The inclusion of vegetable fat in the diet of lactating cows is a practice usually recommended to increase the energy density of diets, so as to increase production and promote beneficial manipulation of milk composition (Palmquist and Jenkins, Reference Palmquist and Jenkins2017). Furthermore, fat supplementation allows reduction of the caloric increment, and has been one of the nutritional strategies used to reduce heat stress in lactating cows, especially in hot climate regions. Another important factor made possible by the addition of fat in the diet of ruminants is the reduction of enteric methane production (Chagas et al., Reference Chagas, Ramin, Exposito, Smidt and Krizsan2021). This is very desirable, since dairy cows can produce around 630 liters of methane per day depending on diet composition, food intake and digestibility (Hristov et al., Reference Hristov, Kebreab, Niu, Oh, Bannink, Bayat, Boland, Brito, Casper, Crompton, Dijkstra, Eugène, Garnsworthy, Haque, Hellwing, Huhtanen, Kreuzer, Kuhla, Lund, Madsen, Martin, Moate, Muetzel, Munoz, Peiren, Powell, Reynolds, Schwarm, Shingfield, Storlien, Weisbjerg, Yanez-Ruiz and Yu2018). Moreover, the addition of lipids to ruminant diets also has an effect on nitrogen (N) metabolism (Munõz et al., Reference Muñoz, Sánchez, Peralta, Espíndola, Yand, Moralesa and Ungerfelde2019) and these responses may vary according to the level of inclusion, fatty acid (FA) profile and lipid source (oils or oilseeds), as well as the roughage used in the diet (Knapp et al., Reference Knapp, Laur, Vadas, Weiss and Tricarico2014).
The increasing cost of ground corn (GC) in recent years has stimulated the search for alternative energy sources in diets for lactating cows. Furthermore, due to the higher occurrence of heat stress in warm climate regions, a significant reduction in feed intake in dairy cows results in negative energy balance, during which GC supply may not meet lactation needs. The partial replacement of GC by economical sources of fat and more practical use in the diets of dairy cows represents a potential alternative to help overcome these problems.
We hypothesized that the inclusion of full fat corn germ (FFCG) as a partial replacement for GC would not alter the performance of lactating cows but would reduce the predicted methane production in vivo. The objective was to evaluate the effects of replacing GC by FFCG on the intake and digestibility of nutrients, efficiency of N utilization and production of milk and its components. Additionally, the objective was to evaluate the in vivo predicted methane production and rumen fermentation parameters using a fully automated in vitro gas production technique.
Material and methods
Two experiments were conducted for the development of this work. The first (Test I) evaluated the performance of Holstein cows in the field submitted to experimental diets with five levels of replacement of GC by FFCG. The second (Test II) was an in vitro gas production experiment in a fully automated system. For the in vitro gas production assay, three incubations were performed in order to evaluate and predict the in vivo methane production from the experimental diets used in Test I. The tests are described separately in this section.
Test I: animal care and experiment location
The procedures involving animals were carried out in accordance with the guidelines of the Ethics Committee on the Use of Animals (ECUA) of the Universidade Federal Rural de Pernambuco (License n° 143/2019). The experiment was carried out at the Experimental Station of the Instituto Agronômico de Pernambuco (IPA), located in the municipality of São Bento do Una (Pernambuco, Brazil).
Test I: animals, experimental design and dietary treatments
Ten multiparous Holstein cows with 90 ± 10 d in milk and yielding 24.2 ± 3.5 (mean ± sd) kg of milk/d were used in the study. The cows were housed in individual pens of 24 m2 equipped with feed bins and water troughs and were randomly assigned to five dietary treatments in a replicated 5 × 5 Latin square design with 21-d experimental periods (14 d for adaptation to diets and the last 7 d for sampling and data collection). Diets consisted of different levels of GC replaced by FFCG (0; 25; 50; 75 and 100%) based on DM (online Supplementary File, Table S2). The FFCG was obtained by wet milling of corn, where the germ is separated by density, resulting in a high fat co-product with high oxidative stability (IngredionTM). The chemical composition of forages and concentrates used in the experimental diets is presented in the online Supplementary File (Table S1), while the proportion of ingredients and chemical composition of the diets are shown in Table S2. Diets were formulated to meet energy and nutrient requirements of dairy cows producing 25 kg/d of fat-corrected milk according to NRC (2001) and were fed ad libitum twice daily after morning and afternoon milking as a total mixed ration (TMR). The amount of TMR provided to each cow was adjusted daily to allow for 5 to 10% of refusals.
Test I: sampling and data collection
Individual feed intake was recorded daily by subtracting the amount of refusals from the amount of feed offered. From the 15th to the 21st day of each experimental period, samples of feed ingredients and refusals were collected daily. Composite samples per period (for feed ingredients) and per cow per period (for refusals) were formed and stored in plastic bags at −20°C for subsequent chemical analyses. To estimate the apparent digestibility, fecal samples were collected directly from the rectal ampoule of the animals, once a day, between the 16th and 20th days of each experimental period, at 6 : 00, 8 : 00, 10 : 00, 12 : 00 and 14 : 00, respectively (Detmann et al., Reference Detmann, Souza and Valadares Filho2012). Then, the samples were composed and homogenized by animal and period. On the last day of each experimental period, four hours after morning feeding, spot urine samples were collected from all cows during urination for quantification of allantoin, nitrogen, uric acid and creatinine concentrations.
The cows were milked twice a day (6 : 00 a.m. and 3 : 00 p.m.) and milk production was recorded between the 15th and 21th days of each trial period. On the 18th and 19th day of each experimental period, composite milk samples from morning and afternoon milking were collected in 50-ml flasks containing Bronopol® as a preservative and analyzed for protein, fat, lactose and total solids content. Another 10 ml aliquot of milk was deproteinized with 5-ml of trichloroacetic acid (25%), filtered and stored at −20°C for allantoin analysis.
Test I: analytical procedures
Samples of feed ingredients, refusals and feces were thawed, pre-dried at 55°C for 72 h in a forced ventilation oven, ground to 1 mm in a knife mill (Model Thomas Wiley Co., Swedesboro, NJ) and analyzed for DM (method 934.01), organic matter (OM, method 930.05), ash (method 942.05), crude protein (CP, method 968.06) and ether extract (EE, method 920.39) according to AOAC (2005). Neutral detergent fiber (NDF) was determined according to Mertens (Reference Mertens2002) using a heat-stable alpha-amylase without sodium sulphite and corrected for residual ash. The NDF value was also corrected for non-protein nitrogenous compounds as described by Licitra et al. (Reference Licitra, Hernandez and Van Soest1996).
The total fecal excretion was estimated using indigestible neutral detergent fiber as an internal marker and the feces, feed and orts contents of the marker were obtained after 288 h of ruminal incubation (Detmann et al., Reference Detmann, Souza and Valadares Filho2012). Uric acid and creatinine analyzes were performed at the Clinical Pathology Laboratory of the Department of Veterinary Medicine at UFRPE using commercial kits (LABTEST®), and the reading was performed on a semi-automatic biochemical analyzer (Labtest Diagnóstica, Lagoa Santa, Brazil). Urine allantoin analyses were performed using the colorimetric method (Chen and Gomes, Reference Chen and Gomes1992). Urine nitrogen assessment was performed by the Kjeldahl distillation method according to INCT-CA method no. N-001/1 (Detmann et al., Reference Detmann, Souza and Valadares Filho2012).
The concentration of fat, protein, lactose and total solids in milk were analyzed by mid-infrared spectrometry (Bentley Instruments, Bentley FTS, Chaska, MN, USA) according to the International Dairy Federation protocols for whole milk samples (ISO 9622/IDF 141, 2013).
Test I: calculations
Non-fiber carbohydrates were calculated according to Detmann et al. (Reference Detmann, Souza and Valadares Filho2012). The diets' TDN content and its conversion in lactation net energy (NEl) were estimated according to NRC (2001). Daily total urinary volume was estimated as described by Valadares et al. (Reference Valadares, Broderick, Valadares Filho and Clayton1999). The daily urinary excretion of creatinine was based on 24.05 mg/kg of BW of creatinine (Chizzotti et al., Reference Chizzotti, Valadares Filho, Valadares, Chizzotti and Thedeschi2008). The microbial protein synthesis was estimated according to Chen and Gomes (Reference Chen and Gomes1992), Verbic et al. (Reference Verbic, Chen, Macleod and Orskov1990) and Gonzalez-Ronquillo et al. (Reference González-Ronquillo, Balcells, Guada and Vicente2003). The milk N was quantified using milk total protein (MTP/6.38) and the allantoin in milk was quantified using the colorimetric method described by Chen and Gomes (Reference Chen and Gomes1992). The nitrogen balance was obtained by calculating the difference between total nitrogen intake and nitrogen excreted in feces (N-feces), urine (N-urine) and milk (N-milk). The milk yield corrected for energy (ECMY) was estimated based on Tyrrel and Reid (Reference Tyrrel and Reid1965).
Test II: In vitro incubations
The in vivo methane production was estimated from an in vitro assay based on a fully automated gas production system and using kinetic parameters estimated by a mechanistic dynamics rumen model developed by Ramin and Huhtanen (Reference Ramin and Huhtanen2012). The in vitro assay was performed at the Swedish University of Agricultural Sciences, Umeå, Sweden. Three 48-hour incubations were performed. The rumen fluid used in the incubations was obtained from two lactating Swedish Red cows fed a diet composed of 60% roughage and 40% concentrate. The animal handling for this trial was approved by the Swedish Ethics Committee on Experimental Animals (Dnr A 32–16). The rumen fluid (average pH 6.3) was collected individually from each cow via cannula, filtered through cheesecloth in two layers, and placed in preheated thermos bottles previously treated with CO2. Similar proportions of the rumen fluid were added to a mineral buffer solution added to PeptoneTM (pancreatic digested casein; Merck, Darmstadt, Germany) according to the methodology described by Menke and Steingass (Reference Menke and Steingass1988).
All diets tested had three replicates (one in each incubation). Also, all incubations included blank bottles for corrections of total gas and methane production. The diets were randomly distributed in the bottles between the three incubations, avoiding repetition of the diets in gas reading channels. Thus, bottles and incubations were added to the statistical model.
Test II: evaluation of pH and ruminal ammoniacal nitrogen
The ruminal pH was measured at the end of the incubations (48 h) as well as the collection of ruminal fluid samples (0.6 ml) from the bottles. The rumen fluid samples were immediately stored at −20°C until the ammonia nitrogen (NH3-N) analysis. The NH3-N concentration was quantified by the colorimetric method described by Chaney and Marbach (Reference Chaney and Marbach1962) using AutoAnalyzer 3 (SEAL Analytical Ltd., Mequon, WI, USA).
Test II: evaluation of in vitro gas production and sampling
The gas production system (Gas Production Recorder, GPR-2, Version 1.0 2015, Wageningen UR) was set to take readings every 12 min and corrected for normal air pressure conditions (101.3 kPa). The in vitro CH4 measurement was performed according to Ramin and Huhtanen (Reference Ramin and Huhtanen2012), in which gas samples were collected during the incubation period (0.2 ml) for each bottle at 2, 4, 8, 24, and 48 h. The CH4 concentration was determined with a gas chromatograph (Varian Star 3400 CX, Varian Analytical Instruments, Walnut Creek, CA, USA) equipped with a thermal conductivity detector.
Test II: calculations and prediction of methane production in vivo
The predicted in vivo methane production was calculated as described by Ramin and Huhtanen (Reference Ramin and Huhtanen2012). The predicted in vivo methane production can be expressed in g/kg DM: CH4 (g/kg DM) = CH4 (L of CH4/kg of DM intake) × 1 (L)/22.4 (l/mol) × 16.04 (g/mol), where 22.4 is the volume of gas and 16.04 is the molar mass of CH4. The total daily methane production in grams was then estimated from DM intake (data obtained in Test I, total of 32 observations) × CH4 production (data obtained in Test II, mean value of methane production for each experimental diet; Table 1). Finally, the methane intensity (g of CH4/kg of ECMY) was calculated by the daily methane production (values obtained from the two tests)/ ECMY (data obtained from Test II).
Table 1. In vitro ruminal fermentation parameters and predicted in vivo CH4 production measured from 48 h of incubation
a Orthogonal polynomial contrasts testing linear (L), and quadratic (Qd), cubic (C), and quartic (Qt) responses to levels of GC replacement for FFCG in diets.
b CH4 production predicted in vivo (g/kg DM) × daily dry matter intake for the respective experimental diets.
c In vivo predicted CH4 production (g/kg DM)/energy corrected milk production.
Statistical analysis
Data generated in Test I were analyzed using the PROC GLIMMIX of SAS (SAS, 2012) according to 5 × 5 Latin square design balanced for carryover effects, using the following model:
$$Y_{ijkl} = \mu + T_i + Q_j + P_k + ( {A/Q} ) _{lj} + ( {T\ast Q} ) _{ij} + \varepsilon _{ijkl}$$where: Yijkl = dependent variable ijkl; μ = overall average; Ti = fixed treatment effect i; Qj = fixed square effect j; Pk = random period effect k; (A/Q)lj = random effect of animal l in the square j; T*Qij, = effect of the interaction treatment i and square j; εijk ~ N(0,σ2e) = random residual error.
The data regarding trial II were analyzed through the model:
$$Y_{ijk} = \mu + T_i + I_j + G_k + \varepsilon _{ijk, }$$where: Yijk = dependent variable ijk; μ = overall average; Ti = treatment i; Ij = incubation j; Gk = bottle k; and εijk ~ N(0,σ2e) random residual error. All polynomial contrast effects of increasing dietary FFCG levels were tested by orthogonal polynomial contrasts. We assumed significant effects when α ≤ 0.05. Whenever the quadratic effect for a given response variable was significant (P < 0.05), the maximum or minimum points of the quadratic function were estimated by calculating the derivative of the mathematic function, where y’ = α2 + bα + c = 0.
Results
Intake and apparent digestibility of nutrients
With the exception of the intake of EE, which increased, the intake of all nutrients decreased linearly (P < 0.01) with the replacement of GC by FFCG. The digestibility of DM, OM and NDF reduced, while the digestibility of EE increased linearly (P ≤ 0.01) with the replacement of GC by FFCG. There were no changes in the digestibility of CP (P ≥ 0.94) (Table 2).
Table 2. Intake and digestibility of nutrients
a Orthogonal polynomial contrasts testing linear (L), and quadratic (Qd), cubic (C), and quartic (Qt) responses to levels of GC replacement for FFCG in diets.
Nitrogen balance and efficiency, microbial protein synthesis and efficiency and milk production
The N intake and daily N excretion in urine and feces decreased, while N use efficiency increased linearly (P ≤ 0.03) with the replacement of GC by FFCG. The N excreted in milk showed a quadratic response with an estimated maximum excretion of 125 g/d with 45.2% replacement of GC by FFCG. There was no significant effect (P > 0.05) of the diets on N balance, microbial protein synthesis and efficiency (Table 3).
Table 3. Nitrogen balance and efficiency, microbial protein synthesis and efficiency
a Orthogonal polynomial contrasts testing linear (L), and quadratic (Qd), cubic (C), and quartic (Qt) responses to levels of GC replacement for FFCG in diets.
b N-milk/N-Intake.
Milk production and composition
Maximum milk production was estimated at 25.5 kg/d with 48.8% replacement of GC by FFCG (Table 4). The yield of protein, lactose and total solids in milk showed a quadratic behavior (P ≤ 0.03), with estimated maximum production of 797, 1189 and 2990 g/d with 44.1, 44.9 and 23.3% of replacement of GC by FFCG, respectively. On the other hand, milk fat yield and ECMY decreased linearly (P < 0.01) with replacement of GC by FFCG.
Table 4. Milk production and composition
a Orthogonal polynomial contrasts testing linear (L), and quadratic (Qd), cubic (C), and quartic (Qt) responses to levels of GC replacement for FFCG in diets.
Test II
Fermentation parameters and predicted in vivo CH4 production
There was no effect (P ≥ 0.05) of the replacement of GC by FFCG on pH or NH3-N, with observed mean pH values of 6.22 and NH3-N of 33.1 mg/dl (Table 1). The production of CH4 (g/kg DM) decreased linearly (P < 0.01) with the replacement of GC by FFCG. When the data from the in vitro study (Test II) were combined with the data from the in vivo study (Test I), it was possible to express the total production of CH4 (g/d), as well as to estimate the intensity of CH4 expressed in grams of CH4 emitted per kg of milk corrected for energy produced. The total CH4 (g/d) and CH4 intensity decreased linearly (P < 0.01) with the replacement of GC by FFCG.
Discussion
Test I: intake and apparent digestibility of nutrients
As expected, the fat content of the diets increased with the inclusion of FFCG (online Supplementary Table S2). This explains the significant increase in EE intake when compared to diets with 0 and 100% FFCG. Possibly, high fat intake reduced DM intake (DMI) through satiety signals that decrease the duration or frequency of meals (Harvatine and Allen, Reference Harvatine and Allen2005), as well as through lower nutrient digestibility (DM, OM NDF), leading to an increase in the retention time of food particles in the rumen (Jenkins and Harvatine, Reference Jenkins and Harvatine2014). As a consequence of the lower DMI, the intake of OM, CP and NDF, as well as net energy required for lactation were also linearly reduced in response to the inclusion of FFCG.
The high intake of dietary fat may also explain the reduction in apparent digestibility of DM, OM and NDF (Table 1). When consumed in excess, fat adheres to food particles, making it difficult for bacteria to adhere, especially cellulolytic bacteria, which allows lower activity of the enzymes involved in cellulose hydrolysis and reduces the digestion of the fibrous fraction. Polyunsaturated fatty acid (PUFA) sources have a more negative effect on rumen fermentation compared to calcium salts and hydrogenated fats (NRC, 2001). This is attributed to possible differences in the effects on microbial populations, as PUFA are known to have a toxic effect on some species of rumen bacteria, especially cellulolytic ones (Mao et al., Reference Mao, Wang, Zhou and Liu2010).
Nitrogen balance and efficiency, microbial protein synthesis and efficiency, and milk production
All diets showed positive N balance. The N in milk reflects the response pattern observed for the yield of CP in milk. High fat intake may decrease N concentrations arriving in the rumen environment, but duodenal nitrogen flux to milk may remain unchanged (Doreau and Ferlay, Reference Doreau and Ferlay1995). These results were sufficient to linearly increase the N utilization efficiency in response to the replacement of GC by FFCG. Protein metabolism in rumen was probably not impaired, since the synthesis and efficiency of microbial protein synthesis were not altered by the substitution of GC by FFCG. The requirement for degradable protein in the rumen is often a function of microbial growth, and this increases as a function of the amount of fermentable carbohydrate in the rumen.
With the replacement of GC by FFCG, there was a reduction in the amount of readily fermentable carbohydrates reaching the rumen and an increase in the amount of fat, which is not digested by microorganisms. Thus, it is suggested that the inclusion of FFCG in the diets promoted a lower need for use of nitrogen compounds.
Milk production and composition
The initial increase in milk production observed until the replacement of 48.8% of GC by FFCG may, at least in part, be explained by the reduction in milk fat content observed in cows fed increasing FFCG levels, since about 50% of net energy for lactation is used to support milk fat synthesis (Palmquist and Jenkins, Reference Palmquist and Jenkins2017). As suggested elsewhere (Boerman and Lock, Reference Boerman and Lock2014), during milk fat depression (MFD) the mammary gland may divert energy spared with the diminished fat synthesis to increase protein, lactose and milk yields. The inhibition of de novo lipogenesis in the mammary gland of cows exhibiting MFD is expected to reduce the demand for NADPH produced via the phosphate pentose pathway, thereby sparing glucose for lactose synthesis (Bauman et al., Reference Bauman, Harvatine and Lock2011), which ultimately determines the amount of absorbed water in the alveoli and thus the volume of milk produced (Costa et al., Reference Costa, López-Villalobos, Sneddon, Shalloo, Franzoi, Marchi and Penasa2019). The reduction in milk production when higher levels of FFCG were added to the diet could be attributed to the harmful effects of excessive fat intake, as discussed earlier.
The reduction in ECMY with the replacement of GC by FFCG can be attributed to the harmful effects of excessive fat intake on nutrient intake and digestibility, and is mainly due to the marked decrease in milk fat yield, which dropped from 824 to 525 g/d in cows fed 0 and 100% replacement of GC by FFCG, respectively. In general, MFD occurs when cows are fed low fiber/high starch diets supplemented with oils, or when marine lipids are added to the diet (Bauman et al., Reference Bauman, Harvatine and Lock2011). The NDF content of experimental diets used in the present study varied between 27.3 and 29.1% DM, which is above the minimum levels recommended by the NRC (2001). However, nearly one-third of dietary NDF was provided by cactus cladodes, a NDF source of low physical effectiveness (Conceição et al., Reference Conceição, Ferreira, Campos, Silva, Detmann, Siqueira, Barros and Costa2016). Thus, the basal diet provided in our study may not have been able to promote sufficient rumination to maintain an adequate rumen environment, resulting in MFD when FFCG was included in the diet. The inclusion of FFCG possibly favored changes in ruminal biohydrogenation pathways, allowing greater ruminal flow of certain intermediates to the mammary gland, such as trans-10.18 : 1 and trans-10, cis-12 CLA, both with potential to induce MFD (Baumgard et al., Reference Baumgard, Corl, Dwyer, Saebø and Bauman2000). Miller et al. (Reference Miller, Shirley, Titgemeyer and Brouk2009) observed a reduction in milk fat content of cows fed 1.6% of supplemental fat from FFCG as compared to an equal amount of lipid from whole cottonseed and in relation to control diet (no lipid supplement), suggesting that lipids in FFCG are more prone to generate anti-lipogenic biohydrogenation intermediates.
Test II: pH and ammoniacal nitrogen
The absence of changes in pH of the incubated material in response to FFCG supplementation was similar to other studies that evaluated the inclusion of vegetable oils in ruminant diets in vitro (Vargas et al., Reference Vargas, Andrés, López-Ferreras, Snelling, Yáñez-Ruíz, Garcia-Estrada and López2020) and in vivo (Chagas et al., Reference Chagas, Ramin, Exposito, Smidt and Krizsan2021). Because in vitro systems are highly buffered, they are less sensitive to changes in pH in response to dietary manipulation when compared to in vivo assessments (Jonker et al., Reference Jonker, Lowe, Kittelmann, Janssen, Ledgard and Pacheco2016). Ammonia nitrogen was not altered by the replacement of GC by FFCG, possibly because the diets had similar levels of CP (online Supplementary Table S2). The in vitro results from Test II are in alignment with the in vivo results from Test I, with respect to protein digestibility and microbial protein production that were not altered.
In vivo predicted methane production
Total daily production of CH4 was estimated at 432 g/d for the diet with 0% FFCG inclusion. Also, DMI and in vivo predicted methane production were 18.9 kg/d (Table 1) and 22.9 g/kg DM (Table 4) for cows in this treatment. Total CH4 production (g/d) decreased as higher levels of FFCG were included in the diets. This result was more evident from the diet with 50% replacement of GC by FFCG (5.3% of total fat), resulting in a reduction of up to 28% of daily CH4 (g/d) for the diet with 100% replacement of GC by FFCG (9% total fat). Furthermore, the CH4 intensity (g CH4/kg ECMY) was also reduced proportionally according to the observed reductions in ECMY (Table 3) and in the predicted in vivo CH4 production as a function of the replacement of GC by FFCG.
The results observed for methane production may initially be associated with the fact that the replacement of GC by FFCG decreased fermentable substrates in the rumen, since the long-chain fatty acids present in FFCG are not fermentable (Knapp et al., Reference Knapp, Laur, Vadas, Weiss and Tricarico2014), and this reduces the excess hydrogen needed for methanogenesis. Moreover, responses from Test I show that the replacement of GC by FFCG reduced the digestibility of DM, NDF and OM. The estimated CH4 production indicates that the increase in fat levels provided by FFCG supplementation can be used as a strategy to reduce enteric CH4, thus corroborating other studies reported in the literature, both in vitro (Vargas et al., Reference Vargas, Andrés, López-Ferreras, Snelling, Yáñez-Ruíz, Garcia-Estrada and López2020) and in vivo (Chagas et al., Reference Chagas, Ramin, Exposito, Smidt and Krizsan2021).
To the best of our knowledge, this is the first study to investigate the effects of various levels of FFCG, a high-lipid co-product of corn, on performance and enteric CH4 production of dairy cows fed cactus cladodes and sugarcane as forage sources. Our results bring innovative data on the use of FFCG from nutritional and productive aspects. The results reinforce the possibility of using in vitro techniques to access predictive values of enteric CH4 production. However, more studies need to be conducted in order to validate in vitro data for tropical conditions.
In conclusion, full-fat corn germ has been shown to be an effective source of fat to reduce methane production in dairy cows, partially supporting our initial hypothesis. However, as it decreases milk fat production, it is not recommended to replace more than 50% of GC with FFCG for lactating cows fed cactus cladodes and sugarcane.
Supplementary material
The supplementary material for this article can be found at https://doi.org/10.1017/S0022029923000201.
Acknowledgments
The authors thank the Pernambuco State Science and Technology Foundation (FACEPE) for granting a postgraduate scholarship (DOCTORATE DEGREE), and Ingredion Incorporated for providing the FFCG with no restrictions placed on this publication, hence no conflict of interest.
