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Learn more: PMC Disclaimer | PMC Copyright Notice Poult Sci . 2026 Apr 2;105(7):106897. doi: 10.1016/j.psj.2026.106897 Search in PMC Search in PubMed View in NLM Catalog Add to search Exploring the effects of dietary starch digestion kinetics on net energy utilization in peak laying hens Haoran Zhu Haoran Zhu 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Haoran Zhu 1 , Minghui Fu Minghui Fu 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Minghui Fu 1 , Haixia Ding Haixia Ding 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Haixia Ding 1 , Jianxin Liang Jianxin Liang 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Jianxin Liang 1 , Xutong Chen Xutong Chen 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Xutong Chen 1 , Guixin Qin Guixin Qin 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Guixin Qin 1 , Li Pan Li Pan 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Li Pan 1 , Nan Bao Nan Bao 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Nan Bao 1, ⁎ , Yuan Zhao Yuan Zhao 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China Find articles by Yuan Zhao 1 Author information Article notes Copyright and License information 1 Key Laboratory of Animal Production, Product Quality and Security, Ministry of Education, Jilin Provincial Key Laboratory of Animal Nutrition and Feed Science, College of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China ⁎ Corresponding author. [email protected] Received 2025 Dec 27; Accepted 2026 Apr 1; Collection date 2026 Jul. © 2026 Published by Elsevier Inc. on behalf of Poultry Science Association Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). PMC Copyright notice PMCID: PMC13091746 PMID: 41965142 Abstract Feed energy constitutes a major cost factor in laying hen production, yet current net energy ( NE ) evaluation ignores the impact of starch digestion kinetics. This study evaluated the effects of different starch digestion kinetics on productive performance and energy utilization in peak laying hens. A total of 360 Hy-Line Brown hens (35 weeks of age) were randomly assigned to four diets: rapid ( RAP ), medium ( MED ), slow ( SLO ) and resistant starch diet ( RES ). Productive performance was measured for 35 d in 280 hens, and respiratory calorimetry was conducted for 5 d in 48 hens selected from an additional group of 80 hens. The results indicated that the RAP diet showed the highest in vitro starch digestion rate constant k ( P < 0.05), with more pronounced postprandial glucose and insulin fluctuations. In terms of laying performance, hens fed the MED diet had higher hen-day egg production ( HDEP ) than in the RAP diet ( P < 0.05). Compared with the RAP diet, the MED, SLO and RES diets increased total retained nitrogen ( TRN ), and the SLO and RES diets further increased total retained nitrogen rate ( TRNR) ( P < 0.05). No differences were observed in the heat increment ( HI ) to dietary gross energy ( GE ) ratio or the NE:GE ratio among the MED, SLO, and RES diets ( P > 0.05), whereas the RAP diet showed the highest HI:GE ratio and the lowest NE:GE ratio ( P < 0.05). Quadratic regression revealed a significant relationship between the starch digestion rate constant k and the HI:GE ratio ( P = 0.030). Overall, an optimal range of glucose release rates may improve NE utilization in peak laying hens, supporting the potential value of incorporating starch digestion kinetics in NE evaluation. Keywords: Laying hen, Starch digestion kinetics, Net energy, Energy utilization Introduction In poultry feed evaluation, adopting a net energy ( NE ) system is necessary ( Noblet et al., 2024 ; Pesti and Choct, 2023 ). Compared with the apparent metabolizable energy ( AME ) system, NE subtracts the heat increment ( HI ) associated with digestion and metabolism, and thus more accurately reflects the utilizable energy of feeds ( Barzegar, et al., 2020 ). Starch-based ingredients contribute 50 to 70 % of dietary energy in laying hens, making energy utilization efficiency a key determinant of poultry production. Starch is composed of amylose ( AM ) and amylopectin ( AP ), whose structural differences can substantially alter the pathway and rate of enzymatic hydrolysis ( Martens, et al., 2018 ). Processing such as extrusion and gelatinization can also modify starch granule crystallinity and enzyme susceptibility ( Ye, et al., 2018 ; Zhang, et al., 2019 ; Zhao, et al., 2024 ), and these structural and processing-related factors together influence starch digestion kinetics. Englyst and Hudson (1996) classified starch into rapidly digestible starch ( RDS ), slowly digestible starch ( SDS ), and resistant starch ( RS ) using predefined in vitro digestion time points, providing a simple description of glucose release characteristics. By contrast, Goñi, et al. (1997) recorded the full in vitro hydrolysis time course and fitted the data using a nonlinear first-order kinetic model to estimate parameters including the rate constant k . High AP or extruded starch typically contains more RDS, whereas high AM starch, intact starch granules, or starch with a C-type granule structure shows a sustained-release digestion profile with a lower digestion rate constant k ( Bertoft, 2017 ; Giuberti, et al., 2012 ; Sharma, et al., 2021 ). In pigs, altering the glucose release kinetics of cereal grains changed the pattern of nutrient oxidation and energy utilization ( Zhu, et al., 2023 ), thereby providing direct evidence that digestive timing affected metabolic efficiency. Moreover, the kinetic pattern of glucose release modified nitrogen utilization, the portal venous amino acid profile, and transport-related expression in the intestinal epithelium, indicating that the synchrony between glucose and amino acid supply was regulated by digestion kinetics ( Li, et al., 2024a ; Selle and Liu, 2019 ). Luo et al. (2025c) also emphasized that overly slow starch digestion reduces protein synthesis efficiency in broilers. A previous study reported that peas with relatively high levels of slowly digestible starch increased dietary AME and NE in broilers ( Sharma, et al., 2021 ). Differences in starch digestion rate in feed formulation may cause a mismatch between glucose supply and metabolic demand, thereby affecting energy utilization efficiency ( Luo, et al., 2025a ). In laying hens, modifying starch digestion rate and extent likewise affected laying performance and feed conversion ratio ( FCR ) ( Herwig, et al., 2019a ), and egg formation follows a diurnal rhythm, with the relative demand for energy and nutrients shifting across the day ( Jahan, et al., 2024 ). In contrast, broilers have been intensively selected for rapid growth and improved feed efficiency ( Zuidhof, et al., 2014 ), while laying hens must coordinate nutrient utilization with the cyclic demands of egg formation. Therefore, understanding how energy metabolism responds to starch digestion rate is particularly important for improving NE utilization efficiency in laying hens. The temporal effects of starch digestion rate on energy supply have not been incorporated into energy evaluation systems, which has overlooked the concept of dynamic nutrition. Numerous studies have been conducted on the effects of starch digestion rate on energy metabolism in broilers ( Luo, et al., 2025c ; Ma, et al., 2020 ; Sharma, et al., 2021 ). However, energy metabolic responses to starch digestion kinetics remain understudied in laying hens, limiting improvements in precision nutrition formulation. Therefore, this study used four diets differing in starch digestion rate and systematically evaluated the effects of glucose release rate on energy utilization efficiency in peak laying hens via in vitro starch digestion, productive performance, blood metabolic indices, nitrogen metabolism, and respiration calorimetry. We hypothesized that an appropriate range of glucose release rates could maximize NE utilization efficiency while maintaining laying performance. Materials and methods Animal ethics All animal care and use procedures were reviewed and approved by the Experimental Animal Ethics Committee of the College of Animal Science and Technology, Jilin Agricultural University (Approval Number: 20230105005). Diets Following the nutritional standards for laying hens during the egg laying period of China (ZB B 43005-86), four diets were formulated to provide equal levels of energy, crude protein (CP), and total starch (TS) but to differ in glucose release rate, being designated as rapid (RAP), medium (MED), slow (SLO), and resistant starch diet (RES). All diets were processed by cold pelleting and crumbling, and their nutrient compositions are shown in Table 1 . Table 1. Ingredient composition and nutrient levels of the diets (as-fed basis, %). Items RAP MED SLO RES Ground corn 28.81 44.58 61.91 34.78 Extruded corn 29.87 14.46 0.00 12.32 Pea 3.24 3.71 0.00 22.96 Soybean meal 16.96 16.68 17.73 8.33 Corn gluten meal 5.04 5.27 5.72 5.99 Soybean oil 1.21 1.31 1.33 1.66 Salt 0.41 0.41 0.41 0.41 Limestone (20 mesh) 11.47 10.59 9.97 10.39 CaHPO 4 1.55 1.55 1.55 1.56 DL-methionine 0.26 0.26 0.24 0.30 L-lysine 0.26 0.26 0.28 0.22 L-tryptophan 0.05 0.05 0.05 0.07 L-threonine 0.08 0.08 0.07 0.10 L-isoleucine 0.06 0.06 0.04 0.08 L-valine 0.06 0.06 0.04 0.10 Choline chloride (60 %) 0.18 0.18 0.18 0.22 Premix¹ 0.50 0.50 0.50 0.50 Total 100.00 100.00 100.00 100.00 Calculated nutrients CP 16.50 16.50 16.50 16.50 AME, kcal/kg 2781 2781 2781 2781 TS 41.20 41.20 41.22 41.20 Calcium 4.54 4.22 4.00 4.15 Available phosphorus 0.39 0.39 0.39 0.39 Open in a new tab 1 Premix (supplied per kg ration): VA 6600 IU, VD3 3 500 IU, VE 6 mg, VK 3 3.3 mg, VB 1 0.96 mg, VB 2 33.18 mg, VB 6 1.8 mg, VB 12 0.006 mg, Biotin 0.03 mg, Calcium pantothenate 5.4 mg, Niacin 30 mg, Folic acid 0.48 mg, Fe 45 mg, Cu 6 mg, Mn 76 mg, Zn 72 mg, I2 0.5 mg, Se 0.3 mg RAP = rapidly digestible starch diet; MED = medium starch digestion rate diet; SLO = slowly digestible starch diet; RES = resistant starch diet; CP = crude protein, AME = apparent metabolizable energy, TS = total starch. In vitro starch digestion and calculations The in vitro starch digestion procedure was referred to previous studies ( Ebsim, 2013 ; Karunaratne, et al., 2018 ). Three independently prepared batches of experimental diets from the same feed ingredients were used for the assay. Feed samples were ground and subjected to a two-step in vitro digestion simulating the gastric and small intestinal phases at 41°C. In the gastric phase, porcine pepsin (P-7000; Sigma-Aldrich) was used for 30 min of digestion. The pH was then adjusted to 5.6 with sodium acetate buffer, followed by the addition of a mixed enzyme solution containing pancreatin (P-7545; Sigma-Aldrich), α-amylase (A-7095; Sigma-Aldrich), and invertase (I-4504; Sigma-Aldrich) to simulate small intestinal digestion (defined as 0 min). The mixture was incubated in a shaking water bath for 240 min, and supernatants were collected at eight time points (15, 30, 45, 60, 90, 120, 180, and 240 min). Glucose levels in supernatants were determined using a glucose oxidase kit (Megazyme Inc., Chicago, IL, USA). The TS content was measured using the Megazyme Total Starch Kit (Megazyme Inc., Ireland). The starch digestion coefficient at each time interval ( D C t ) was calculated as follows ( Giuberti, et al., 2012 ): D C t = G t ( mg ) TS ( mg ) × 0 . 9 where G t is the glucose content at every hydrolysis time; TS is the total starch content of the sample; 0.9 is the conversion coefficient between starch and glucose ( Stevnebø, et al., 2006 ). The starch digestion kinetics were described using a first-order kinetic equation according to the method of Goñi, et al. (1997) . The equation was expressed as: C t = C ∞ ( 1 − e − kt ) where C t is the amount of starch digested at time t, C ∞ is the potential digestible fraction of starch, k is the digestion rate constant (min⁻¹), and t is the incubation time (min). The parameters C ∞ and k were estimated by nonlinear regression using OriginPro 2022 software (OriginLab Corp., USA). The starch digestion coefficient at 20 min ( C 20 ) and 120 min ( C 120 ) were calculated from the fitted kinetic equation, and then converted to the levels of RDS, SDS, and RS according to the equation proposed by Englyst, et al. (2018) , as follows: RDS ( % ) = ( C 20 − C 0 ) × 100 SDS ( % ) = ( C 120 − C 20 ) × 100 RS ( % ) = 100 − RDS ( % ) − SDS ( % ) where C 0 , C 20 , and C 120 are the starch digestion coefficients at 0, 20, and 120 min, respectively, and C 0 was set to 0. Bird production management A total of 280 healthy Hy-Line Brown laying hens (35 weeks of age, with similar body weight) were randomly assigned to four dietary treatments. Hens were housed two per cage. Within each treatment, five cages (10 hens) were considered one replicate, giving seven replicates per treatment (70 hens per treatment). The experiment consisted of a 10-day adaptation period followed by a 35-day experimental period. At 16:00 each day, the number of birds present, the number of eggs produced, and the total egg weight were recorded. After the experiment, feed intake ( FI ), hen-day egg production ( HDEP ), egg mass ( EM ), and FCR were calculated using the following equations: FI ( g / d ) = Total feed intake ( g ) Total hen − days HDEP ( % ) = ( Total number of eggs produced Total hen − days ) × 100 EM ( g / d ) = Total eggs weight ( g ) Total hen − days FCR = Total feed intake ( g ) Total egg mass ( g ) Respiratory chamber and management The design principle of the open-circuit respiration chamber was similar to that described by Van Milgen, et al. (1997) , and the equipment parameters were reported in a previous study ( Liu, et al., 2020 ). In brief, twelve open-circuit respiration chambers were operated in parallel, each with a volume of 0.43 m³. Temperature and relative humidity in the chambers were maintained by an air-conditioning system, and gas was continuously extracted by a vacuum pump. Oxygen ( O 2 ) was measured with a zirconium-oxide sensor (Model 65-4-20; Advanced Micro Instruments, Huntington Beach, CA, USA), and carbon dioxide ( CO 2 ) was measured with a nondispersive infrared sensor (AGM 10; Sensors Europe GmbH, Erkrath, Germany). The analyzer measurement ranges were 0 – 25 % for O 2 and 0 – 2.5 % for CO 2 . Prior to the experiment, all respiration chambers were cleaned, disinfected, and calibrated. Eighty healthy Hy-Line Brown laying hens, aged 35 weeks and of similar body weight, were from the same flock as those used in the production performance trial and were reared under the same environmental and management conditions, and randomly assigned to four treatments to evaluate four diets. After 15 days of pre-feeding, 12 hens with similar body weights were selected from each treatment and placed into six respiration chambers, with two hens per chamber ( n = 6 chambers per treatment). The room temperature was maintained at 22 ± 1°C with a relative humidity of 50 ± 10 % and a light intensity of 20 lux. Birds had free access to feed and water under a 16 h light schedule (6:00 to 22:00). The calorimetric phase lasted for 5 days, including 2 days of adaptation and 3 days of data collection. During the collection phase, initial and final body weight ( BW ), egg number, egg weight, FI, O 2 consumption, and CO 2 production were recorded. Excreta from the 3-day collection period were collected using the total excreta collection method. For every 100 g of excreta, 10 mL of 10 % sulfuric acid solution was sprayed to fix nitrogen, and samples were stored at −20°C. After the experiment, excreta were dried at 65°C for 72 h, kept at room temperature for 24 h, then ground and stored at 4°C. For each diet, about 500 g feed sample was randomly selected, ground, and stored at 4°C. Nitrogen balance experiment Nitrogen levels in feed and excreta samples ( N intake and N excreta ) were measured using a Kjeldahl nitrogen analyser (Kjeltec 8420, FOSS Analytical Co., Beijing, China). The main calculation formulae were as follows: Total retained nitrogen ( TRN , g / d ) = N intake ( g / d ) − N excreta ( g / d ) Egg nitrogen retention ( RN egg , g / d ) = EM ( g / d ) × 1.936 % where the nitrogen content of eggs was 1.936 % ( Miranda, et al., 2015 ), Body nitrogen retention ( RN body , g / d ) = TRN ( g / d ) − RNegg ( g / d ) Total nitrogen retention rate ( TRNR , % ) = [ N intake ( g / d ) − N excreta ( g / d ) N intake ( g / d ) ] × 100 Energy metabolism experiment The dry matter (DM) contents of diets and excreta samples were determined at 105°C, while GE of diets and excreta energy ( E excreta ) were measured using an oxygen bomb calorimeter (C 3000, IKA, Germany). The respiratory quotient ( RQ ) represents the ratio of CO 2 produced to O 2 consumed during metabolism. Heat production intake ( HP intake ) was calculated using the Brouwer equation ( Brouwer, 1965 ), without correction for methane and nitrogen. The equation used was: HP intake ( kcal / d ) = 3.866 × VO 2 ( L / d ) + 1.200 × VC O 2 ( L / d ) where VO 2 and VCO 2 are volumes of O 2 and CO 2 , respectively. Fasting heat production ( FHP ) was adopted from Wu, et al. (2016) and set at 88 kcal/kg BW 0.75 . Heat increment intake ( HI intake ) was calculated as the difference between HP intake and FHP. Other energy allocation equations were as follows: Gross energy intake ( GE intake , kcal / d ) = GE ( kcal / g ) × FI ( g / d ) Gross energy in excreta ( GE excreta , kcal / d ) = E excreta ( kcal / g ) × Excreta output ( g / d ) Apparent metabolizable energy intake ( AME intake , kcal / d ) = GE intake ( kcal / d ) − GE excreta ( kcal / d ) Net energy intake ( NE intake , kcal / d ) = AME intake ( kcal / d ) − HI intake ( kcal / d ) Retained energy ( RE , kcal / d ) = AME intake ( kcal / d ) − HP intake ( kcal / d ) Energy retained as protein ( RE prot , kcal / d ) = TRN ( g / d ) × 6.25 × 5.7 where 6.25 is the nitrogen-to-protein conversion factor, and 5.7 is the energy coefficient for protein deposition ( Chwalibog, et al., 2005 ), Energy retained as fat ( RE fat , kcal / d ) = RE ( kcal / d ) − RE prot ( kcal / d ) Energy retained as egg ( RE egg , kcal / d ) = − 19.7 + 1.810 × EM ( g / d ) ( Sibbald, 1979 ), Energy retained as body ( RE body , kcal / d ) = RE ( kcal / d ) − RE egg ( kcal / d ) To assess energy value, AME and nitrogen-corrected apparent metabolizable energy ( AMEn ) were calculated as follows: AME ( kcal / kg DM ) = AME intake ( kcal / d ) FI ( kg / d DM ) AMEn ( kcal / kg DM ) = AME ( kcal / kg DM ) − [ TRN ( g / d ) FI ( kg / d DM ) ] × 8 . 22 where 8.22 is the empirical correction factor derived from the heat of combustion of uric acid ( Hill and Anderson, 1958 ). NE, heat production ( HP ), and heat increment ( HI ) were respectively calculated by dividing NE intake , HP intake , and HI intake by FI. Blood analysis At the end of the production performance experiment, blood samples were collected from brachial (wing) vein, with one hen per replicate randomly selected within each diet. After a 12 h fasting period, a fasting blood sample was collected (designated 0 min). Birds were then permitted to feed freely, and blood samples were taken at 30, 60, 90 and 120 min after feeding. Blood was collected into potassium oxalate-sodium fluoride tubes and serum separator tubes. Samples were immediately centrifuged in a refrigerated centrifuge at 4°C at 3,000 rpm for 10 min. The separated plasma and serum were stored at − 80°C. An automated biochemical analyser (BS-400, Mindray Biomedical Electronics Co., Shenzhen, China) was used to determine plasma glucose at each sampling time and fasting serum uric acid and blood urea nitrogen. The serum insulin at each time point and fasting serum luteinizing hormone ( LH ), estradiol ( E2 ), prolactin ( PRL ), follicle stimulating hormone ( FSH ) and progesterone ( P4 ) were measured using ELISA kits from Shanghai Enzyme-linked Biotechnology Co., Ltd (Shanghai, China). Data analysis Data were analyzed by one-way analysis of variance ( ANOVA ) using SPSS 20.0 software (IBM, Inc., Armonk, NY, USA) after testing for normality and homogeneity of variance. For production performance, the replicate (10 hens) was the experimental unit. For blood measurements, one bird randomly selected from each replicate was used for statistical analysis. For calorimetry and nitrogen balance, the respiration chamber (two hens) was the experimental unit. When a significant treatment effect was detected, group means were compared using Tukey’s multiple comparison test. Data are presented as means with standard error of the mean ( SEM ), whereas data in figures are shown as mean and standard deviation ( SD ). Differences were considered significant at P < 0.05. Regression equations were fitted to describe the relationships between starch digestion kinetics and energy utilization efficiency. Results Starch digestion kinetics As shown in Fig. 1 , different diets showed distinct starch digestion kinetics. In short, the RAP diet exhibited the fastest hydrolysis, the MED diet was intermediate, and the SLO and RES diets were slower, especially during the early and middle phases of digestion. Specifically, from 15 to 90 min, the RAP diet remained the highest, the MED diet was intermediate, and the SLO and RES diets were lower and did not differ from each other ( P < 0.05). As digestion progressed, the differences among the RAP, MED, and SLO diets became smaller at 120 and 180 min, whereas the RES diet remained the lowest ( P < 0.05). By 240 min, the RAP and MED diet did not differ, the SLO diet was intermediate, and the RES diet remained lower than the RAP and MED diet ( P < 0.05). Table 2 further showed that the RAP diet had the highest RDS and C ∞ values, the SLO diet had the highest SDS value, and the RES diet had the highest RS value together with the lowest C ∞ value ( P < 0.001). For the kinetic constant k , the values decreased in the order of RAP, MED, RES, and SLO ( P < 0.001). Fig. 1. Open in a new tab In vitro starch digestion coefficients of the diets. Different letters at the same time point indicate significant differences ( P < 0.05). RAP = rapidly digestible starch diet; MED = medium starch digestion rate diet; SLO = slowly digestible starch diet; RES = resistant starch diet. Table 2. Ratio of RDS, SDS and RS (%) and digestive kinetic constants. Items RAP MED SLO RES SEM P -value RDS, % 63.4 a 52.9 b 41.5 c 43.4 c 2.63 < 0.001 SDS, % 28.3 d 36.4 c 45.5 a 40.4 b 1.91 < 0.001 RS, % 8.4 d 10.7 c 13.0 b 16.1 a 0.88 < 0.001 k , min −1 0.0587 a 0.0446 b 0.0314 d 0.0357 c 0.003 < 0.001 C ∞ , % 91.7 a 89.7 b 89.1 b 85.1 c 0.74 < 0.001 Open in a new tab Means with different superscripts in a row indicate significant differences ( P < 0.05), number of replications = 3. RAP = rapidly digestible starch diet; MED = medium starch digestion rate diet; SLO = slowly digestible starch diet; RES = resistant starch diet; RDS = rapidly digestible starch; SDS = slowly digestible starch; RS = resistant starch; k = starch digestion rate constant; C ∞ = asymptotic extent of starch digestion; SEM = standard error of the mean. Production performance Production performance of laying hens is shown in Table 3 . The BWG was higher in the RAP and SLO diets than in the MED diet, and the highest BWG occurred in the RES diet ( P < 0.05). The HDEP and EM did not differ among the MED, SLO, and RES diets ( P > 0.05), but both were higher in the MED diet than in the RAP diet ( P < 0.05) whereas differences between the RAP and SLO or RES diets were not significant ( P > 0.05). Moreover, the FCR among all diets showed no significant difference ( P > 0.05). Table 3. Effects of starch digestion kinetics on productive performance of laying hens (as-fed basis). Items RAP MED SLO RES SEM P -value FI prod , g/d 124 129 127 128 0.85 0.235 Initial BW prod , kg 2.00 1.98 1.98 1.99 0.01 0.916 Final BW prod , kg 2.13 ab 2.06 b 2.10 ab 2.16 a 0.01 0.044 BWG, g 124 b 82 c 119 b 164 a 6.83 < 0.001 HDEP, % 84.5 b 91.3 a 88.1 ab 87.0 ab 0.88 0.042 EM, g/d 55.2 b 59.6 a 57.5 ab 57.3 ab 0.55 0.045 FCR 2.25 2.17 2.22 2.28 0.05 0.227 Open in a new tab Means with different superscripts in a row indicate significant differences ( P < 0.05), number of replications = 7. FI prod = feed intake in production, BW prod = body weight in production, BWG = body weight gain, HDEP = hen-day egg production, EM = egg mass, FCR = feed conversion ratio per egg mass; SEM = standard error of the mean. Nitrogen balance Table 4 summarizes the effects of the diets on nitrogen metabolism. N intake was higher in the MED diet than in the RAP diet ( P < 0.05) and was similar to the SLO and RES diets ( P > 0.05). N excreta in the MED diet was higher than in the SLO and RES diets ( P < 0.05). TRN in the RAP diet was lower than in the other diets ( P < 0.05). In terms of retained nitrogen partitioning, RN egg did not differ among diets ( P > 0.05), whereas RN body in the RES diet was higher than in the RAP diet ( P < 0.05) and represented the highest value among treatments. TRNR differed among diets ( P = 0.001). The RES diet showed higher TRNR than the MED and RAP diets ( P < 0.05), and the SLO diet showed higher TRNR than the RAP diet ( P < 0.05), whereas no differences were noted between the RES and SLO diets or between the MED and RAP diets ( P > 0.05). Mean values were 46.8 %, 45.1 %, 41.7 % and 39.8 % for the RES, SLO, MED and RAP diets, respectively. Table 4. Effects of starch digestion kinetics on nitrogen balance of laying hens. Items RAP MED SLO RES SEM P -value Initial BW res , kg 2.010 2.041 2.002 2.003 0.01 0.492 Final BW res , kg 2.011 2.038 2.005 2.013 0.01 0.709 FI res , g/d (as-fed) 117 126 117 123 1.77 0.232 Nitrogen balance, g/d N intake 3.15 b 3.58 a 3.32 ab 3.34 ab 0.05 0.037 N excreta 1.90 ab 2.09 a 1.82 b 1.78 b 0.04 0.016 TRN 1.25 b 1.50 a 1.50 a 1.56 a 0.04 0.004 RN egg 1.05 1.15 1.11 1.12 0.02 0.565 RN body 0.21 b 0.35 ab 0.39 ab 0.45 a 0.03 0.040 TRNR, % 39.8 c 41.7 bc 45.1 ab 46.8 a 0.78 0.001 Open in a new tab Means with different superscripts in a row indicate significant differences ( P < 0.05), number of replications = 6. BW res = body weight in respiration experiment, FI res = feed intake in respiration experiment, N intake = nitrogen intake, N excreta = nitrogen excreta, TRN = total retained nitrogen, RN egg = egg nitrogen retention, RN body = body nitrogen retention, TRNR = total nitrogen retention rate; SEM = standard error of the mean. Energy metabolism Table 5 demonstrates the effects of starch digestion kinetics on energy metabolism and utilization. RQ differed significantly between diets ( P = 0.012), with the RES diet showing the highest value and the RAP diet the lowest. In energy balance, while GE intake showed no significant difference ( P = 0.066), GE excreta differed significantly ( P = 0.001), with the MED diet exhibiting the highest value. AME intake varied significantly between treatments ( P = 0.038), being higher in the RES diet than in the RAP diet. HP intake and HI intake were higher in the RAP diet than in the other diets ( P = 0.005). The RES diet showed significantly higher NE intake and RE than the RAP diet ( P < 0.001). In terms of RE, RE egg was not affected by diet ( P = 0.589). RE body , RE prot and RE fat were all higher in the RES diet than in the RAP diet ( P < 0.05). Most indicators for the MED and SLO diets were at intermediate levels with no significant differences ( P > 0.05). Table 5. Effects of starch digestion kinetics on energy metabolism and utilization efficiency of laying hens. Items RAP MED SLO RES SEM P -value RQ 0.97 b 0.99 ab 0.98 b 1.00 a 0.003 0.012 Energy balance, kcal/kg BW 0.75 per d GE intake 273 298 275 295 4.22 0.066 GE excreta 53.3 b 61.8 a 50.8 b 50.2 b 1.30 0.001 AME intake 220 b 236 ab 224 ab 245 a 3.47 0.038 HP intake 151 a 135 b 137 b 135 b 2.00 0.005 HI intake 62.2 a 46.6 b 48.5 b 46.6 b 2.00 0.005 NE intake 158 c 189 ab 176 bc 198 a 4.07 < 0.001 RE 69.3 c 101 ab 87.6 bc 110 a 1.27 < 0.001 RE egg 46.9 51.6 50.6 50.8 3.58 0.589 RE body 22.4 c 49.3 ab 37.0 bc 58.8 a 0.76 < 0.001 RE prot 26.5 b 31.2 a 31.7 a 33.0 a 3.50 0.005 RE fat 42.8 c 69.7 ab 55.9 bc 76.5 a 4.22 < 0.001 Energy values, kcal/kg DM AME 3482 c 3585 b 3579 b 3711 a 18.44 < 0.001 AMEn 3471 c 3573 b 3567 b 3698 a 18.26 < 0.001 NE 2179 c 2500 ab 2474 b 2656 a 40.95 < 0.001 HP 2386 a 2053 b 2189 ab 2059 b 38.69 0.001 HI 984 a 709 b 767 b 712 b 31.16 0.001 Energy utilization, % NE:AME 62.6 b 69.8 a 69.1 a 71.6 a 0.90 < 0.001 NE:AMEn 62.8 b 70.0 a 69.4 a 71.9 a 0.91 < 0.001 AME:GE 88.6 b 88.6 b 90.1 ab 91.4 a 0.31 < 0.001 NE:GE 55.5 b 61.8 a 62.2 a 65.5 a 0.90 < 0.001 HP:GE 60.7 a 50.7 b 55.1 b 50.7 b 1.08 < 0.001 HI:GE 25.1 a 17.5 b 19.3 b 17.5 b 0.82 < 0.001 Open in a new tab Means with different superscripts in a row indicate significant differences ( P < 0.05), number of replications = 6. RAP = rapidly digestible starch diet; MED = medium starch digestion rate diet; SLO = slowly digestible starch diet; RES = resistant starch diet. RQ = respiratory quotient; GE intake = gross energy intake; GE excreta = gross energy in excreta; AME intake = apparent metabolizable energy intake; HP intake = heat production intake; HI intake = heat increment intake; NE intake = net energy intake; RE = retained energy; RE egg = energy retained as egg; RE body = energy retained as body; RE prot = energy retained as protein; RE fat = energy retained as fat; AME = apparent metabolizable energy; AMEn = nitrogen-corrected apparent metabolizable energy; NE = net energy; HP = heat production; HI = heat increment; GE = gross energy; SEM = standard error of the mean. For energy values, AME and AMEn were higher in the RES diet than in the MED, SLO and RAP diets ( P < 0.001), whereas NE was lowest in the RAP diet, highest in the RES diet ( P < 0.001). AME and AMEn did not differ between the MED and SLO diets ( P > 0.05). It is worth noting that HI was higher in the RAP diet than in the other diets ( P < 0.05). For energy utilization efficiency, the RAP diet showed the lowest NE:AME, NE:AMEn and NE:GE ratio ( P < 0.001), while the HP:GE and HI:GE ratios were the highest ( P < 0.001). The NE:GE ratio did not differ among the MED, SLO and RES diets ( P > 0.05). Most efficiency metrics were similar between the MED and SLO diets ( P > 0.05). Blood biochemical parameters Dynamic variation of blood glucose and insulin Fig. 2 A shows the changes in plasma glucose during feeding. At 30 min, the RAP diet reached its peak and this value was higher than in the other diets ( P < 0.05). Glucose in the MED, SLO and RES diets peaked at 60 min with no differences among them, while the RAP diet was lower than MED and RES at this point ( P < 0.05). No significant differences were measured from 90 to 120 min ( P > 0.05). Fig. 2. Open in a new tab Effects of starch digestion kinetics on dynamic variation of blood glucose and insulin of laying hens. Different letters at the same time point indicate significant differences ( P < 0.05). RAP = rapidly digestible starch diet; MED = medium starch digestion rate diet; SLO = slowly digestible starch diet; RES = resistant starch diet. The insulin response during feeding is shown in Fig. 2 B. The RAP diet elicited the greatest insulin response and reached its peak as early as 30 min ( P < 0.05), followed by pronounced temporal fluctuations. By contrast, the other diets exhibited later peak responses, mostly at 60 min, with comparatively flatter response curves. Fasted serum reproductive hormones Table 6 presents the serum reproductive hormones. The LH level appeared highest in the MED diet among all diets ( P < 0.05). Moreover, the E2 level was raised in the RES diet relative to the other diets ( P < 0.05). No significant effects were found for PRL, P4, or FSH across the four diets ( P > 0.05). Table 6. Effects of starch digestion kinetics on reproductive hormones and nitrogen related metabolites in laying hens. Items RAP MED SLO RES SEM P -value Reproductive hormones LH, mIU/mL 12.4 b 17.0 a 13.0 b 13.3 b 0.46 < 0.001 E2, pg/mL 296 b 318 b 332 b 385 a 9.87 < 0.001 PRL, ng/mL 33.9 32.6 33.6 33.6 0.86 0.737 P4, ng/mL 26.8 26.5 27.5 27.9 1.04 0.785 FSH, ng/mL 21.6 22.5 22.5 22.4 0.43 0.432 Nitrogen related metabolites Urea nitrogen, mmol/L 0.27 0.21 0.22 0.23 0.022 0.215 Uric acid, µmol/L 250 a 204 b 197 b 195 b 11.35 0.007 Open in a new tab Means with different superscripts in a row indicate significant differences ( P < 0.05), number of replications = 7. RAP = rapidly digestible starch diet; MED = medium starch digestion rate diet; SLO = slowly digestible starch diet; RES = resistant starch diet; LH = luteinizing hormone; E2 = estradiol; PRL = prolactin; P4 = progesterone; FSH = follicle stimulating hormone; SEM = standard error of the mean. Fasted serum uric acid and urea nitrogen The fasted serum levels of uric acid and urea nitrogen are shown in Table 6 . Urea nitrogen did not differ among diets ( P > 0.05). The uric acid level was higher in the RAP diet than in the other three diets ( P < 0.05). Regression model Fig. 3 shows the regression curves between digestion rate constant k and the energy utilization indices, and the regression equations and their predicted extrema are presented in Table 7 . Quadratic regression showed curved relationships between k and the NE:AME, NE:GE, HP:GE and HI:GE ratio. The regression for the NE:AME ratio reached its maximum at k = 0.0391 ( R² = 0.970; P = 0.173), while the NE:GE ratio showed a maximum at k = 0.0368 ( R² = 0.908; P = 0.304). The minimum HP:GE ratio was obtained at k = 0.0422 ( R² = 0.980; P = 0.141). Only the regression for the HI:GE ratio was statistically significant, with the minimum at k = 0.0407 ( R² = 0.999; P = 0.030). Fig. 3. Open in a new tab Regression curves of energy utilization efficiency with the starch digestion kinetic parameter k . NE = net energy; AME = apparent metabolizable energy; GE = gross energy; HP = heat production; HI = heat increment; k = starch digestion rate constant. Table 7. Regression equations of energy utilization efficiency with the starch digestion kinetic constant k . No. Prediction equation Extreme value R 2 P -value A NE:AME = − 21880 k 2 + 1710 k + 37.5 k max = 0.0391 0.970 0.173 (NE:AME) max , % = 70.9 B NE:GE = − 17725 k 2 + 1306 k + 39.7 k max = 0.0368 0.908 0.304 (NE:GE) max , % = 63.8 C HP:GE = 39454 k 2 − 3326 k + 120 k min = 0.0422 0.980 0.141 (HP:GE) min , % = 50.0 D HI:GE = 24830 k 2 − 2023 k + 58.3 k min = 0.0407 0.999 0.030 (HI:GE) min , % = 17.1 Open in a new tab NE = net energy; AME = apparent metabolizable energy; GE = gross energy; HP = heat production; HI = heat increment; k = starch digestion rate constant (min −1 ). Discussion The four diets showed differences in in vitro starch hydrolysis, blood glucose and insulin responses. Building in vitro digestion models with several starch-degrading enzymes is a relatively simple and low-cost method ( Butterworth, et al., 2012 ; Sharma, et al., 2022 ), and well-designed systems have shown strong correlations with in vivo digestion ( Boisen and Ferna´ndez, 1995 ; Zaefarian, et al., 2021 ). Starches from different sources showed different in vitro digestion characteristics ( Dona, et al., 2010 ), especially the rapid digestion of extruded maize and the slow digestion of pea starch ( Sharma, et al., 2021 ; Zhu, et al., 2023 ), which aligned with the digestive trends observed in the dietary patterns we designed. The RAP diet containing 29.87 % extruded maize showed the highest digestion rate constant k and RDS level, and hens in the RAP diet showed more pronounced postprandial glucose and insulin fluctuations compared with the other diets. Insulin is a key regulator of glucose transport and of fat and amino acid metabolism ( Selle, et al., 2025 ). When insulin levels are high, blood glucose is converted into glycogen, body protein and body fat for energy storage, thereby maintaining normal blood glucose levels ( Lewis, et al., 2021 ). Marked insulin fluctuations can cause a sharp fall in glucose after the postprandial peak ( Ji, et al., 2020 ), which is unfavorable for sustained energy supply. Conversely, the other three diets had higher SDS and RS levels and elicited milder peaks in glucose and insulin. Previous studies have shown that SDS reduces postprandial glucose–insulin fluctuations in poultry ( Luo, et al., 2023 ; Yang, et al., 2025 ), supporting a sustained energy supply through the gradual release of glucose in the small intestine. RS that escapes enzymatic digestion is typically fermented in the hindgut to produce short chain fatty acids ( SCFAs ) ( Regassa and Nyachoti, 2018 ), providing an energy source for the hindgut. However, excessive RS levels can reduce starch digestibility potential and may fail to sustain the high energy demand required for egg production. In summary, an excessively rapid glucose release elevates blood glucose and insulin within a short period and intensifies their fluctuations, whereas a moderate glucose–insulin dynamic helps sustain the supply of glucose and energy. As laying hens rely on high energy output for egg formation, a stable and continuous blood glucose supply is particularly important. This study showed that the dietary glucose release rate affected laying performance and reproductive endocrine responses in hens. Under the conditions of this experiment, diets differing in starch digestion kinetics did not significantly alter FI prod or FCR, but they did influence the partitioning of nutrients between BWG and EM. Compared with the MED diet, the RAP, SLO and RES diets all resulted in greater BWG. Based on the in vitro digestion characteristics, the higher BWG observed with the RAP diet may be related to its higher digestion rate constant k and digestion potential C ∞ . The SLO diet contained highest levels of SDS, and previous research has shown that moderate amounts of slowly digestible pea starch can promote BWG in laying hens ( Herwig, et al., 2019a ). The RES diet showed the highest BWG. This could not be explained solely by the higher SDS level, and the k was not the lowest among all treatment groups, although the high RS level reduced C ∞ . Overall, the relationship between EM and BWG may be influenced by a combination of digestion rate and digestion extent. Regarding laying performance, the MED diet showed higher HDEP and EM than the RAP diet. On the one hand, the result may be attributable to its steadier glucose–insulin dynamics, which can support continuous energy provision for egg production. On the other hand, laying performance is primarily regulated by reproductive hormones secreted by the hypothalamic–pituitary–gonadal ( HPG ) axis. Energy supply is an important determinant of reproductive function in poultry ( dePersio, et al., 2015 ; Xue, et al., 2022 ). We speculate that metabolic responses induced by fluctuations in glucose and insulin may influence hormonal secretion from the HPG axis ( Lu, et al., 2024 ; Sliwowska, et al., 2014 ), thereby affecting laying performance. LH is key hormone regulating ovulation in poultry ( Li, et al., 2025 ; Prastiya, et al., 2022 ). The MED diet showed the highest HDEP value together with a higher LH level, supporting the positive association between reproductive hormone levels and laying performance. E2 is a key promoter of yolk synthesis and secondary follicle development, but elevated E2 exerts negative feedback on the HPG axis and suppresses pituitary secretion of FSH and LH ( Hanlon, et al., 2022 ). In the RES diet, we observed the highest E2 level, whereas FSH and LH levels were not the highest, which may explain why the RES diet did not show higher egg production than the MED diet despite its adequate energy supply. Overall, we infer that the glucose release rate may influence endocrine regulation by altering blood glucose fluctuations, which in turn affects laying performance. We assessed nitrogen balance and blood nitrogenous metabolites to determine the effect of dietary glucose release rate on nitrogen utilization efficiency in laying hens. Nitrogen balance reflects the actual distribution of nitrogen intake, excretion and body deposition, whereas blood nitrogenous metabolites indicate the extent of amino acid catabolism. In this study, the RES and SLO diets exhibited significantly higher TRNR than the RAP diet, and the RAP diet resulted in markedly higher uric acid levels than the other diets. Uric acid is the principal end product of nitrogen metabolism in poultry ( Scanes, 2015 ). By contrast, the lower uric acid concentrations in the MED, SLO and RES diets suggest reduced amino acid oxidation. SDS can increase glucose availability in the distal small intestine to meet the energy demands of enterocytes, thus reducing amino acid catabolism and enhancing protein deposition ( Aftab, et al., 2018 ). We consider that the excessively rapid glucose release of the RAP diet may cause substantial glucose absorption in the proximal gut, limiting glucose supply to the distal regions and increasing the reliance of enterocytes on amino acids for energy production or gluconeogenesis, ultimately lowering TRNR ( Macelline, et al., 2025 ). In addition, insulin can stimulate amino acid absorption ( Davis, et al., 2010 ). The higher insulin levels observed under the RAP diet may accelerate amino acid uptake, creating asynchrony in the release of dietary amino acids and thereby reducing nitrogen utilization ( Selle, et al., 2022 ; Zhang, et al., 2022 ). Matching the release kinetics of glucose and amino acids in the diet is essential, as imbalance between the two can impair amino acid utilization ( Luo, et al., 2025b ). Herwig, et al. (2019b) reported that an appropriate level of SDS improved feed efficiency in broilers. However, increasing SDS in low-protein diets reduced growth performance and amino acid digestibility in broilers ( Luo, et al., 2025c ). These findings suggest that the mode of action of starch digestion kinetics may differ under low-protein conditions or when unconventional protein sources are used. Notably, the SLO and RES diets showed relatively high nitrogen retention, although this nitrogen was stored mainly as body protein rather than being deposited in eggs. We suggest that egg quality is influenced by reproductive hormones, while the glucose release profiles of the SLO and RES diets did not significantly affect laying performance yet were supportive of body protein synthesis. These results suggest that shifting starch digestion toward a slower pattern may help reduce nitrogen loss, which could be beneficial for lowering the environmental burden of laying hen production. Overall, nitrogen balance and blood nitrogenous metabolites provided aligned evidence at whole-body and metabolic levels, indicating that an appropriate range of glucose release can support protein deposition in laying hens. Our findings showed that energy metabolism in laying hens was clearly influenced by starch digestion kinetics. In this study, “energy control” by different feed types mainly reflects how dietary energy was partitioned between HI and NE, which was driven by differences in the rate and extent of glucose release from starch. In general, energy intake is positively associated with heat production in animals ( Barzegar, et al., 2020 ). In this study, the RAP diet did not differ from the other diets in GE intake , with a slightly lower mean value, yet its HP intake and HI intake were significantly higher than those of the other diets. The RAP diet lost a comparatively greater proportion of its AME intake as heat, resulting in the lowest NE intake . Accordingly, the RAP diet showed the lowest NE value and the highest HI. In terms of energy utilization efficiency, the RAP diet also showed the lowest NE utilization efficiency. More than 25 % of GE was converted into HI under the RAP diet, whereas the MED, SLO and RES diets remained below 20 %. These results indicate that, under comparable GE intake , an excessively rapid glucose release increased the proportion of AME dissipated as HI and reduced the NE available for productive purposes, whereas more gradual glucose release limited this heat loss and improved NE utilization efficiency. Sharma, et al. (2021) reported that a pea-based diet with slower starch digestion showed higher AME and NE than a wheat-based diet with faster starch digestion, while HI remained unchanged. This may be attributed to the larger differences in starch digestibility among the diets formulated in our study, which resulted in more pronounced effects on energy metabolism. From a metabolic perspective, rapid glucose release causes distinct fluctuations in blood glucose and insulin, which may increase the metabolic cost of maintaining homeostasis. When excess glucose is available over a short period, more nutrients may be directed toward glycogen synthesis, lipogenesis, and related amino acid metabolism ( Alemany, 2011 ), whereas catabolic pathways are activated during egg production or when energy supply is insufficient. Frequent shifts between these anabolic and catabolic processes may increase energy expenditure as heat ( Bender, 2012 ; Solinas, et al., 2015 ). In particular, amino acid oxidation for energy causes additional nitrogen loss ( Macelline, et al., 2025 ), which is reflected in the clearly lower RE prot observed in the RAP diet. Our previous study in growing pigs showed that extruded maize with rapid glucose release reduced protein deposition ( Zhu, et al., 2023 ). Li, et al. (2024b) also showed that modifying the glucose release rate can enhance nitrogen utilization and deposition in laying hens. In addition, RS is less digestible in the upper intestine and is instead fermented to SCFAs in the hindgut, a pathway that may recover energy less efficiently than direct glucose absorption from enzymatically digestible starch ( Regassa and Nyachoti, 2018 ). This may partly explain why increasing RS does not necessarily improve NE. However, when included at appropriate levels as a prebiotic ( Yaqoob, et al., 2021 ), RS can improve the hindgut immune–metabolic environment, which may provide a potential route for enhancing energy utilization efficiency ( Li, et al., 2024b ). The effects of starch digestion kinetics on energy metabolism may also be modulated by environmental and physiological conditions ( Fernández-Calleja, et al., 2019 ; Qaid and Al-Garadi, 2021 ). The optimal range of dietary glucose release rates may vary according to environmental conditions and production objectives. In summary, under positive environmental and management conditions, we consider that an appropriate range of dietary glucose release rates enables tissues to efficiently absorb and utilize glucose, supporting normal metabolic and laying demands while reducing HI production. We consider that a suitable rate of glucose release may exist to improve energy utilization in peak laying hens. To explore this relationship, we performed an exploratory analysis using a quadratic regression model. We used the digestion rate constant k, rather than RDS, SDS, RS, or C ∞ , as the kinetic indicator in this analysis because k better reflects the rate related feature of starch hydrolysis across the whole digestion process. By contrast, RDS, SDS, and RS are fraction based indices derived from fixed digestion windows, whereas C ∞ mainly reflects the potential extent of hydrolysis rather than the rate of glucose release. For this reason, k was considered more suitable than C ∞ for discussing how starch digestion kinetics may be linked to the NE system, because NE utilization depends not only on how much substrate is digested, but also on when it becomes available for metabolism. With only four treatment levels, most regressions were not statistically significant. However, the models still provided useful information. As k increased, NE utilization efficiency followed a quadratic pattern with a maximum, whereas the HI:GE and HP:GE ratios showed quadratic minima, and only the HI:GE model was significant. del Alamo, et al. (2009) reported quadratic effects of dietary starch digestibility on most growth variables in broilers, and Herwig, et al. (2019a) showed a quadratic relationship between HDEP and the content of slowly digestible pea starch in laying hens during weeks 10–20. Given the limited number of data points, the precision of this estimated optimum requires validation with additional data, and the optimal k may differ with breed, age, environment, etc. Nevertheless, as a preliminary exploration, this study suggests a direction: energy utilization efficiency in peak laying hens may be improved by adjusting the dietary starch digestion kinetic to an appropriate range. Conclusion This study showed that starch digestion kinetics shaped metabolic homeostasis and energy efficiency in peak laying hens. The digestion rate constant k appeared to have an optimal range that may stabilise blood glucose patterns and coordinate endocrine and nitrogen metabolism, thereby improving NE efficiency. Consequently, this study proposes a k -centred kinetic perspective, providing a theoretical basis for precision nutrition and diet optimization in commercial layers. CRediT authorship contribution statement Haoran Zhu: Writing – review & editing, Writing – original draft, Methodology, Formal analysis, Data curation, Conceptualization. Minghui Fu: Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Haixia Ding: Writing – original draft, Visualization, Formal analysis. Jianxin Liang: Investigation. Xutong Chen: Investigation. Guixin Qin: Supervision, Resources, Conceptualization. Li Pan: Supervision, Project administration, Conceptualization. Nan Bao: Writing – review & editing, Validation, Supervision, Resources, Methodology, Funding acquisition, Data curation, Conceptualization. Yuan Zhao: Writing – review & editing, Validation, Supervision, Resources, Methodology, Conceptualization. Disclosures The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. 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