an experiment was conducted involving two rice cultivars and four P application levels. The objective of this study was to determine how P application regulates lipid synthesis and fatty acid components in rice and to provide theoretical and practical guidance for the improvement of rice eating quality.
2. Materials and Methods
2.1. Experimental Site Information
Field experiments were conducted during the growing seasons of 2019 and 2020 at the research farm of Sichuan Agricultural University, Chongzhou city, Sichuan Province, China (30°56′ N, 103°65′ E). Prior to the establishment of the field experiment, soil samples from the topsoil layer (0.20 m) were analyzed. The clay soil had the following nutrient contents in 2019 and 2020: 2.04 and 1.91 g kg−1 total N (Kjeldahl method, UDK-169, ITA); 17.50 and 18.91 mg kg−1 available P (Mo–Sb colorimetry after digestion with H2SO4 and HClO4); 19.20 and 21.50 g kg−1 organic matter (K2Cr2O7—volumetric method); 60.24 and 58.31 mg kg−1 available K (flame spectrometry after NH4OAc extraction) and 6.02 and 5.93 pH (tested in a sample containing a 1:2.5 ratio of soil to water).
2.2. Experimental Design
The experiment was conducted in a randomized block pattern with four treatments: P0, P1, P2 and P3 for 0, 45, 67.5 and 135 kg ha−1, respectively, and N fertilizer (135 kg ha−1) was used as basal manure and top dressing at a 3:7 ratio. A total of 12 treatments were performed with three repetitions. Two rice cultivars with significant differences in lipid content were used as the test materials. NJ 9108 (Jiangsu Academy of Agricultural Sciences) is a japonica rice cultivar and IR72 (International Rice Research Institute) is an indica rice cultivar, both with high yield and good quality. Seeds were sown on 16 April 2019 and 12 April 2020, and the seedlings were transplanted on 26 May 2019 and 16 May 2020, respectively. The area of each test plot was 5.0 m × 5.0 m, and the transplant density was 25 cm × 20 cm with two seedlings per hill. Urea (N, 46.4%) was used as the N source, superphosphate (P2O5, 12.0%) was used as the P source and potassium chloride (K2O, 60.0%) was used as the K source. Basal N (94.5 kg ha−1), P and K (135 kg ha−1) were applied to the soil 1 day (d) before transplanting. For the fertilizer treatments, ridges with plastic film were used for separation, and protection lines were established between the treatment blocks to ensure the isolation of the experiment. Field management, including the prevention and control of pests and weeds, was conducted according to local cultural practices.
2.3. Sampling
After flowering, approximately 300 panicles were selected on the same day and tagged for each plot. After full heading, 40 tagged panicles were sampled from each plot every 6 d at 10:00 am. The collected panicles were divided into three groups. Twenty tagged panicles were dried at 80 °C, after which the brown rice was crushed and sieved through a 100-mesh screen for measurements of lipid and protein contents. Another 10 tagged panicles were used to determine PA, MCA, PYR and OAA contents, and the remaining 10 tagged panicles were placed in liquid N for 3 min and then stored at −80 °C for enzymatic analysis. At harvest, 10 plants from each plot were sampled randomly and allowed to dry naturally in the sun to assess the rapid visco-analyzer (RVA) value, eating quality and fatty acid components after the material was stored at room temperature for 3 months.
2.4. Measurements and Methods
2.4.1. Lipid Content
Lipids in rice grains were obtained by ultrasound-assisted extraction (UAE) according to a previously reported method with a slight modification [22]. UAE was carried out with an ultrasonic cleaner (CPX3800H-C, Emerson Electric Co., St. Louis, MO, USA). Samples (2.000 g each) were weighed and extracted with 50 mL of n-hexane in a centrifuge tube and then mixed thoroughly by using a Vortex Genie (G560E, Scientific Industries Inc., Bohemia, NY, USA). The tube was immersed in an ultrasonic cleaner bath, and the lipids were extracted with the appropriate sonication power (110 W), duration (37 min) and temperature (42 °C). The supernatant was transferred to a centrifuge tube and then centrifuged (5430R, Eppendorf AG, Hamburg, Germany) for 10 min at 7000 r min−1. The supernatant was then transferred to a conical flask (weighed and recorded as m1 beforehand) and evaporated by using an electric hot plate (ML-3-4, Beijing Zhongxing Weiye Century Instrument Co., Ltd., Beijing, China), and the sample was ultimately dried and weighed (recorded as m2). The lipid content (m3) in the rice grain was then calculated by using the following formula: m3 = m2 − m1.
2.4.2. Free Fatty Acid Content
The FFA content from the UAE was measured according to a previously reported method [12]. The extracted lipids and 100 mL of diethyl ether/95% ethanol (v:v, 1:1) were mixed together, and 3 drops of phenolphthalein indicator were added to the mixture. Then, each mixture was titrated with 0.1 mol L−1 of KOH solution, unless the color changed to red, and the volume of the KOH solution used was recorded. The FFA content in the rice grain was calculated by using the following formula: ω = V × C × 282/m.
Here ω represents the FFA content (mg g−1), V represents the volume of KOH (mL), C represents the concentration of KOH (mol L−1), 282 is the molar mass of oleic acid (g mol−1) and m is the lipid content in the rice grain (g).
2.4.3. Fatty Acid Components
The fatty acid components from the UAE were measured by using a gas chromatograph-mass spectrometer (GC-MS) according to a previously reported method [22]. The extracted lipids and 1 mL of petroleum ether/benzene (v:v, 1:1) were mixed together and then flushed with 1 mL of petroleum ether/benzene. All the mixtures were collected and transferred into a 10 mL volumetric flask. The mixtures were neutralized with 0.4 mol L−1 of KOH/carbinol, mixed thoroughly, incubated at room temperature for 10 min and then brought to volume by the addition of water, followed by mixing. The organic layer was collected for analysis via the GC-MS (Agilent 7890-5975C, Agilent Technologies Co., Ltd., Santa Clara, CA, USA) and the NIST Mass Spectral Database (National Institute of Standards and Technology, Gaithersburg, MD, USA). The GC-MS conditions and components were as follows: carrier gas (He), approximately 1 mL min−1; oven temperature, initially maintained at 80 °C for 3 min, increased at 10 °C min−1 to 260 °C and then held for 15 min; injected sample, 1 μL; injection, split 100:1; and mass ranges, 20–500 m/z. Fatty acids were identified by comparisons with standard fatty acids. The masses of fatty acid methyl esters were quantified as percentages of the total methyl ester peak area.
2.4.4. Protein Content
The protein content was measured from the total N content of head rice with a conversion index of 5.95 via the Kjeldahl method.
2.4.5. Metabolites during Lipid Synthesis and Enzyme Activity Assay
Substances produced during lipid synthesis and enzyme activity were measured according to a previously reported method [12]. Based on the double antibody sandwich method, the optical density (OD) of samples was measured at 450 nm by using an ELISA Kit, and then the concentrations of metabolites and enzyme activity in the sample were calculated according to the standard curve.
2.4.6. Rapid Visco-Analyzer Value
A 3.0000 g sample and 25.0 mL of distilled water were added to a test tube. Pasting properties were measured by using an RVA device (3-D, Newport Scientific, Sydney, Australia) and analyzed with Thermal Cycle for Windows (TWC) software. Viscosity values were measured in centipoise (cP).
2.4.7. Eating Quality
The sensory properties of the cooked rice were measured by using a rice sensory analyzer (STA 1B, Satake Asia Co., Ltd., Tokyo, Japan). Milled rice (30.00 g) was washed in a stainless-steel container and then transferred into a 50 mL aluminum box containing 40 mL of water. The milled rice was cooked in a multifunctional, timed food steamer (GF-339, Goodway Electrical Enterprise Ltd., Hong Kong, China). After the cooking, the sensory properties of the cooked rice were determined. Cooked rice texture properties were measured by using a rice texture analyzer (RHS 1A, Satake Asia Co., Ltd., Tokyo, Japan).
2.5. Data Analysis
An analysis of variance (ANOVA) model was performed to test the effects of the P application rate on lipid accumulation and rice eating quality and the relationship of lipid content, lipid compositions, lipid synthesis-related enzyme activities and rice eating quality among different P treatments. For the analysis, year, cultivar, P treatment and sampling time were considered fixed effects, whereas the replicates were considered random effects. The means of each treatment were compared based on the least significant difference (LSD) test at the 0.05 probability level by using SPSS 20.0 (Statistical Product and Service Solutions Inc., Chicago, IL, USA). Origin Pro 2020 (OriginLab, Northampton, MA, USA) was used to draw the figures. The differences of the main indicators are shown in Table 1.
3. Results
3.1. Effects of Phosphorus Application Rate on Lipid Accumulation
During the grain filling process, the lipid content in rice grains showed a tendency to decrease gradually (Figure 1). As the P application level increased, the lipid contents of NJ 9108 and IR72 increased. The lipid contents of both NJ 9108 and IR72 tended to be in the order of P3 > P2 > P1 > P0 at 36 d after flowering, whereas the lipid content of NJ 9108 under the P3 treatment was significantly higher than that under the other treatments. Compared with that under P0, the lipid content of NJ 9108 under P3, P2 and P1 increased by 9.2%, 3.4% and 0.5%, respectively, and the lipid content of IR72 increased by 8.3%, 3.1% and 1.4%, respectively. The two-year test results showed the same trend. In 2020, the lipid content of NJ 9108 at 36 d after flowering under P3, P2 and P1 increased by 11.8%, 9.6% and 2.3%, respectively, when compared with that under P0. The lipid content of IR72 under P3 and P2 increased by 8.0% and 7.2%, respectively, when compared with that under P0. The increase in lipid content of NJ 9108 was higher than that of IR72 under the P3 treatment. One possible reason for this might be that the lipid content of NJ 9108 was higher than that of IR72. As a result, lipid accumulation was more easily affected by the P application to NJ 9108. Taken together, these results indicated that the application of P could increase the lipid content in rice grains. Both NJ 9108 and IR72 achieved the highest lipid content in response to the P application level of 135 kg ha−1.
3.2. Effects of Phosphorus Application Rate on Free Fatty Acid Accumulation
During the grain filling process, the FFA contents of both NJ 9108 and IR72 decreased gradually and then stabilized (Figure 2). In 2019, the FFA contents of NJ 9108 and IR72 decreased rapidly from 6 d to 12 d after flowering, and there were significant differences between all treatments at 6 d after flowering. In 2020, the FFA contents of both cultivars decreased slowly from 6 d to 18 d after flowering, and significant differences between all treatments were detected at 6 d and 12 d after flowering. The FFA contents of both NJ 9108 and IR72 tended to be in the order of P3 > P2 > P1 > P0 during the entire filling stage. In 2019, the FFA contents under P1, P2 and P3 increased by 13.3%, 14.7% and 26.0% for NJ 9108 and by 16.6%, 17.7% and 43.2% for IR72, respectively, when compared with that under P0. In 2020, the FFA contents under P1, P2 and P3 increased by 20.9%, 15.9% and 31.5% for NJ 9108 and by 1.2%, 13.7% and 38.0% for IR72, respectively, when compared with that under P0. Taken together, these results indicated that P could increase the FFA content in rice grains. The highest FFA content was obtained in response to the P application level of 135 kg ha−1 for both NJ 9108 and IR72.
3.3. Effects of Phosphorus Application Rate on Fatty Acid Composition
The fatty acid composition of each rice cultivar analyzed is shown in Table 2. In both cultivars, the most abundant fatty acids found were oleic acid (C18:1), linoleic acid (C18:2), palmitic acid (C16:1) and stearic acid (C18:0). These four fatty acids accounted for more than 94% of the total fatty acid content in the rice grain. No significant impact was observed on fatty acid composition between the four P levels. As more P was gradually applied, the UFA content increased, but the SFA content decreased. Under the P0 treatment, the UFA content of NJ 9108 was significantly lower than that under the other treatments, whereas the SFA content showed the opposite trend. When compared with that under P0, the UFA content under P3 increased by 2.46 percentage points. Under the P3 treatment, the UFA content of IR72 was significantly higher than that under the other treatments, whereas the SFA content showed the opposite trend. When compared with that under P0, the UFA content under P3 increased by 0.68 percentage points. Taken together, these results suggested that increasing amounts of P could increase the UFA content but decrease the SFA content in the rice grain. The highest UFA content and lowest SFA content were obtained in response to the P application level of 135 kg ha−1 for both NJ 9108 and IR72.
3.4. Effects of Phosphorus Application Rate on the Activities of Key Enzymes Involved in Lipid Synthesis
ACCase, FAS, 3-GPD, PPase and GPAT are the key enzymes involved in lipid synthesis in rice grains. PEPCase and ACCase compete for the same PYR substrate and can catalyze PYR into OAA and acetyl-CoA (A-CoA), respectively. The enzyme activities of NJ 9108 and IR72 first increased and then decreased with the grain filling process (Figure 3 and Figure 4). As more P was gradually applied, the ACCase, FAS, 3-GPD, PPase and GPAT activities of NJ 9108 and IR72 showed significant increases and both followed the trend of P3 > P2 > P1 > P0 at the peak stage. PEPCase activities in NJ 9108 and IR72 both increased first and then decreased (Figure 4E,F). The activities of PEPCase at the peak stage followed the trend of P2 > P3 > P1 > P0, and the maximum value was observed under P2. Overall, the results indicated that the activities of key enzymes involved in lipid synthesis in rice grains could be enhanced by increasing P application levels. The highest activities of ACCase, FAS, 3-GPD, PPase and GPAT were obtained in response to a P application level of 135 kg ha−1, and the highest activities of PEPCase were obtained in response to a P application level of 67.5 kg ha−1.
3.5. Effects of Phosphorus Application Rate on Metabolite Accumulation during Lipid Synthesis
PYR is the initial substrate in lipid synthesis in rice grains, and MCA and PA are important metabolites during lipid synthesis. The content of these metabolites in rice grains can indicate the activity of lipid synthesis. During the grain filling process, the PYR, MCA and PA contents of NJ 9108 and IR72 first increased and then decreased (Figure 5). However, no significant differences in PYR content were found with increasing P application, whereas the MCA and PA contents increased significantly. These results indicated that increases in P application levels did not enhance the PYR content but significantly increased the MCA and PA contents. The increase in MCA and PA contents might be due to the increase in the activities of key enzymes involved in their synthesis, which was beneficial to lipid synthesis as a result.
3.6. Effects of Phosphorus Application Rate on Protein Accumulation
During the grain filling process and as more P was gradually applied, the protein contents of NJ 9108 and IR72 first increased and then decreased. However, the OAA contents showed the opposite trend (Figure 6 and Figure 7). In 2019, the protein contents of both NJ 9108 and IR72 followed the trend of P2 > P1 > P0 > P3 at 36 d after flowering. Under the P2 treatment, the protein contents of the two cultivars were significantly higher than those under the other treatments (except P1 in IR72). Compared with that under P0, the protein content under P1, P2 and P3 increased by 4.0%, 9.3% and −7.5% for NJ 9108 and by 3.9%, 4.2% and −2.7% for IR72, respectively. Similar results were detected in 2020. Taken together, these results indicated that the protein content in rice grains could be increased with certain P fertilizer levels, and the highest protein content was obtained at the P level of 67.5 kg ha−1. The OAA content represents the activity level of OAA synthesis from PYR. Correlation analysis showed that the OAA content had a positive correlation with the protein content of NJ 9108 (r = 0.686) and IR72 (r = 0.620). These results indicated that increasing the application rate of P fertilizer could increase the activity level of OAA synthesis, which could increase the protein content as a result. Protein synthesis benefited the most in response to the P level of 67.5 kg ha−1.
3.7. Effects of Phosphorus Application Rate on Rice Eating Quality
In 2019, the peak viscosity and breakdown viscosity of NJ 9108 and IR72 increased significantly as more P was gradually applied (Table 3). In contrast, the final viscosity, setback viscosity and pasting temperature decreased significantly. There were no significant differences in trough viscosity or peak time between the four P levels. With the exception of breakdown viscosity, all the RVA profile characteristics of IR72 were higher than those of NJ 9108. A similar trend was found in 2020. Previous studies showed that higher peak viscosity and breakdown viscosity and lower final viscosity, setback viscosity and pasting temperature could lead to improved rice eating quality. In 2019, the taste value, parameter and appearance of NJ 9108 and IR72 rice increased as more P was gradually applied (Table 4). No significant differences in hardness, stickiness or balance were observed between the four P levels. Compared to IR72, NJ 9108 had a higher taste value, parameter, appearance, stickiness and balance, but a lower hardness. These results indicated that the application of P fertilizer could improve rice eating quality and that NJ 9108 rice had a better eating quality than IR72 (Table 5).
4. Discussion
4.1. Effects of Phosphorus Application Rate on the Activities of Key Enzymes Involved in Lipid Synthesis and Lipid Accumulation
The lipid content in rice grains was determined by the combined effects of the activities of key enzymes involved in lipid synthesis, such as ACCase, FAS, 3-GPD, PPase and GPAT [23,24,25,26]. PA is the initial substrate for both lipid and protein synthesis; PA can be converted to MCA by ACCase as part of lipid synthesis or converted to OAA by PEPCase as part of protein synthesis. Thus, there is competition between ACCase and PEPCase for the same substrate. High ACCase concentrations can decrease PEPCase activity, which could promote the ACCase-catalyzed conversion of more PA in the lipid synthesis pathway. Therefore, PEPCase is the key enzyme that can balance the lipid and protein contents in rice grains [27]. The activities of these enzymes are not only regulated by genetic characteristics but also affected by other factors, such as the amount of fertilizer applied [11,12]. Prior to this study, little information was available that described the effects of different P levels on rice lipid content. In the present study, we observed that ACCase, FAS, 3-GPD, PPase and GPAT activities increased as more P was gradually applied. Moreover, the activities of these enzymes still increased when conventional P application rates were exceeded in the field. This suggests that the amount of P applied was probably not large enough. With the increasing application of P, PEPCase activity first increased and then decreased. ACCase and PEPCase activities increased simultaneously at P levels ranging from 0 kg ha−1 to 67.5 kg ha−1. However, the ACCase activity continued to increase when the P application rate exceeded 135 kg ha−1, whereas the PEPCase activity decreased. These results indicated that PEPCase activity could start to decrease only when ACCase activity reached a certain level. The contents of MCA and PA continued to increase at P application levels ranging from 0 kg ha−1 to 135 kg ha−1. As a consequence, lipid synthesis became more active, which in turn increased the lipid content in rice grains. The protein and OAA contents in the rice grains first increased and then decreased with an increasing P application level, and the peak value was obtained in response to the P application level of 67.5 kg ha−1. The protein and lipid contents increased simultaneously at P levels ranging from 0 kg ha−1 to 67.5 kg ha−1. However, the lipid content continued to increase when the P application level exceeded 135 kg ha−1, whereas the protein content decreased. Taken together, these results showed that a high P level was more beneficial for lipid synthesis than for protein synthesis. Further analysis showed that PEPCase activity was strongly correlated with the protein content of NJ 9108 (r = 0.171) and IR72 (r = 0.019).
4.2. Relationship between Lipid Content and Rice Eating Quality
Previous studies have yielded different conclusions on the effects of lipid content on rice grain quality. Some studies have reported that high quality rice is characterized by a high lipid content, rich flavor, good luster and good palatability [7,8,11]. Compared to rice grain starch and protein contents, lipid content, especially the starch lipid content in milled rice, had a significant effect on the cooking and eating quality of rice, which increases with an increase in starch lipid content in milled rice [11,28]. Rice cultivars with high eating quality normally show higher breakdown viscosity and lower setback viscosity, as determined by the RVA. In the present study, we observed that with the increasing P level, the lipid content in rice grains increased; the peak viscosity and breakdown viscosity increased significantly; and the final viscosity, setback viscosity and pasting temperature decreased significantly. The taste value, parameter and appearance of rice increased; this was the case especially for the taste value, which increased significantly. UFAs accounted for approximately 75% of the total fatty acids in rice grains and not only had high nutritional value, but also were closely associated with rice cooking and eating quality [29]. Increasing the UFA content could significantly improve the eating quality of rice [9]. In general, rice cultivars that have better eating quality have higher starch lipid and linoleic acid contents [10]. In addition, the UFA content in rice grains showed a significant relationship with palatability [8]. In this study, four main fatty acids, oleic acid (C18:1), linoleic acid (C18:2), palmitic acid (C16:1) and stearic acid (C18:0), were detected in both cultivars, which accounted for more than 94% of the total fatty acid content in the rice grains. The UFA content increased with increasing P application, and the SFA content decreased. The RVA results showed that the highest breakdown viscosity and lowest setback viscosity were observed under P3 in both NJ 9108 and IR72; this treatment also resulted in the highest UFA content and lowest SFA content, in agreement with the results of previous studies. Another explanation for this is that SFAs preferentially form amylose fatty acid complexes with starch granules, which could significantly affect the gelatinization properties of starch. However, unsaturated bonds in UFAs could suppress the formation of these complexes, which might be the key reason for the decrease in breakdown viscosity [30]. Although lipids were present in small amounts in rice relative to those of starch and protein, lipid components could greatly influence the eating quality of cooked rice. This study found that applying more P fertilizer could improve rice lipid content and eating quality. The increase in FFA content in rice grains was due to the increase in the P application rate, which stimulated lipid synthesis. The improvement in rice eating quality was mainly caused by the increase in the UFA proportion of FFAs. Therefore, more attention should be given to the accumulation of UFAs while increasing the lipid content in rice.
5. Conclusions
Although lipids have lower contents than other compositions, such as starch and protein, they are regarded as one of the main factors that influence the cooking and eating qualities of rice cultivars. However, due to the poor content and difficult testing method of lipids, there are limited studies on the effects of fertilizer on lipid synthesis and rice eating quality. Increasing the application of P fertilizer could optimize fatty acid components and increase lipid contents by enhancing lipid synthesis-related enzyme activities, improving rice eating quality as a result. The maximum protein content was obtained in response to the P application level of 67.5 kg ha−1, and the highest rice lipid content and eating quality were observed in response to the P application level of 135 kg ha−1. Therefore, the optimal P application rate for both NJ 9108 and IR72 lipid synthesis was 135 kg ha−1. The present study indicates that increasing the application rate of P could be used as a simple and easy practice to achieve high lipid content and eating quality of rice and provides theoretical and practical guidance for the cooperative improvement of lipids and quality.
Investigation, methodology and writing—original draft, L.P. and G.C.; data curation, Y.T. and J.W.; investigation and methodology, M.H., C.L. and X.H.; supervision and validation, Y.L.; conceptualization, funding acquisition, supervision and validation, T.L. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Not applicable.
The data presented in this study are available on request from the authors.
We would like to thank our teacher for carefully reading and correcting our manuscript and providing technical assistance and financial support for the study, as well as our scientific research team for their contribution to this paper.
The authors declare that they have no known competing financial interests or personal relationships that could appear to influence the work reported in this paper.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Enlarge this image.Figure 1. Effects of P application rate on lipid accumulation of NJ 9108 and IR72. P0, P1, P2 and P3 refer to the different fertilizer treatments (0, 45, 67.5 and 135 kg ha−1, respectively). DW represents dry weight, lower case letters indicate that the physical and chemical properties of both cultivars are significantly different with the different treatments (p < 0.05, LSD method). The data presented are the mean ± standard deviation, n = 3.
Enlarge this image.Figure 2. Effects of P application rate on FFA accumulation of NJ 9108 and IR72. P0, P1, P2 and P3 refer to the different fertilizer treatments (0, 45, 67.5 and 135 kg ha−1, respectively). DW represents dry weight. The data presented are the mean ± standard deviation, n = 3.
Enlarge this image.Figure 3. Effects of P application rate on the activities of ACCase (A,B), FAS (C,D) and 3-GPD (E,F) of NJ 9108 and IR72. P0, P1, P2 and P3 refer to the different fertilizer treatments (0, 45, 67.5 and 135 kg ha−1, respectively). FW represents fresh weight. The data presented are the mean ± standard deviation, n = 3.
Enlarge this image.Figure 4. Effects of P application rate on the activities of PPase (A,B), GPAT C,D) and PEPCase E,F) of NJ 9108 and IR72. P0, P1, P2 and P3 refer to the different fertilizer treatments (0, 45, 67.5 and 135 kg ha−1, respectively). FW represents fresh weight. The data presented are the mean ± standard deviation, n = 3.
Enlarge this image.Figure 5. Effects of P application rate on the contents of PYR (A,B), MCA (C,D) and PA (E,F) of NJ 9108 and IR72. P0, P1, P2 and P3 refer to the different fertilizer treatments (0, 45, 67.5 and 135 kg ha−1, respectively). FW represents fresh weight. The data presented are the mean ± standard deviation, n = 3.
Enlarge this image.Figure 6. Effects of P application rate on protein accumulation of NJ 9108 and IR72. P0, P1, P2 and P3 refer to the different fertilizer treatments (0, 45, 67.5 and 135 kg ha−1, respectively). DW represents dry weight, lower case letters indicate that the physical and chemical properties of both cultivars are significantly different with the different treatments (p < 0.05, LSD method). The data presented are the mean ± standard deviation, n = 3.
Enlarge this image.Figure 7. Effects of P application rate on OAA contents of NJ 9108 and IR72. P0, P1, P2 and P3 refer to the different fertilizer treatments (0, 45, 67.5 and 135 kg ha−1, respectively). FW represents fresh weight.
Analysis of variance on lipid contents, key enzymes activities and taste value of NJ 9108 and IR72.
| ANOVA | Lipid | SFA | UFA | FFA | Protein | Taste Value | ACCase | PEP Case | MCA | PA | OAA |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Year (Y) | 922.76 ** | 1.73 ns | 3.25 ns | 6.53 * | 183.78 ** | 119.23 ** | 0.27 ns | 1.21 ns | 0.65 ns | 0.03 ns | 1.14 ns |
| Cultivar (C) | 292.96 ** | 66.84 ** | 53.82 ** | 0.89 ns | 286.87 ** | 1526.26 ** | 0.68 ns | 1797.31 ** | 0.27 ns | 204.74 ** | 5.27 ns |
| Treatment (T) | 17.72 ** | 12.32 ** | 9.92 ** | 37.46 ** | 124.48 ** | 18.70 ** | 245.59 ** | 19454.39 ** | 2.24 ns | 401.07 ** | 25.71 ** |
| Y × C | 47.38 ** | 17.07 ** | 13.74 ** | 2.15 ns | 7.50 * | 0.06 ns | 108.16 ** | 8749.27 ** | 1.21 ns | 216.39 ** | 14.08 ** |
| Y × T | 2.51 ns | 5.68 * | 24.37 ** | 0.51 ns | 21.40 ** | 1.20 ns | 11.52* * | 167.85 ** | 0.57 ns | 17.32 ** | 4.32 * |
| C × T | 0.64 ns | 5.22 * | 4.21 ns | 2.42 ns | 9.07 ** | 2.14 ns | 6.55 * | 361.48 ** | 0.48 ns | 35.59 ** | 5.39 * |
SFA, UFA, FFA, MCA, PA and OAA represent the saturated fatty acid, unsaturated fatty acid, free fatty acid, malonyl CoA, phosphatidic acid and oxaloacetic acid, respectively. ANOVA p values and symbols were defined as: * p < 0.05; ** p < 0.01; ns: p > 0.05.
Effects of P application rate on fatty acid composition in rice grains (%).
| Cultivar | NJ 9108 | IR72 | ||||||
|---|---|---|---|---|---|---|---|---|
| P level | P0 | P1 | P2 | P3 | P0 | P1 | P2 | P3 |
| Lauric acid, C12:0 | 0.49 ± 0.18 a | 0.21 ± 0.00 b | 0.59 ± 0.04 a | 0.22 ± 0.02 b | 0.49 ± 0.00 a | 0.41 ± 0.26 a | 0.41 ± 0.30 a | 0.24 ± 0.04 a |
| Myristic acid, C14:0 | 0.48 ± 0.07 a | 0.54 ± 0.05 a | 0.47 ± 0.07 a | 0.46 ± 0.03 a | 0.36 ± 0.01 bc | 0.39 ± 0.01 a | 0.38 ± 0.00 ab | 0.35 ± 0.01 c |
| Palmitoleic acid, C16:1 | 0.29 ± 0.12 a | 0.26 ± 0.00 a | 0.22 ± 0.02 a | 0.21 ± 0.01 a | 0.33 ± 0.03 a | 0.25 ± 0.03 b | 0.28 ± 0.01 ab | 0.28 ± 0.03 ab |
| Palmitic acid, C16:0 | 20.27 ± 1.26 a | 19.74 ± 0.14 a | 19.47 ± 0.14 a | 18.84 ± 0.17 a | 21.73 ± 0.12 b | 21.29 ± 0.10 b | 21.47 ± 0.04 ab | 21.19 ± 0.12 a |
| Linoleic acid, C18:2 | 33.77 ± 1.00 ab | 35.85 ± 1.04 a | 33.32 ± 0.36 b | 33.77 ± 0.98 ab | 32.50 ± 1.07 a | 32.78 ± 1.19 a | 31.86 ± 0.43 a | 32.06 ± 0.16 a |
| Oleic acid, C18:1 | 36.49 ± 5.08 a | 36.06 ± 1.35 a | 39.29 ± 1.11 a | 39.12 ± 1.26 a | 37.64 ± 1.08 a | 37.56 ± 0.96 a | 38.43 ± 0.37 a | 38.83 ± 0.04 a |
| Stearic acid, C18:0 | 3.52 ± 0.80 a | 3.67 ± 0.17 a | 3.23 ± 0.38 a | 3.29 ± 0.19 a | 3.18 ± 0.08 a | 3.26 ± 0.03 a | 3.14 ± 0.10 a | 3.19 ± 0.04 a |
| Linolenic acid, C18:3 | 0.32 ± 0.06 a | 0.40 ± 0.05 a | 0.31 ± 0.05 a | 0.42 ± 0.27 a | 0.21 ± 0.02 a | 0.22 ± 0.01 a | 0.36 ± 0.18 a | 0.20 ± 0.00 a |
| Gadoleic acid, C20:1 | 1.10 ± 0.37 a | 0.93 ± 0.01 a | 0.88 ± 0.06 a | 0.92 ± 0.07 a | 0.97 ± 0.00 a | 4.03 ± 0.00 a | 0.99 ± 0.04 a | 0.98 ± 0.01 a |
| Arachidic acid, C20:0 | 1.35 ± 0.71 a | 0.92 ± 0.08 a | 0.89 ± 0.06 a | 0.95 ± 0.08 a | 1.37 ± 0.00 a | 1.42 ± 0.01 a | 1.40 ± 0.03 a | 1.40 ± 0.01 a |
| Heneicosanoic acid, C21:0 | 0.39 ± 0.07 a | 0.37 ± 0.03 a | 0.38 ± 0.09 a | 0.52 ± 0.07 a | ― | ― | ― | ― |
| Docosanoic acid, C22:0 | 0.51 ± 0.38 a | 0.30 ± 0.03 a | 0.27 ± 0.04 a | 0.35 ± 0.03 a | 0.49 ± 0.02 a | 0.56 ± 0.03 a | 0.51 ± 0.01 a | 0.51 ± 0.04 a |
| Tetracosanoic acid, C24:0 | 0.79 ± 0.61 a | 0.45 ± 0.05 a | 0.40 ± 0.06 a | 0.55 ± 0.01 a | 0.72 ± 0.02 a | 0.84 ± 0.05 a | 0.78 ± 0.02 a | 0.78 ± 0.08 a |
| Hexacosanoic acid, C26:0 | 0.23 ± 0.05 b | 0.31 ± 0.00 ab | 0.28 ± 0.01 ab | 0.38 ± 0.07 a | ― | ― | ― | ― |
| UFA | 71.97 ± 0.69 b | 73.49 ± 0.27 a | 74.02 ± 0.62 a | 74.43 ± 0.47 a | 71.66 ± 0.01 b | 71.85 ± 0.19 b | 71.92 ± 0.17 b | 72.34 ± 0.08 a |
| SFA | 28.03 ± 0.69 a | 26.51 ± 0.27 b | 25.98 ± 0.62 b | 25.57 ± 0.47 b | 28.34 ± 0.01 a | 28.15 ± 0.19 a | 28.08 ± 0.17 a | 27.66 ± 0.08 b |
P, SFA and UFA represent the phosphorus, saturated fatty acid and unsaturated fatty acid, respectively. Lower case letters indicate that the fatty acid composition of both cultivars is significantly different with the different treatments (p < 0.05, LSD method). The data presented are the mean ± standard deviation, n = 3.
Effects of P application rate on the RVA profile characters of rice.
| Year | Cultivar | P Level | Peak Viscosity |
Trough Viscosity |
Breakdown Viscosity |
Final Viscosity |
Setback Viscosity |
Peak Time |
Pasting Temperature |
|---|---|---|---|---|---|---|---|---|---|
| 2019 | NJ 9108 | P0 | 158.97 ± 9.13 b | 92.22 ± 4.66 c | 41.14 ± 4.33 b | 201.56 ± 5.06 a | 24.81 ± 3.04 a | 5.62 ± 0.04 c | 72.10 ± 0.20 a |
| P1 | 159.83 ± 8.63 b | 144.83 ± 4.07 a | 41.97 ± 3.81 b | 187.36 ± 5.14 b | 15.58 ± 5.31 a | 6.31 ± 0.08 a | 71.29 ± 1.05 a | ||
| P2 | 184.75 ± 3.10 a | 117.86 ± 9.33 b | 48.89 ± 4.98 b | 171.19 ± 9.46 c | 11.36 ± 2.99 b | 6.09 ± 0.14 b | 67.70 ± 1.10 b | ||
| P3 | 185.97 ± 0.27 a | 135.86 ± 6.44 a | 66.75 ± 4.64 a | 134.17 ± 6.19 d | 4.50 ± 1.26 c | 6.13 ± 0.07 b | 66.21 ± 0.82 b | ||
| IR72 | P0 | 141.28 ± 8.60 d | 221.25 ± 9.75 a | –0.97 ± 0.32 c | 325.11 ± 3.92 a | 122.06 ± 4.63 a | 6.73 ± 0.12 b | 89.14 ± 1.24 a | |
| P1 | 174.42 ± 6.74 c | 194.53 ± 3.54 b | 0.58 ± 0.14 c | 322.06 ± 9.14 a | 115.47 ± 2.78 a | 6.73 ± 0.12 b | 83.99 ± 1.52 b | ||
| P2 | 200.00 ± 4.77 b | 142.25 ± 8.30 d | 5.47 ± 2.07 b | 276.56 ± 8.79 b | 102.14 ± 9.38 b | 7.00 ± 0.00 a | 81.83 ± 2.38 bc | ||
| P3 | 244.44 ± 7.49 a | 172.83 ± 4.88 c | 23.19 ± 2.29 a | 256.75 ± 9.06 c | 80.67 ± 3.66 c | 6.93 ± 0.07 a | 79.91 ± 0.84 c | ||
| 2020 | NJ 9108 | P0 | 172.96 ± 0.76 c | 99.13 ± 1.59 b | 60.25 ± 0.59 b | 170.17 ± 8.37 a | –2.11 ± 1.00 a | 5.78 ± 0.14 a | 73.77 ± 0.96 a |
| P1 | 173.75 ± 0.24 c | 102.64 ± 5.66 b | 76.39 ± 5.03 a | 175.75 ± 0.24 a | –28.08 ± 6.01 b | 6.10 ± 0.14 a | 72.98 ± 0.25 a | ||
| P2 | 179.03 ± 0.67 b | 112.71 ± 0.18 ab | 74.63 ± 1.35 a | 143.92 ± 5.22 b | –35.11 ± 4.62 b | 5.80 ± 0.00 a | 72.76 ± 0.23 a | ||
| P3 | 198.25 ± 2.36 a | 119.88 ± 9.37 a | 78.38 ± 7.01 a | 143.29 ± 1.82 b | –30.46 ± 1.59 b | 6.00 ± 0.18 a | 72.74 ± 0.23 a | ||
| IR72 | P0 | 177.09 ± 1.29 c | 250.46 ± 5.60 a | 1.35 ± 0.14 a | 546.11 ± 21.22 a | 302.97 ± 20.43 a | 6.97 ± 0.05 a | 86.60 ± 1.13 a | |
| P1 | 218.14 ± 4.22 b | 242.17 ± 9.95 a | 1.21 ± 0.12 a | 508.00 ± 14.38 b | 257.54 ± 8.43 b | 6.93 ± 0.07 a | 82.29 ± 0.44 ab | ||
| P2 | 250.46 ± 5.95 a | 177.92 ± 1.65 c | –0.83 ± 0.35 a | 432.95 ± 6.49 c | 225.58 ± 4.95 bc | 7.00 ± 0.00 a | 82.28 ± 2.79 ab | ||
| P3 | 251.81 ± 2.57 a | 218.14 ± 4.14 b | –12.22 ± 2.01 b | 402.67 ± 3.66 c | 214.81 ± 7.59 c | 6.96 ± 0.08 a | 81.32 ± 0.19 b |
P represents phosphorus. Lower case letters indicate that the physical and chemical properties of both cultivars are significantly different with the different treatments (p < 0.05, LSD method). The data presented are the mean ± standard deviation, n = 3.
Effects of P application rate on the eating quality of rice.
| Year | Cultivar | P Level | Taste Value | Parameter | Appearance | Hardness | Stickiness | Balance |
|---|---|---|---|---|---|---|---|---|
| 2019 | NJ 9108 | P0 | 79.67 ± 1.53 b | 7.07 ± 0.32 c | 7.00 ± 0.35 b | 2.65 ± 0.40 a | 0.56 ± 0.06 a | 0.21 ± 0.02 ab |
| P1 | 83.67 ± 0.58 a | 7.50 ± 0.10 b | 7.40 ± 0.20 ab | 3.38 ± 0.30 a | 0.57 ± 0.06 a | 0.17 ± 0.01 b | ||
| P2 | 84.00 ± 1.00 a | 7.80 ± 0.10 ab | 7.50 ± 0.17 a | 2.77 ± 0.49 a | 0.66 ± 0.10 a | 0.24 ± 0.01 a | ||
| P3 | 84.33 ± 0.58 a | 7.87 ± 0.15 a | 7.53 ± 0.15 a | 3.06 ± 0.50 a | 0.68 ± 0.07 a | 0.22 ± 0.04 a | ||
| IR72 | P0 | 68.00 ± 2.00 b | 6.33 ± 0.32 a | 5.87 ± 0.31 a | 4.85 ± 0.20 a | 0.01 ± 0.01 b | 0.00 ± 0.00 a | |
| P1 | 69.00 ± 2.00 b | 6.47 ± 0.25 a | 5.97 ± 0.25 a | 5.09 ± 0.37 a | 0.01 ± 0.01 b | 0.00 ± 0.00 a | ||
| P2 | 69.33 ± 0.58 ab | 6.57 ± 0.15 a | 6.03 ± 0.12 a | 5.31 ± 0.33 a | 0.04 ± 0.01 a | 0.01 ± 0.00 a | ||
| P3 | 72.00 ± 1.00 a | 6.70 ± 0.10 a | 6.20 ± 0.10 a | 5.40 ± 0.33 a | 0.02 ± 0.01 b | 0.00 ± 0.00 a | ||
| 2020 | NJ 9108 | P0 | 85.67 ± 0.58 b | 8.03 ± 0.15 c | 7.80 ± 0.17 c | 4.03 ± 0.28 a | 1.27 ± 0.21 ab | 0.33 ± 0.02 a |
| P1 | 86.67 ± 0.58 ab | 8.33 ± 0.06 b | 8.10 ± 0.00 b | 4.09 ± 0.43 a | 1.04 ± 0.07 b | 0.26 ± 0.01 b | ||
| P2 | 87.00 ± 1.00 a | 8.27 ± 0.06 b | 8.20 ± 0.10 b | 4.63 ± 0.49 a | 1.35 ± 0.12 a | 0.29 ± 0.02 ab | ||
| P3 | 87.67 ± 0.58 a | 8.57 ± 0.15 a | 8.53 ± 0.21 a | 4.10 ± 0.35 a | 1.33 ± 0.03 a | 0.32 ± 0.03 a | ||
| IR72 | P0 | 71.67 ± 0.58 b | 7.17 ± 0.31 b | 6.17 ± 0.31 b | 4.27 ± 0.10 a | 0.03 ± 0.00 a | 0.01 ± 0.00 a | |
| P1 | 72.33 ± 1.53 b | 7.23 ± 0.12 ab | 6.30 ± 0.10 ab | 4.65 ± 0.27 a | 0.02 ± 0.01 ab | 0.00 ± 0.00 a | ||
| P2 | 73.67 ± 1.53 ab | 7.37 ± 0.15 ab | 6.47 ± 0.15 ab | 4.86 ± 0.51 a | 0.02 ± 0.01 ab | 0.01 ± 0.01 a | ||
| P3 | 75.33 ± 1.15 a | 7.53 ± 0.06 a | 6.57 ± 0.06 a | 4.79 ± 0.31 a | 0.01 ± 0.00 b | 0.00 ± 0.01 a |
P represents phosphorus. Lower case letters indicate that the eating quality of both cultivars are significantly different with the different treatments (p < 0.05, LSD method). The data presented are the mean ± standard deviation, n = 3.
Correlation coefficients between lipid contents, key enzymes activities and taste value of NJ 9108 (below the diagonal) and IR72 (above the diagonal).
| Index | Lipid | SFA | UFA | FFA | Protein | Taste Value | ACCsase | PEPCase | MCA | PA | OAA | P Level |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Lipid | −0.992 ** | 0.992 ** | 0.468 | −0.589 | 0.993 ** | 0.996 ** | 0.653 | 0.987 * | 0.958 * | −0.312 | 0.946 | |
| SFA | −0.778 | −1.000 ** | −0.397 | 0.534 | −0.998 ** | −0.989 * | −0.662 | −0.983 * | −0.970 * | 0.263 | −0.950 | |
| UFA | 0.778 | −1.000 ** | 0.397 | −0.534 | 0.998 ** | 0.989 * | 0.662 | 0.983 * | 0.970 * | −0.263 | 0.950 | |
| FFA | 0.882 | −0.957 * | 0.957 * | −0.984 * | 0.445 | 0.394 | −0.285 | 0.333 | 0.194 | −0.961 * | 0.173 | |
| Protein | −0.607 | 0.09 | −0.090 | −0.369 | −0.579 | −0.516 | 0.019 | −0.457 | −0.332 | 0.620 | −0.301 | |
| Taste value | 0.617 | −0.971 * | 0.971 * | 0.899 | 0.054 | 0.985 * | 0.621 | 0.975 * | 0.956 * | −0.317 | 0.932 | |
| ACCase | 0.909 | −0.969 * | 0.969 * | 0.983 * | −0.301 | 0.887 | 0.721 | 0.998 ** | 0.977 * | −0.225 | 0.972 * | |
| PEPCase | 0.671 | −0.930 | 0.930 | 0.805 | 0.171 | 0.888 | 0.879 | 0.766 | 0.822 | 0.494 | 0.862 | |
| MCA | 0.997 ** | −0.723 | 0.723 | 0.842 | −0.655 | 0.549 | 0.871 | 0.615 | 0.988 * | −0.158 | 0.986 * | |
| PA | 0.742 | −0.998 ** | 0.998 ** | 0.945 | −0.046 | 0.982* | 0.954 * | 0.931 | 0.684 | −0.031 | 0.995 ** | |
| OAA | 0.522 | −0.492 | 0.492 | 0.360 | 0.686 | 0.350 | 0.527 | 0.740 | 0.510 | 0.474 | 0.012 | |
| P level | 0.932 | −0.949 | 0.949 | 0.963 * | −0.314 | 0.847 | 0.995 ** | 0.881 | 0.899 | 0.930 | 0.593 |
P, SFA, UFA, FFA, MCA, PA and OAA represent phosphorus, saturated fatty acid, unsaturated fatty acid, free fatty acid, malonyl CoA, phosphatidic acid and oxaloacetic acid, respectively. ANOVA p values and symbols were defined as: * p < 0.05; ** p < 0.01.
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