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Huhtanen Title: Variation in individual milk production responses to supplementary protein feeding with two types of forages Year: 2024 Version: Published version Copyright: The Author(s) 2024 Rights: CC BY 4.0 Rights url: https://creativecommons.org/licenses/by/4.0/ Please cite the original version: A. Sairanen, P. Huhtanen, Variation in individual milk production responses to supplementary protein feeding with two types of forages, Livestock Science, Volume 280, 2024, 105394, ISSN 1871-1413, https://doi.org/10.1016/j.livsci.2023.105394. https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.1016/j.livsci.2023.105394 Livestock Science 280 (2024) 105394 Available online 22 December 2023 1871-1413/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Variation in individual milk production responses to supplementary protein feeding with two types of forages A. Sairanen a,*, P. Huhtanen b a Natural Resources Institute Finland (Luke), Halolantie 31, Maaninka FI-71750, Finland b Natural Resources Institute Finland (Luke), Jokioinen FI-31600, Finland H I G H L I G H T S • Production responses to supplementary protein were not related to forage type. • Production responses were not related to animal variables during covariate period. • Responses to supplementary protein were positively related to intake responses. • Metabolizable protein supply per unit of intake increases with intake. • High yielding cows may not need higher dietary protein concentration. A R T I C L E I N F O Keywords: Dairy cow Nitrogen utilization Rapeseed meal Whole crop silage Grass silage Precision feeding A B S T R A C T The objectives of the present experiment were to investigate the effects of forage type and protein supplemen tation on feed intake and milk production, and between-cow variability in responses to protein supplementation. The experiment was conducted using 40 cows (28 Holstein, 12 Nordic Red, 25 multiparous, 15 primiparous). Experiment started with a covariate period of 14 d when cows received TMR (concentrate:forage, 40:60). After the covariate period four experimental diets were arranged in 2 × 2 factorial design with two forages and two concentrate CP levels. The forage treatment included grass silage (GS) and a mixture of whole-crop wheat/oats silage and grass silage (MIX; 40:60) on DM basis. The concentrate treatment included two concentrate CP levels [low CP (115 g CP/kg DM) and medium CP (166 g CP/kg DM)]. Concentrate CP concentration was increased by replacing barley and oats with rapeseed meal. The cows were fed the same forage throughout the 63-d experi ment, whereas the CP treatments were compared in a switch-back design including three 21 d periods. Individual protein supplementation response was calculated based on switch-back periods. Feeding the MIX forage increased total DM intake by 1.3 kg/d compared with the GS diets but milk production was not influenced by forage type. Dry matter and nutrient intake increased with CP level similarly with forages. The production of milk components and milk urea concentration increased with CP level, whereas milk N efficiency decreased. Energy corrected milk (ECM) yield response to protein supplementation was not related to ECM yield measured during the covariate period whereas the ECM response was negatively related to calculated energy balance during covariate period. It is concluded that intake and production responses to moderate level of protein supplementation were highly variable, but the extent of variation could not be predicted from animal charac teristics available in farm conditions. When the supply of metabolizable protein (MP) was simulated by the Karoline model for each animal, predicted MP concentration increased 0.8 g/kg increase in DM intake. This is compatible to increased MP requirement on DM basis with enhanced production level. Both the lack of the effects of initial production level on CP response and the higher predicted MP concentration with increased intake suggest that high yielding cows can deal with the higher MP requirement (on DM basis) without increasing dietary CP concentration. This project was funded by the Finnish Ministry of Agriculture and Forestry (project number 2213/03.01.02/2015) and Valio Ltd. and Raisioagro Ltd. * Corresponding author. E-mail address: auvo.sairanen@luke.fi (A. Sairanen). Contents lists available at ScienceDirect Livestock Science journal homepage: www.elsevier.com/locate/livsci https://doi.org/10.1016/j.livsci.2023.105394 Received 2 May 2023; Received in revised form 6 November 2023; Accepted 21 December 2023 mailto:auvo.sairanen@luke.fi www.sciencedirect.com/science/journal/18711413 https://www.elsevier.com/locate/livsci https://doi.org/10.1016/j.livsci.2023.105394 https://doi.org/10.1016/j.livsci.2023.105394 https://doi.org/10.1016/j.livsci.2023.105394 http://crossmark.crossref.org/dialog/?doi=10.1016/j.livsci.2023.105394&domain=pdf http://creativecommons.org/licenses/by/4.0/ Livestock Science 280 (2024) 105394 2 1. Introduction The efficiency of utilization of feed N (milk N/N intake; MNE) is relatively low in milk production. According to Huhtanen and Hristov (2009) the average MNE was 0.25 in 736 North American diets and 0.28 in 998 North European diets. The MNE varied from 0.14 to 0.45 showing the possibility to improve the N efficiency (Huhtanen and Hristov, 2009). Because large amounts of N cannot be retained in body tissues, the major proportion of N intake in excess to milk N is excreted in manure, especially in urine (Tamminga 1992). Low marginal milk pro tein yield (MPY) responses (100–136 g/kg incremental CP intake) even to high quality protein supplements (Huhtanen et al., 2011a) suggest that the major fraction of incremental N given as protein supplements is lost in urine which is more vulnerable than faecal N for leaching and evaporative losses (Castillo et al., 2000). Milk production and MNE responses to protein supplementation have been intensively studied, but variation in responses among the cows to protein supplementation has not received much attention. Milk yield decreases with reduced protein supplementation, but some cows may tolerate low protein diets better as they may have a higher effi ciency of microbial protein synthesis. They may be metabolically more efficient in producing milk protein. By identifying responsive cows, or alternatively cows that have resilience to low protein diets (Liu and VandeHaar, 2020), greater MNE together with smaller ammonia losses could be obtained. The objective of the current study was designed to evaluate variation in production response to moderate level of protein supplementation. Heterogenous group of cows varying in feed intake, milk production, days in milk (DIM) and parity was used to determine possible factors affecting the responses. Two different basal diets based on two forages (grass silage and mixture of grass and whole-crop silage) were used to study if the CP concentration of basal diet affects on re sponses. The supply of MP for individual cows was predicted by the Nordic dairy cow model Karoline (Danfaer et al., 2006; Huhtanen et al., 2015b) to evaluate the effects of feed intake on dietary MP concentra tion. Karoline was used to test the hypothesis if increased supply of MP per unit of intake covers the higher MP requirement with increased milk yield without changing diet composition. 2. Materials and methods 2.1. Experimental feeds The regrowth grass silage from timothy (Phleum pratense, cv. Tuure) and meadow fescue (Festuca pratensis, cv. Valtteri) sward was harvested on 27th July 2017 at the experimental farm of Natural Institute Finland (Luke) and stored in a bunker silo. The swards were cut using a mower conditioner, wilted for 12–24 h before harvesting with a self-propelled harvester and ensiled using a formic acid-based additive (AIV2 Plus Na, Eastman, Oulu, Finland) at a target rate of 5 l/t. The whole crop silage was harvested on 4th September 2017 from a mixture of oats (Avena sativa, cv. Bettina) and wheat (Tricum aestivum, cv. Puntari) sward using a direct-cut forage harvester. The crop was ensiled with formic acid-based additive (AIV Ässä Na) applied at the rate of 5 l/t and stored in a bunker silo. Pelleted experimental concentrates (Raisioagro Ltd.) contained two levels of CP. The low CP concentrate (LCP) consisted of (g/kg on weight basis) of barley (390), oats (390), sugar beet pulp (180), vegetable oil (20) and minerals (20), respectively. The medium CP concentrate (MCP) consisted of barley (310), oats (310), sugar beet pulp (200), rapeseed meal (RSM, 140), vegetable oil (20) and minerals (20). 2.2. Animals, diets, and experimental design The experiment was conducted with 40 cows (28 Holstein, 12 Nordic Red; 25 multiparous, 15 primiparous). The average (±SD) energy cor rected milk yield (ECM) was 33.5 ± 4.60 kg, body weight (BW) 619 ± 72.8 kg and DIM 164 ± 58 d The experiment started with a 14-day covariate period when the cows were fed a total mixed ration (TMR). Ingredients and nutritional values of the diets is presented in Table 1. After the covariate period the cows were blocked three blocks according to parity and DIM. The blocks were primiparous cows, mid-lactating and late-lactating multiparous cows. The forage treatment was randomly assigned to the cows within a block. After the covariate period the forages and concentrates were fed separately with the target of 400 g/kg of concentrate on DM basis. The experimental design was 2 × 2 factorial consisting of two concentrate CP levels and two forages. The forage treatments were grass silage (GS) and a mixture (MIX) of whole-crop silage and grass silage (400:600 g/kg on DM basis). The diets were GS + LCP, GS + MCP, MIX + LCP and MIX + MP, respectively. The cows were fed same forage through the experi ment, whereas the design for concentrate treatments was a switch-back with three 21 d periods. The first 14 d of each period were used as a transition and the last 7 days were used for data collection. The cows were kept in a loose-house dairy barn with rubber mat beds, offered TMR or experimental forages in separate compartments ad libitum with 10 % refusals and had a free access to drinking water. The daily TMR intake was measured with the Insentec feeders (Insentec BV, Marknesse, Netherlands). Concentrates were offered from automatic concentrate feeders (Pellon Ltd., Ylihärmä, Finland) which were equipped with BW scales. The cows were milked in a milking parlour twice daily starting at 6:00 and 16:00. 2.3. Sampling and chemical nutrient analysis Milk samples were collected from 4 consecutive milking at the end of each period and stored with Bronopol in a refrigerator before analysis. The samples were analyzed for fat, protein, lactose, and urea using an infrared analyzer (Milkoscan FT6000, Valio Ltd., Seinäjoki). Milk composition was determined based on the weighted means of the a.m. and p.m. milking. Energy corrected milk (ECM) yield was calculated according to Sjaunja et al. (1990). The DM concentration of TMR and silages were determined daily during the data collection period. Silages and concentrates for chemical analysis were sampled separately before TMR mixing during the data collection period, pooled per each experimental period, and stored at –20 ̊C. Table 1 Ingredients and nutritional values of experimental diets. Covariate period GSa MIXb LCPc MPCd LCP MCP Grass silage 400 600 600 360 360 Whole crop silage 190 240 240 Compound concentrate 400 400 400 400 Barley 240 Rapeseed meal 140 Minerals 30 g/kg DMe Neutral detergent fibre 378 408 414 402 408 Crude protein 170 147 169 134 156 Metabolizable protein 92.7 87.2 93.7 84.6 90.8 Protein balance in the rumenf 16.5 20.5 37.7 11.7 28.1 Metabolizable energyf, MJ/ kg DM 11.1 11.1 11.0 10.9 10.8 a Grass silage. b Grass silage and whole crop silage mixture in proportion of 60:40 as DM basis. c Low crude protein concentrate. d Medium crude protein concentrate. e Dry matter. f Luke 2023. A. Sairanen and P. Huhtanen Livestock Science 280 (2024) 105394 3 The DM concentration of feeds were determined by drying the samples at 105 ◦C for 20 h, while samples for chemical analyzes were dried at 60 ◦C. Dry samples were analyzed for ash (AOAC 1990, No 942.05), nitrogen (N) with the Dumas method using a Leco FP 428 analyzer, and neutral detergent fibre (NDF) according to Van Soest et al. (1991) using Na-sulphite without amylase for forages and presented ash-free. The silage samples were analyzed for pH, volatile fatty acids (VFA, Huhtanen et al. 1998), lactic acid (Haacker et al., 1983), ammonia N (McCullough 1967), water soluble N (AOAC 1990, No 984.13), water soluble carbohydrates (Somogyi 1945) and in vitro organic matter pepsin-cellulase solubility (OMS) according to Nousiainen et al. (2003). The in vitro digestibility results were calculated with correction equa tions to convert OMS values into in vivo digestibility using equations based on a data set comprising of Finnish in vivo digestibility trials (Huhtanen et al., 2006). 2.4. Simulation of nutrient supply The supply of nutrients was predicted for each cow/period obser vations by the mechanistic dynamic dairy cow model Karoline (Danfaer et al., 2006; Huhtanen et al., 2015b). Metabolizable protein was calcu lated by assuming that microbial protein contained 80 % true protein and feed MP as the amount of feed protein fractions absorbed from the small intestine. In addition to Karoline, the feed MP was also calculated based on DMI according to NRC (2001). 2.5. Calculations and statistical analysis The ME concentration of concentrates were based on the manufac turer’s information. Silages ME concentration was calculated from the concentration of digestible organic matter (Luke 2023). Metabolizable protein expressed as amino acids absorbed from the small intestine and protein balance in the rumen (PBV) were calculated according to Luke (2023). Milk nitrogen efficiency was calculated as milk N / N intake. Relative forage and total DMI potential were estimated according to equations of Huhtanen et al. (2007). Individual production responses to protein supplementation within the forage were calculated as actual means of period differences: 0.5 × (Period1 + Period3) – Period2 for the sequence MCP – LCP – MCP and as Period2 - 0.5 × (Period1 + Period3) for the sequence LCP – MCP – LCP, respectively. The regressions between the individual variables measured in the covariate period (milk production, DMI, milk yield, milk constituents, energy balance, DIM) and responses to protein supplementation during switch-back periods were tested using SAS regression analysis (SAS REG, Release 9.4, SAS Institute Inc., Cary, NC, USA). The number of obser vations in regression analysis for each independent variable was 40. A statistical comparison of production variables was performed with SAS MIXED procedure (Release 9.4, SAS Institute Inc., Cary, NC, USA). The model included treatment, sequence, CP level, forage type and CP level × forage type interaction as fixed variables. A cow and period were used as random variables. The effect of breed on milk and feed intake was rejected from the final model due the lack of significance. The co variate measured during the last 7 days of pre-experimental period was used with production variables. Due the use of covariate, the block was rejected from the final model. 3. Results 3.1. Experimental forages Both grass and whole-crop silages had low pH (4.18 vs. 3.93, respectively) with moderate fermentation quality in terms of acid and ammonia concentrations (Table 2). Both silages had relatively low ME concentrations. Silage intake potential expressed as SDMI-index was higher for the silage mixture than grass silage (Huhtanen et al., 2011b). Metabolizable protein balance value was negative for the LCP diet and positive for the MCP diet. The whole crop silage was typically low in NDF concentration compared with grass silage. 3.2. Feed intake and milk production Table 3 includes the data collected during covariate period. The variation in production parameters was large due experimental design, which included different stages of lactation. The cows fed the MIX diets had 1.1 and 1.3 kg/d (P < 0.01) higher forage and total DMI than the cows fed the GS dies (Table 4). Protein Table 2 Composition of experimental silages and concentrate supplements. Grass silage Whole crop silagea Grass-Whole crop mixtureb Concentrate LCPc MCPd DMe, g/kg 221 321 261 882 884 Chemical composition, g/kg DM Ash 103 67 89 62 62 Neutral detergent fibre 518 457 494 244 257 Crude protein 171 118 150 115 166 Starch 0 161 64.3 421 341 Water soluble carbohydrates 16 28 21 Lactic acid 67 39 56 Volatile fatty acids 34 15 26 Ammonium N, g/ kg N 97 63 83 Silage DM-intake index 82 99 89.0 Feeding values MEf, MJ/kg DM 10.3 9.5 10.0 12.2 12.0 MPg 81 77 79 95 111 PBVh 51 34 44 − 19 20 pH 4.18 3.93 4.08 D-valuei, g/kg DM 645 615 633 Ammonium N, g/ kg N 97 64 84 Soluble N, g/kg N 553 614 577 a Oats and wheat in proportion of 40:60 as seed basis. b The mixture of grass silage and whole crop silage in proportion of 60:40 as DM basis. c Low crude protein concentrate. d Medium crude protein concentrate. e Dry matter. f Metabolizable energy, Luke 2023. g Metabolizable protein, Luke 2023. h Protein balance in the rumen. i Concentration of digestible organic matter in DM. Table 3 Intake and production variables during covariate period. Mean SD Min Max Intake, kg dry matter/d Silage 11.5 1.49 9.1 14.1 Concentrate 9.8 1.03 8.1 11.6 Total 21.3 2.52 17.2 25.7 Crude protein 3.12 0.365 2.53 3.76 Metabolizable protein 1.89 0.219 1.54 2.28 Metabolizable energy, MJ 237 27.9 191 286 Milk yield, kg/d 30.5 5.07 19.9 40.3 Energy corrected milk yield, kg/d 33.5 4.64 24.1 43.4 Milk composition, g/kg Fat 47.5 5.7 37.5 57.5 Protein 35.9 2.64 30.9 41 Lactose 46.6 1.84 41.8 49.7 Urea, mg/dl 24.7 4.28 17.2 33.8 Body weight, kg 619 73.4 472 794 Days in milk 159 58.4 83 385 Days in pregnant 38 38.0 0 130 Lactation 2.48 1.63 1 8 A. Sairanen and P. Huhtanen Livestock Science 280 (2024) 105394 4 supplementation increased total DMI by 0.7 kg/d (P < 0.001) with the effect being slightly greater with the MIX diets compared with GS diets silage (interaction P = 0.10). The differences in CP intake were not significant but estimated MP intake tended (P = 0.07) to be greater for the MIX diets. Calculated PBV was positive for all diets, and greater (P < 0.01) for the GS than for the MIX and it increased with protein supplementation. Forage type did not affect milk yield, ECM yield or yield of milk components (Table 5), except milk protein concentration was higher (P = 0.03) in cows fed the MIX diets than in those fed the GS diets. Feed efficiency expressed as ECM/DMI was higher (P < 0.01) for the GS diets compared with the MIX diets. Increased protein supplementation increased (P < 0.001) the yields of milk, ECM, and milk components. Milk fat (P = 0.03) and lactose concentration (P < 0.001) decreased with increased protein supplementation, whereas milk protein and milk urea (MU, mg urea/dl) concentrations increased (P < 0.01). However, quantitatively the effects were small except for MU. Protein supple mentation increased MU more (P < 0.01) in cows fed the MIX diets compared with those fed the GS diets. 3.3. Individual cow responses The responses to protein supplementation were highly significant excluding milk protein concentration (P < 0.001; Table 6). Quantita tively the responses in milk composition were small except for MU concentration. The coefficient of variation (CV) in protein responses Table 4 Feed and nutrient intake. GSa MIXb SEM P-values LCPc MPCd LCP MCP Silage Protein Silage Protein S × P Intake, kg/d Silage DMe 11.6 12.1 12.5 13.3 0.26 0.22 <0.01 <0.01 0.10 Concentrate DM 8.9 8.9 9.1 9.1 0.21 0.16 0.38 0.50 0.80 Total DM 20.5 21.0 21.6 22.4 0.29 0.22 <0.01 <0.01 0.10 Neutral detergent fibre 8.15 8.54 8.60 9.13 0.131 0.106 <0.01 <0.01 0.09 Crude protein 3.00 3.54 2.90 3.49 0.045 0.034 0.21 <0.01 0.13 Metabolizable protein 1.78 1.96 1.83 2.04 0.026 0.019 0.10 <0.01 0.11 PBVf 0.42 0.79 0.25 0.63 0.018 0.015 <0.01 <0.01 0.42 Metabolizable energy, MJ/d 227 231 235 242 3.2 2.3 0.03 <0.01 0.14 a Grass silage. b Grass silage and whole crop silage in proportion of 60:40 as DM basis. c Low crude protein concentrate. d Medium crude protein concentrate. e Dry matter. f Protein balance in the rumen. Table 5 Milk yield, milk composition and feed efficiency. GSa MIXb SEM P-values LCPc MPCd LCP MCP Silage Protein Silage Protein S × P Milk yield, kg/d 27.4 28.7 27.0 28.4 0.73 0.67 0.59 <0.001 0.76 ECMe yield, kg/d 29.9 30.9 29.7 31.4 0.66 0.58 0.88 <0.001 0.19 Milk composition, g/kg Fat 48.0 46.6 48.4 48.3 0.69 0.55 0.23 0.03 0.05 Protein 35.3 36.0 36.0 36.7 0.36 0.33 0.04 <0.001 0.94 Lactose 44.6 44.2 44.7 44.4 0.28 0.27 0.38 <0.001 0.99 Urea, mg/dl 20.0 25.9 17.1 25.7 0.77 0.68 0.06 <0.001 <0.01 Milk components, g/d Fat 1296 1321 1289 1357 27.6 23.2 0.61 <0.001 0.07 Protein 961 1028 963 1035 19.4 16.6 0.81 <0.001 0.76 Lactose 1214 1262 1204 1256 38.5 35.5 0.80 <0.001 0.81 Feed efficiency ECM/DMIf, kg/kg 1.45 1.47 1.37 1.39 0.019 0.017 <0.01 0.04 0.87 Milk N/N intake 0.31 0.28 0.32 0.29 0.004 0.003 0.11 <0.001 0.39 a Grass silage. b Grass silage and whole crop silage in proportion of 60:40 as DM basis. c Low crude protein concentrate. d Medium crude protein concentrate. e Energy corrected milk. f Dry matter intake. Table 6 Average responses to increased protein supplementation. Response SD P-value DMa intake, kg/d 0.65 0.491 <0.001 CPb intake, g/d 564 109.6 <0.001 MPc intake, g/d 192 50.3 <0.001 Milk yield, kg/d 1.38 0.813 <0.001 Energy corrected milk yield, kg/d 1.42 1.008 <0.001 Milk composition, g/kg <0.001 Fat − 0.7 1.92 <0.001 Protein 0.7 0.70 0.03 Lactose − 0.4 0.58 <0.001 Milk urea, mg/100 ml 7.3 3.44 <0.001 Milk protein g/d 69 35.4 <0.001 g per g CP /kg DM 0.12 0.062 <0.001 g per g MP/kg DM 0.37 0.182 <0.001 a Dry matter. b Crude protein. c Metabolizable protein. A. Sairanen and P. Huhtanen Livestock Science 280 (2024) 105394 5 variables was high for milk protein yield (50 %) and even higher for milk (59 %) and ECM yield (71 %). The mean and SD of responses were not related to the length of recoding period (Fig. 1) which suggests that one week measurement period was decent. The responses of ECM to supplementary protein were not related to ECM yield (Table 7). The ECM response was greater (P = 0.01) in cows with negative ME balance during the covariate period compared with cows in positive ME-balance (2.64 vs. 1.46 kg/d). Milk protein yield responses (g / incremental unit of CP or MP) were not related to ECM or protein yield during the covariate period. Calcu lated ME balance was negatively related to milk protein yield responses when expressed per changes in dietary CP or MP concentrations, similarly. 3.4. Modelling MP The differences in MP supply predicted by the Karoline model re flected similar pattern to values based on Luke (2023) feed tables but were numerically about 6 % greater. Predicted increase in dietary MP concentration of the same diet with increased DMI was similar to the changes in MP requirement with increased production and intake in NRC (2001) and Luke (2023) systems (Fig. 2). 4. Discussion 4.1. Intake and production responses The individual amount of concentrate for experimental periods was fixed according to intake measurement during covariate period. The realised concentrate proportion was little higher compared with the target of 400 g/kg in DM and it was 15 g/kg DM higher with MIX compared with GS. The difference was so small that it had minor effect on results. Observed increase in DMI (1.3 kg/d) with MIX agreed with the predictions (1.4 kg/d) based on silage DMI index (Huhtanen et al., 2007). Grass silage was harvested from regrowth, and it had lower DM concentration and higher total acid concentration than whole crop silage, all which have negative effects on silage DMI. Feeding mixtures of whole-crop and grass silages has caused positive associative effects in intake compared with feeding a single forage (Huhtanen et al., 2007; Jaakkola et al., 2009). Increased DM intake compensated the low di gestibility of MIX compared with GS, and the calculated ME intake was higher with MIX diets. Increasing dietary CP concentration by RSM supplementation increased total DMI by 0.30 kg per 10 g/kg increase in CP which agrees with the meta-analysis of RSM supplementation studies (Huhtanen et al., 2011a). The average intake response to RSM supplementation (0.7 kg DM/d) is in line with the study of Jaakkola et al. (2009). In their study the intake responses to RSM supplementation were not related to the proportion of whole-crop silage. No differences were observed between the forages in milk yield or milk components although calculated ME intake was about 10 MJ/ d greater for the MIX diets compared with the GS diets. Assuming 0.10 kg ECM/MJ ME production response to increased ME intake when the cows are close to zero energy balance, ECM yield should have been about 1.0 kg/d greater for cows fed the MIX diets. However, the depression in diet digestibility at production level of intake could be greater for the MIX diets compared with GS. This is supported by Ahvenjärvi et al. (2006) who suggested that the digestibility of pdNDF is decreased with increased proportion of whole-crop silage. Overall, the positive associative intake effects of feeding mixtures of grass and whole crop silages compensates for the lower digestibility of whole crop silages. The average MPY responses of 125 g/kg incremental CP intake agrees with the values of 136 and 133 g/kg CP for untreated and heat- treated RSM in the meta-analysis of Huhtanen et al. (2011a). The posi tive effect of RSM on milk and protein yield was similar in cows fed diets based on GS or MIX despite lower CP concentration in MIX. When forage CP concentration was increased by earlier harvesting of grass (Rinne et al., 1999), higher N fertilization of grass sward (Shingfield et al., 2001) or increasing replacement of grass silage with red clover silage (Gidlund et al., 2017) production responses to increased protein sup plementation were not related to forage CP concentration. The efficiency of N utilization of GS was in accordance with pub lished reviews (Castillo et al., 2000; Huhtanen and Hristov, 2009). Typically, the utilization decreases with increasing diet CP concentra tion, but forage type had no significant effect despite of 12 g/kg DM difference between MIX and GS. Increased intake of MIX increased CP intake which compensated low CP content. Using treatment mean values MNE decreased 1.28 g/kg N (R2 = 0.92) per 1 g/kg DM increase in di etary CP concentration. This value agrees with Huhtanen and Hristov (2009) who reported corresponding decreases of 1.21 and 1.40 for typical North European and North American diets, respectively. 4.2. Individual cow responses Milk yield response remained stable irrespective of the length of measurement period suggesting that full response to protein supple mentation was obtained in one week (Fig. 1). With post-ruminal casein infusion changes over time for key response variables indicated that a 4- day adaptation period was appropriate (Ardalan et al., 2022). Choung et al. (1993) reported that maximum response to abomasal casein infusion was reached in 3 days. Even shorter period reaching the com plete response was reported by Whitelaw et al. (1986). Although reaching the full production response with protein supplementation can take longer compared with protein infusions, stable responses (Fig. 1) indicate that the length of adaptation or measurement period did not affect the results. Neither between-cow variability in production was not influenced by the length of measurement periods There was considerable variability among cows in ECM (coefficient of variation, CV = 0.70) and milk protein yield (CV = 0.50) responses to increased CP supplementation. High variability in ECM responses can partly be related to random sampling errors in milk fat composition. Numerically ECM and MPY responses were positive for 38 and 39 out of 40 cows. The two cows with negative ECM responses had unexpected low milk fat concentration with MCP diet. Ideally, protein supplements should be given to the cows that respond better to optimize economy and to reduce environmental emissions. The practical problem is how to identify the cows responding better to increased CP intake and/or less to decreased CP intake. To be useful the response predictor should be easily available in farm conditions, such as current milk yield and composition, DIM, and parity. Intake of efficiency variables are not practical due to difficulties in measuring DMI on farm conditions. The proportion of RSM in dietary DM was constant, i.e., high yield Fig. 1. The effect of the length of recording period on mean and standard deviation (SD) of milk yield responses to supplementary protein feeding. A. Sairanen and P. Huhtanen Livestock Science 280 (2024) 105394 6 cows with higher DMI also consumed more RSM. When the ECM response to protein supplementation was expressed per kg RSM intake (or incremental CP intake) the effect of covariate ECM yield on the response was not significant. Overall, the effects of covariate ECM yield on protein responses were quantitatively small. Reallocating RSM from low yielding cows to high yielding cows would result in 0.11 kg increase in average ECM yield / d. Negative relationship between calculated ME balance during the covariate period and ECM response could be expected. This phenome non agrees observations from energy metabolism. In a respiration chamber study (Kirkland and Gordon, 2001) early lactation cows in negative energy balance partitioned more energy to milk than late lactation cows in positive energy balance. It is also possible that the cows in negative ME balance were more efficient than cows in positive ME balance, since ME balance was calculated from maintenance and production coefficients. The calculation of ME balance also requires data on DMI that is not available in practical farms. Milk protein yield response was not related with ECM or protein yields during the covariate period when expressed per kg CP or MP intake (Table 7). In agreement with the present study, responses to increased MP supply were not related to average milk production level in the study (Huhtanen and Nousiainen 2012). The lack of DIM effects on MPY agrees with Liu and VandeHaar (2020) who reported 0.14 and 0.12 kg/d higher MPY for high vs low protein diets in early and late lactation, respectively. Milk urea concentration is positively related to dietary CP concentra tion and negatively to MNE (Broderick and Clayton, 1997; Nousiainen et al., 2004) when dietary effects are considered. Therefore, it could be expected that cows with high MU have lower MNE than the cows with low MU when fed the same diet. In the present study MU was highly variable between the cows during covariate period (CV = 0.17), but it was not related to MNE. Neither the response to supplementary protein was related to MU during the covariate period or to the difference in MU between LP and MP treatments. The changes in MU between low and high CP diets were similar among high and low protein resilience cows in both early and late lactation (Li and VandeHaar, 2020). In the meta-analysis of individual cow data (Huhtanen et al., 2015a) MNE decreased significantly with increased MU concentration, but the effects were quantitatively too small for reliable ranking of the cows according to MNE. The intake response (mean 0.65 kg DM/d) was highly variable among the cows (CV = 0.75, range -0.4 -1.8 kg/d), but it was insignif icantly related to any animal (BW, DIM), feed intake, milk production and composition variables or calculated MP and ME balances during the covariate period. Observed ECM responses to supplementary protein were more closely (P = 0.001, R2 = 0.25) related to observed DMI response during the experiment than to DMI or ECM levels during the covariate period (ECM response (kg/d) = 0.75 ± 0.23 + 1.02 ± 0.29 × DMI response (kg/d)). Both regression coefficient and intercept were significant (P < 0.01). Assuming ME concentration of 11 MJ/kg DM the ECM response was 0.093 kg ECM per MJ incremental ME that agrees with marginal ME intake responses in cows at different production levels in meta-analysis Table 7 The effects of covariate period variables on production responses to protein supplementation. Covariate Intercept Slope RMSE R2 Estimate SE P-value Estimate SE P-value ECMa response, g /kg MP intake Milk, kg/d 4.48 3.484 0.21 0.03 0.112 0.75 3.57 0.003 ECM, kg/d − 0.34 4.066 0.93 0.17 0.120 0.15 3.48 0.054 DMIb, kg/d 5.14 4.939 0.30 0.02 0.229 0.93 3.58 0.000 Body weight, kg 4.26 4.909 0.39 0.00 0.008 0.79 3.57 0.002 Days in milk 6.45 1.649 <0.001 − 0.01 0.010 0.57 3.56 0.008 Milk fat, g/kg − 4.74 4.506 0.30 0.21 0.094 0.03 3.35 0.123 MEc balance, MJ/d 25.6 17.52 0.15 − 0.73 0.366 0.05 13.0 0.095 Milk protein/fat 42.2 19.74 0.04 − 38.8 14.85 0.01 12.6 0.152 MUd 3.69 3.35 0.28 0.07 0.133 0.57 3.56 0.008 Protein yield response, g/kg CP intake ECM, kg/d 61 73 0.41 1.9 2.16 0.38 62.5 0.02 Protein yield, g/d 80 71 0.27 0.04 0.065 0.52 62.8 0.011 DMI, kg/d 155 87 0.08 − 1.4 4.04 0.73 63.0 0.003 MU, mg/100 mL 92 59.1 0.13 1.3 2.35 0.58 62.9 0.008 ME balance, MJ/d 110 11.3 <0.001 − 1.7 0.70 0.02 58.9 0.131 Protein yield response, g/kg MP intake ECM, kg/d 254 215 0.24 3.5 6.36 0.59 184.1 0.008 Protein yield g/d 299 208.7 0.30 0 0 0.82 184.5 0.003 DMI, kg/d 510 254.1 0.05 − 6.5 11.81 0.58 184.1 0.008 Days in milk 344 85.4 0 0.2 0.51 0.74 184.6 0.003 MU, mg/100 mL 274 173 0.12 3.9 6.89 0.57 184.1 0.008 ME balance, MJ/d 329 33.3 <0.001 − 4.6 2.06 0.03 173.9 0.115 a Energy corrected milk. b Dry matter intake. c Metabolizable energy. d Milk urea. Fig. 2. The effect of dry matter intake (DMI) on MP requirement (g/kg DMI) according to NRC (2001) and Luke (2023) systems and predicted changes in MP concentration (g/kg DM) according to Karoline simulations when fed experi mental diets. A. Sairanen and P. Huhtanen Livestock Science 280 (2024) 105394 7 of Huhtanen and Nousiainen (2012). Positive intercept could be inter preted as a specific protein effect. Liu and VandeHaar (2020) reported greater decreases in DMI and ECM yield in low protein resilience cows compared with high protein resilience cows when dietary CP concentration was decreased. The same effects were observed in both early and late lactation. Their results indicated that there was significant variation in DMI responses among cows when fed low protein diet. Different DMI responses to supple mentary protein could be explained by minimizing discomfort (Forbes, 2007). The animal must balance the problems arising from insufficient amino acids with those arising from excess energy. Greater intake re sponses to duodenal protein infusion compared with ruminal protein or glucose infusions (Faverdin et al., 2003) and to high quality (fish meal, RSM) protein supplements compared with low quality (feather meal, wheat gluten meal) protein supplements (Chamberlain et al., 1992; Shingfield et al., 2001) support this theory. Improved AA/ME balance increased milk production that “pulled” intake. It could be expected that there are between-cow differences in the MP supply even at the same intake due to differences in digesta passage rate. 4.3. Between-cow variation in MP supply Although calculated MP/ME ratio is constant within a diet, differ ence in feed intake and passage rate can lead to substantial differences in the efficiency of microbial protein synthesis and escape of rumen undegraded protein. In the study of Volden (1999) the efficiency of microbial N synthesis per kg digested organic matter (OM) was on average 19 % greater for cows at high feeding level compared to those at low level of feeding (18 vs. 9 kg OM/d, respectively). Similarly, Bro derick et al. (2010) reported increased microbial N efficiency with increased DMI. Most likely these effects are related to increased digesta passage rate and to reduced ATP requirement for microbial mainte nance. Substantial between-animal variation in digesta passage kinetics (Pinares-Patiño et al., 2003; Cabezas-Garcia et al., 2017) suggest that MP/ME ratio can differ between the cows even when fed the same diet at same intake. The increase in the efficiency of microbial N synthesis with increased DMI was similar (0.29 vs. 0.34 g/kg OM truly digested per kg increase in DMI) in Karoline simulations and in the analysis of omasal flow data (Broderick et al., 2010). Whether the variation in the MP supply even at the same intake is related to variation in production re sponses to supplementary protein needs further investigations. Calculated MP requirement per kg DMI increases with increased production level (NRC, 2001; Luke, 2023) and therefore dietary MP concentration should increase with milk yield to meet the calculated requirements. However, because of the faster digesta passage rate with increased dietary MP concentration increases with intake. According to the Karoline simulations predicted dietary MP concentration increased by 0.8 g/kg DMI with increased intake. The model simulations suggested that the MP supply from the same diet enhanced with DMI to cover increased MP requirements per kg DMI with increased intake and pro duction (Fig. 2). This suggests greater MP flow per kg DMI covers the need for higher dietary MP concentration with milk production. In line with this, in the analysis of data from 21 milk production studies eval uation responses to supplementary protein feeding only in one study the blocks of high yielding cows responded better than low yielding cows (Sairanen et al., unpublished report) 5. Conclusions Moderate level of protein supplementation increased feed intake and milk production independently of forage type. Intake and production responses varied largely among cows. The responses of ECM and milk protein to protein supplementation were negatively related to calculated energy balance but poorly related to production level during the co variate period. However, ECM response was significantly related to DMI response, but DMI response was not related to any variables measured during the covariate period. Because MU during covariate period and MU responses to the changes in dietary CP concentration were poorly associated with intake or production responses, we suggest that using MU to rank cows for protein efficiency or responses to protein may be misleading. It is concluded that intake and production responses to moderate level of protein supplementation were highly variable, but the extent of variation could not be predicted from available animal char acteristics. More work is needed to examine whether the protein re sponses are repeatable across other types of basal diets and different number of lengths of time periods. CRediT authorship contribution statement A. Sairanen: Funding acquisition, Project administration, Data curation, Resources, Validation, Investigation, Writing – original draft. P. Huhtanen: Conceptualization, Methodology, Formal analysis, Su pervision, Validation, Writing – original draft. 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