INTRODUCTION
Corn is the main energy feed ingredient for animal production [1]. However, corn shortages and distribution difficulties continue unabated due to its high usage in animal and human food, which affects national food security. Since 2020 in China, the National Animal Nutrition Guidance Committee has drawn up several strategies to reduce the utilization of corn and soybean meal in swine and poultry production. One of the strategies emphasized the utilization of paddy rice and its by-products as alternatives to corn. Brown rice contains more energy and protein and has better palatability and nutritional value compared with paddy rice [2,3]. The production of brown rice in China, approximate 2.4 million tons, ranks the first all over the world [2].
Brown rice, known as whole grain rice, consists of 2% to 3% germ, 6% to 7% of bran and 90% of endosperm after removal of the inedible outer hull and is commonly used in animal production [3–6]. However, the great variations in nutrient composition of brown rice have caused a significant difference between the “true value” and the “static parameters” in existing databases due to differences in sources, processing, and storage, making precision formulation difficult. Additionally, the limited studies on the amino acid (AA) digestibility of brown rice also affect the available use of brown rice in diets. Feed formulation can be formulated with precision by dynamically predicting the nutritional composition of ingredients via constructing prediction equations. Therefore, we conducted research to determine the physical and chemical composition, the apparent ileal digestibility (AID) and standardized ileal digestibility (SID) of crude protein (CP) and AA in brown rice fed to pigs and to establish predicted equations for SIDAA.
MATERIALS AND METHODS
Animal care
The animal experiment was carried out in the metabolism laboratory of the Institute of Subtropical Agriculture, Chinese Academy of Sciences (Changsha, China). All the experimental protocol was reviewed and approved by the Animal Care and Use Committee at the Institute of Subtropical Agriculture, Chinese Academy of Sciences (IACUC#201302).
Sources of brown rice samples
Ten paddy rice samples were collected from Hunan (n = 4), Anhui (n = 1), Hubei (n = 1), Guangxi (n = 1), Henan (n = 1), Jiangxi (n = 1), and Guizhou (n = 1) province and were processed into brown rice after dehulling (Table 1). All brown rice were crushed and sieved through 40-mesh screen and stored at −20°C before chemical analysis [7].
Animals, diets, and experimental design
A total of 22 pigs (Duroc×[Yorkshire×Landrace], initial body weight: 42.0±1.2 kg) were installed a simple T-cannula in their distal ileum [8]. All pigs were placed in individual metabolism cages (1.4 m×0.7 m×0.5 m) in an environmentally controlled room (23°C±1°C). Pigs were allotted to a replicated 11×3 incomplete Latin square design with 3 consecutive periods and 11 diets. Ten brown rice diets containing the selected brown rice as the sole nitrogen source and a nitrogen-free diet for determination of basal endogenous losses of CP and AA were formulated (Table 2). All diets were supplemented with 0.3% of chromic oxide (Cr2O3) as an indigestible marker. All diets were fortified with vitamins and minerals to meet or exceed the nutritional requirements recommended by the NRC [9] for 20- to 50-kg pigs. The analyzed CP and AA composition of diets is represented in Table 3.
Sample collection and preparation
Ileal digesta were collected on d 6 and d 7 for 8 h every day from 0800 to 1600 h according to the standard procedure [11]. Cannulas were opened and plastic bags were fastened with the help of a rubber band to collect the digesta flowing into the bags. The bags were replaced every 30 minutes, and the ileal digesta were promptly frozen at −20°C. During the collection, 5 mL of 10% (v/v) formic acid was added into each bag to minimize the bacterial fermentation. At the end of each period, all the digesta samples were thawed, mixed, and lyophilized in a Vacuum-Freeze Dryer (ACIENTZ-50F/A; Ningbo Xinzhi Lyophilization Equipment Co, Ltd, Ningbo, China) for 72 h and subsampled.
Sample analysis and calculation
The samples of brown rice and diets were analyzed using the procedures for bulk weight (GB 5498-85), thousand-kernel weight (GB/T 5519-88), and thousand-kernel volume (GB/T 5519-88). The AOAC [12] procedures were used to determine the contents of dry matter (DM, 930.15), CP (984.13), ether extract (EE, 920.39), crude ash (Ash, 942.05), calcium (Ca, 968.08), and total phosphorus (TP, 964.06). Total starch (TS) contents were analyzed with a commercial starch assay kit (Megazyme, Bure, Ireland). The contents of crude fiber (CF), neutral detergent fiber (NDF), and acid detergent fiber (ADF) were determined using a fiber analyzer (ANKOM A200i Fiber Analyzer; Beijing ANKOM Technology Co. Ltd, Beijing, China) in combination with fiber bags.
The samples of brown rice, diets and lyophilized ileal digesta were analyzed for the contents of DM, CP, and AA. The fifteen AA profiles were measured by the HPLC (Agilent 1200, Agilent Technologies, Santa Clara, CA, USA) after acid hydrolysis with 6 M HCl. Methionine (Met) and cysteine (Cys) were determined after oxidative hydrolysis (method 982.30 E(a); AOAC, 2006). Tryptophan (Trp) was measured after 10% of KOH hydrolysis for 16 to 18 h at 40°C using the spectrophotometric method of GB/T 15400-2018. The AID and SID of AA (%) in brown rice samples were determined using the method of Stein et al [11] described as following:
where AAd and Td represent the concentrations of AA and chromium in the ileal digesta (g/kg of DM), respectively, and AAr and Tr are the concentrations of AA and chromium in the brown rice diets (g/kg of DM), respectively. The same equation was used to calculate the AID of CP.
where IAAend is the basal endogenous loss of each AA (g/kg of DM intake) and AAd and Td represent the concentrations of AA and chromium in the ileal digesta from the growing-finishing pigs fed the N-free diet, respectively. The Tr represents the concentration of chromium in the N-free diet. The same equation was used to calculate the endogenous loss of CP.
Statistical analysis
The normality and equal variance of data were assessed using the Descriptive Statistics procedure of SPSS 17.0 (SPSS Inc, Chicago, IL, USA) and outliers were identified by analyzing the Z-scores of the data. Correlation coefficients among the physical characteristics, chemical composition, and AA digestibility (AID and SID of lysine [Lys], Met, Trp, and threonine [Thr]) of brown rice samples were examined using the CORR procedure. The stepwise regression was employed to establish the prediction equations for the SID of Lys, Met, Trp, and Thr of the brown rice samples based on its the physical characteristics and chemical composition. The best-fit equations were selected depending on relative standard deviation (RSD), R2, and p-value; p<0.05 means significant difference and p<0.01 means extremely significant difference, when R2 is closer to 1 and p-value represent a significant difference, the equation is considered more accurate.
RESULTS
Physical characteristics, chemical composition, and AA profile of brown rice
On air-dry basis, the coefficient of variation (CV) of CP, EE, Ash, CF, NDF, ADF, Ca, TP, TS, thousand-kernel weight and thousand-kernel volume were greater than 10%, and the CV of EE, Ca, CF, NDF, and ADF were greater than 30%. The content of CP, EE, Ca, TP, CF, NDF, ADF, TS, thousand-kernel weight and thousand-kernel volume in 10 brown rices averaged 6.73% (5.34% to 8.39%), 1.97% (1.10% to 2.77%), 0.02% (0.01% to 0.03%), 0.17% (0.14% to 0.20%), 0.92% (0.20% to 1.53%), 5.04% (2.17% to 9.58%), 1.61% (0.74% to 2.49%), 69.08% (56.76% to 77.94%), 20.53 g/kg kernel (14.59 to 25.82 g/kg kernel) and 25.22 mL/1,000 grain (19.90 to 32.00 mL/1,000 grain), respectively (Table 4). The CV of all AA contents exceeded 10%. The concentrations of Lys, Met, Thr, and Trp in 10 brown rice samples were 0.34% (0.25% to 0.49%), 0.14% (0.07% to 0.26%), 0.24% (0.19% to 0.30%), and 0.07% (0.06% to 0.10%), respectively.
AID and SID of CP and AA
As shown in Table 5, the AIDCP wa6-181s 37.8% (20.0% to 54.6%). The AIDLys, AIDMet, AIDThr, and AIDTrp were 63.7% (49.7% to 73.9%), 73.9% (57.0% to 87.0%), 36.1% (25.4% to 47.0%), and 76.2% (68.6% to 81.3%), respectively. The SID of CP and AA of 10 brown rices were shown in Table 6. The SIDCP was 77.2% (62.6% to 85.5%), and the SID of Lys, Met, Thr, and Trp ranged from 80.3% to 94.3% (87.5%), 78.9% to 98.9% (89.2%), 46.1% to 67.6% (55.4%), and 86.3% to 96.3% (92.5%), respectively.
Correlation analysis and prediction equations for SID of CP and AA
The correlation among physical characteristics, chemical composition, and the SID of the first four limiting AA of brown rice is presented in Table 7. The SID of Thr was positively related to EE (p<0.05). As shown in Table 8, the best fit equations for SIDCP, SIDLys, SIDThr, and SIDTrp as following, SIDCP = −664.181+8.484×DM (R2 = 0.40; RSD = 6.46; p = 0.05), SIDLys = 53.126+6.031×EE+0.893×thousand-kernel volume (R2 = 0.66; RSD = 3.43; p<0.05), SIDThr = 39.916+ 7.843×EE (R2 = 0.41; RSD = 5.99; p<0.05) and SIDTrp = −361.588+4.891×DM+0.387×TS (R2 = 0.85; RSD = 1.66; p<0.01).
DISCUSSION
Physical characteristics, chemical composition, and AA profile of brown rice
Great variation in chemical composition and physical property was observed among 10 brown rice samples. The CV value for CP, Ash, TP, TS, 1,000 kernel weight and 1,000 kernel volume exceeded 10%, and EE, Ca, CF, NDF and ADF even surpassed 30%. The detected contents of gross energy (GE), DM, EE, Ca, and TS were within the range of the tabulated value [13,14], and most chemical compositions and physical properties were close to the values in previous literature [15–19], indicating that our results were credible. However, bulk weight, 1,000 kernel weight and 1,000 kernel volume were not provided in tabulated value, the CP, Ash, and TP concentrations were lower than the tabulated value, and the content of CF, NDF, and ADF were higher than the tabulated value, which may be attributed to the incomplete shelling of paddy rice to obtain brown rice. This phenomenon was confirmed by the findings that a large number of hulls were not completely removed due to the inefficiency of sheller and the analyzed fiber (CF, NDF, and ADF) contents were relatively high in our study. The separation of different parts of grains during the milling process, might influence the physical and chemical properties of rice by-products [20]. Chen [21] pointed out that the quality of paddy rice is mainly related to varieties, starch content, storage, and environment. The nutrients of brown rice in this study are inconsistent with published data, which may be due to differences in paddy rice cultivation regions, periods, and environments. In addition, the variation of brown rice might result from processing and storage technology and different growth conditions, such as climate and soil conditions [22,23].
The AA and protein contents of brown rice varied greatly. The 10 brown rice samples were from different regions with multiple natural conditions in China, which provided an explanation for the deviation from uniformity. The analyzed CP and AA values in our study were close to the reported values in the database [16,24,25]. Lysine, Met, Thr, and Trp are the main limiting AAs in livestock and poultry, and play an irreplaceable role in pig growth [26]. He et al [27] analyzed and compared the AA content of 18 varieties of brown rice samples and found that the first, second and third limiting AA were Lys, Thr, and Ile when brown rice used in corn-brown rice-SBM fed to pigs. In our study, the content of Lys, Thr, and Ile in brown rice were similar to tabulated value [13,14].
SID of AA in brown rice
Diversified low-protein diets for swine production have been fully pushing ahead in China [28]. Accuracy estimation of AA availability in diets or feedstuffs is the basis for the comprehensive implementation of low-protein diets system. Standardized ileal digestibility of AA is recognized as the gold method for estimation of AA availability [11]. Lysine, Met, Thr, and Trp are the main limiting AA in poultry. In the study, the mean SID values of the Lys, Met, and Trp in brown rice samples were greater than those in the Nutrient Requirements of Swine in China [11]. Meanwhile, the analyzed SID of the Lys, Met, and Trp contents fell within the range of the reports by Li [24], Wu et al [25], and Zhang et al [29].
Correlation analysis and prediction equations for SID of AA in brown rice
The SID was calculated by correcting AID for the ileal basal endogenous losses and dietary composition, especially dietary protein, and fiber, is responsible for ileal basal endogenous CP and AA losses [30,31]. In the current study, the SIDThr was positively correlated with EE. The increase in dietary fat delayed gastric emptying [32], and the slower gastric emptying may result in slower rate of passage of the diet, causing an increase in the time of exposure of feed to proteolytic enzymes, thus providing longer time for peptides and AA to be digested and absorbed, and increase in AID of AA [33,34]. The addition of oil to diets fed to growing pigs increased not only the AID but also the SID of AA [35,36]. Imbeah and Sauer [37] concluded that the level of fat may affect ileal AA digestibility. Additionally, positive correlation trends between SIDLys or SIDThr and EE, and SIDTrp with DM and TS were observed. The release rate of glucose during the digestion process of feed starch from different sources varies, and the synchronization degree of glucose and AA supply varies. Therefore, the AA absorption of feed starch from different sources are also different [38]. The digestibility of starch also directly affects the absorption of AA in the intestine [38]. Also, we obtained that DM and GE are closely related in brown rice, and with the raise of DM, the GE and TP will also increase, and then affect the SID of AA [39]. Unfortunately, there is no literature specifically explaining the interaction between DM and SIDAA, nor the mechanism by which DM has a negative impact on CP and AA digestibility, which may be one of the questions that we need to explore in our subsequent experiments. Our findings suggest that EE, DM, and TS might be key predictors for SID of Lys, Met, Thr, and Trp.
The research on a prediction model of AA digestibility in brown rice for pigs is limited. Nutritional Requirements of Chinese Pigs [13] reported that CP was the key predictors to estimate the SID of the first four limiting AA in brown rice. Yu et al [40] found that there is no correlation between biomimetic digestion and biological measurements of Thr, histidine, arginine, and Cys. However, Liu et al [41] established a prediction equation for SIDLys, SIDMet, and SIDThr in sunflower seeds, showed a positive correlation between SIDLys and Met, and a negative correlation between SIDLys and Trp, the SIDMet was negatively correlated with EE and positively with Ca and Met, the SIDThr was positive with Met. Yun et al [42] established a prediction equation for SIDLys and SIDMet in wheat, showing a positive correlation between SIDLys, SIDMet, and NDF. In the present study, we selected 10 brown rice to do a similar study and got one prediction equation for SIDCP, two equations for SIDLys, one equation for SIDThr and two equations for SIDTrp, respectively. Meanwhile, the key predictors for the SID of CP and AA are DM, EE, 1,000-kernel volume, and TS. Until now, the prediction equations of SID of AA are not as applicable as the available energy in practice due to the complex factors, mainly including accurate assessment of endogenous nitrogen losses and determination of AA, and more effort and work are required for the future.
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