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Record W2568990289

Energy and protein efficiency of lactating dairy cows fed ground peas, canola meal and rumen-protected amino acids

2016· article· en· W2568990289 on OpenAlexaboutno aff
Andre de Barros Duarte Pereira

Bibliographic record

VenueUniversity of New Hampshire Scholars Repository (University of New Hampshire at Manchester) · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsCanolaRumenMealAnimal scienceAgronomyFood scienceDairy cattleChemistryBiologyFermentation
DOInot available

Abstract

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Forages as conserved silage or grass cannot supply enough nutrients and energy as required by lactating dairy cows. As a result, supplementation with grains is needed to provide animals with enough nutrients to be healthy and produce milk being profitable (NRC, 2001). High producing cows need protein supplementation from sources other than forages in order to maximize milk protein production, with emphasis on replenishing requirements for specific amino acids. Excessive protein in the diet or deficiency of an essential amino acid can reduce productivity and increase excretion of N to the environment, causing pollution. Research must be conducted to help dairy farmers make informed decisions about the use of alternative protein supplements as a way to improve farm profitability, optimize protein and energy utilization and increase knowledge about environmental pollution. Therefore, strategies to reduce feed costs through sourcing lower-cost, yet high nutritional value feed ingredients, may optimize milk production enhancing the economic and social sustainability of dairy farming in the Northeast U.S. Therefore, the 2 research areas identified as the main focuses of this dissertation were: 1) development of a proof of concept technique to determine dry matter intake (DMI) for animals on pasture, and 2) improvement of economic and nutrient use efficiencies when feeding ground field peas (GFP), an alternative feedstuff, in order to decrease costs of dairy rations. In the first step, a proof of concept technique was developed to estimate energy requirements and DMI of lactating Holstein cows in a tie stall. The objective of this technique was to create a methodology to use spot short-term measurements of CH4 (QCH4) and CO2 (QCO2) integrated with backward dietary energy partition calculations to estimate DMI. Twelve multiparous cows averaging 173 ± 37 days in milk and 4 primiparous cows averaging 179 ± 27 days in milk were blocked by days in milk, parity, and DMI (as a percentage of body weight) and, within each block, randomly assigned to 1 of 2 treatments: ad libitum intake (AL) or restricted intake (RI = 90% DMI) according to a crossover design. Each experimental period lasted 22 d with 14 d for treatments adaptation and 8 d for data and sample collection. Diets contained (DM basis): 40% corn silage, 12% grass-legume haylage, and 48% concentrate. Spot short-term gas measurements were taken in 5-min sampling periods from 15 cows (1 cow refused sampling) using a portable automated open circuit gas quantification system (GreenFeed, C-Lock Inc., Rapid City, SD) with intervals of 12 h between the 2 daily samples. Sampling points were advanced 2 h from a day to the next to yield 16 gas samples/cow over 8 d to account for diurnal variation in QCH4 and QCO2. The following equations were used sequentially to estimate DMI: 1) Heat production (HP) (MJ/d) = (4.96 + 16.07 ÷ respiratory quotient) × QCO2; respiratory quotient = 0.95; 2) Metabolizable energy intake (MJ/d) = (heat production + milk-energy) ± tissue energy balance; 3) Digestible energy (DE) intake (MJ/d) = metabolizable energy + CH4-energy + urinary-energy; 4) Gross energy (GE) intake (MJ/d) = DE + [(DE ÷ in vitro true dry matter digestibility) – DE]; and 5) DMI (kg/d) = GE intake estimated ÷ diet GE concentration. Data were analyzed using the MIXED procedure of SAS and Fit Model procedure in JMP (α = 0.05). Cows significantly differed in measured DMI (23.8 vs. 22.4 kg/d for AL and RI, respectively; P < 0.01). Dry matter intake estimated using QCH4 and QCO2 coupled with dietary backward energy partition calculations (equations 1 to 5 above) was highest in cows fed for AL (22.5 vs. 20.2 kg/d). The resulting R2 were 0.28 between measured DMI and estimated by gaseous measurements and 0.36 between measured and DMI predicted by the NRC (2001). Results showed that spot short-term measurements of QCH4 and QCO2 coupled with dietary backward estimations of energy partitions underestimated DMI by 7.8%. However, the approach proposed herein was able to significantly discriminate differences in DMI between cows fed for AL or RI. The second focus of this dissertation was aimed to decrease feed costs while improving nutrient efficiency in dairy cows. Ground field peas are an adequate source of energy and protein compared to corn meal and soybean meal (SBM) that could be used as an alternative feedstuff in order to decrease feeding costs. Field peas are available for feed in the northern regions of the United States and Canada. Previous studies showed that diets with more than 25% GFP, DM basis) resulted in reduced milk and milk protein yield in dairy cows. Decreased yields may be caused by limited supplies of MP-Lys and MP-Met due to extensive degradation of GFP RDP in the rumen and we hypothesize that cows fed with GFP supplemented with RP Lys and RP Met will maintain performance when compared to a diet with corn meal and soybean meal supplemented with RP Lys and Met. The objective of this study was to compare a source of non-protein N (i.e. urea) vs. a source of soluble true protein (i.e. GFP) and evaluate diets with 25% of GFP supplemented with rumen-protected (RP) Lys (AjiPro-L, Ajinomoto, Japan) and Met (Smartamine-M, Adisseo, France) as a substitute for corn meal and SBM on animal performance and energy balance. Twelve multiparous and 4 primiparous lactating Holstein cows were blocked by days in milk, milk yield and parity, and randomly assigned to 1 of 4 diets in a replicated 4 × 4 Latin square design. Diets were 35.5% corn silage, 15.5% grass-legume haylage, 5.9% roasted soybean, and: (1) 36% corn meal and 1.3% urea (3.59:1 MP-Lys:MP-Met ratio; negative control (U), (2) 29.7% corn meal, 9.8% SBM, and RP-Lys RP-Met (3.07:1 MP-Lys:MP-Met ratio (CSAA), (3) 25% GFP, 12.3% corn meal, and 2.4% SBM (3.88:1 MP-Lys:MP-Met ratio; FP), and (4) 25% GFP, 12.2% corn meal, 2.4% SBM, and RP-Lys RP-Met (3.13:1 MP-Lys:MP-Met ratio; FPAA). Data were analyzed using the MIXED procedure of SAS with orthogonal contrasts for pairwise comparisons between treatments (α = 0.05). Dietary treatments had 15.4%, 15.1%, 14.9% and 15.0% CP, respectively for U, CSAA, FP and FPAA. As expected, cows fed U had decreased DMI (23.3 kg vs. 24.6 kg/d, P < 0.01), milk protein yield (1.15 kg vs. 1.21 kg/d, P < 0.001), total concentration of ruminal VFA (103 mM vs. 112 mM, P < 0.001), HP (129 MJ/d vs. 141 MJ/d, P < 0.001), NDF digestibility (30.2% vs. 46.0%, P < 0.01), ADF digestibility (37.6% 50.4%, P < 0.02), total purines derivatives (343 mmol/d vs 414 mmol/d, P < 0.01), and highest excretion of MUN (9.85 mg/dL vs. 9.09 mg/dL, P < 0.01) when compared to cows fed FP. Cows fed FP had decreased plasma concentration of Met (19.6 mM). Feeding cows CSAA and FPAA mitigated these negative responses. Cows fed FPAA had positive tissue energy balance, higher HP and consequently higher metabolizable energy intake when compared to CSAA diet. In addition, increased milk yield was correlated to a decrease in HP (R2 = 0.329, n = 16 observations). Results showed that feeding FPAA increased HP and milk protein yield to levels compared to cows fed CSAA. Results suggest that feeding diets with 25% GFP and RP-Lys and RP-Met will improve animal performance and energy efficiency. When cows were fed FPAA, a decrease in plasma His concentration was found compared to CSAA. Cows fed FPAA could, then, be limiting in His, which could have caused a decrease in milk protein production. Results from the literature show that feeding RP-Met can cause a decrease in the plasma concentration of EAA for reasons that still need to be studied. Canola meal is a good alternative to SBM that has potential to mitigate the effect on AA concentration in plasma. Previous studies reported increased plasma concentrations of most EAA when feeding CAM, mostly due to an increase in DMI, but research feeding GFP and CAM with RP Met have never been performed. The hypothesis of this study was that cows fed GFP with CAM and RP Met would have higher milk protein percentage and yield when compared to cows fed 25% GFP, SBM and RP Met due to an increase in DMI and consequent increase in plasma AA concentration. The objectives of this study were to compare lactating production responses of cows fed diets with (DM basis) 35.0% Corn silage, 14.0% grass-legume silage, 25% GFP, 1.5% citrus pulp, and corn meal, flaked corn and dry distillers grains in variable amounts with 1) SBM (11%) as the major source of supplemental protein, (FPSB diet), 2) CAM (13.5%) as the major source of supplemental protein (FPCM diet). For each experimental diet, RP Met was top dressed to half of the cows (27 g/d) to result in a total of 4 treatments: 1) FPSB diet with no RP Met supplemented, 2) FPSB diet with supplementation of RP Met, 3) FPCM diet with no RP Met supplemented and 4) FPCM diet with supplementation of RP Met. Twelve multiparous and 4 primiparous lactating Holstein cows were blocked by DIM, milk yield and parity, and randomly assigned to 1 of 4 diets in a replicated 4 × 4 Latin square design. Data were analyzed using the MIXED procedure of SAS and pairwise tests for protein source and supplementation or not of RP Met was performed (α = 0.05). Cows fed FPCM had higher DMI and milk yield when compared to cows fed FPSB. No effect on DMI and milk yield was observed for supplementation of RP Met. Cows produced milk with higher concentration of protein when supplemented with RP Met, but RP Met had no effect on milk protein yield. On the other hand, cows fed FPCM had higher yield of milk protein when compared to cows fed FPSB. No difference was found for milk fat and lactose concentrations between diets and addition of RP Met. Milk true N efficiency (Milk true N ÷ N intake) was higher and MUN was lower for cows fed FPCM compared to cows fed FPSB, showing that overall N efficiency of cows fed FPCM was better. Results show that CAM will increase N efficiency and increase milk and milk prote

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.180
Teacher spread0.160 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2016
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