Overview of Recent AA Work in Growing Pigs

A.B. Clark1*, M.D. Tokach1, S.S. Dritz1, K.J. Touchette2, J.M. DeRouchey1, R.D. Goodband1, and J.C. Woodworth1

1Kansas State University, Manhattan, 2Ajinomoto Heartland, Inc., Chicago, IL.

Background

• Inclusion of synthetic amino acids allows producers to meet specific requirements while reducing both diet cost by replacing specialty protein sources.

Current literature lacks:

Research where pigs were fed below their lysine requirement

The application of best-fitting nonlinear statistical models

Objective

To determine the SID Lys, Val:Lys, and Ile:Lys

requirement for 7 to 11 kg nursery pigs

using best-fitting mixed models.

Lysine

300 nursery pigs (PIC 327 × 1050, 21 d of age, 6.7 initial BW)

6 d on a common starter diet Pens allotted to treatments in a completely

randomized design 6.7 kg initial BW 10 replications/treatment 5 pigs/pen

Materials and Methods, Lys Exp.

6 treatment diets increasing in SID Lys: 1.10, 1.20, 1.30, 1.40, 1.50, and 1.60 % SID Lys NRC requirement – 1.35%, PIC – 1.46% Diets for 1.10 and 1.60% SID Lys manufactured

and blended at feed mill All diets were fed in meal form. With increasing Lys level, soybean meal was

replaced with crystalline amino acids and corn

NRC, 2012. PIC Nutrient Specifications Manual, 2016.

Pigs were fed treatment diets for 14 d, followed by a common diet for 14 d.

Pigs were weighed on d 0, 7, 14, 21, and 28 to determine ADG, ADFI, and G:F.

Each pen (1.2 × 1.5 m) contained a 4-hole dry, self-feeder and a nipple waterer for ad libitumaccess to feed and water.

Materials and Methods, Lys Exp.

PROC GLIMMIX in SAS (SAS Institute, Inc., Cary, NC) Experimental unit: pen Results considered significant at P ≤ 0.05 and

tendencies between P > 0.05 and P ≤ 0.10. Models evaluated: Quadratic (QP), broken-line linear (BLL), and

broken-line quadratic (BLQ) A lower Bayesian Information Criterion (BIC)

indicated a better fit. A decrease in BIC greater than 2.0 among models

for a particular response criterion was considered an improved fit.

Statistical Analysis, Lys Exp.

Gonçalves et al. (2016)

Lys Results, Experimental Period

SID Lys, % P <Item 1.10 1.20 1.30 1.40 1.50 1.60 SEM Lin Quadd 0 to 141

ADG, g 265 263 298 313 319 320 10.1 0.001 0.278ADFI, g 432 417 446 438 441 442 14.6 0.336 0.835G:F 0.616 0.631 0.670 0.714 0.725 0.729 0.0173 0.001 0.273F/G 1.64 1.60 1.50 1.40 1.39 1.38 0.040 0.001 0.136

1BW ≈ 6.7 to 10.8

Modeling Results: ADG (d 0 to 14; 6.7 to 10.8 kg BW) Best Fit: BLL and QP Model

BLL Breakpoint: 1.45% [95% CI:1.31, 1.58% ]QP Maximum: >1.60%, 95% of Max: 1.43

Modeling Results: G:F (d 0 to 14; 6.7 to 10.8 kg BW) Best Fit: BLL and QP Model

BLL Breakpoint: 1.45% [95% CI:1.35, 1.54% ]QP Maximum: >1.60%, 95% of Max: 1.43

Valine

280 nursery pigs (PIC 327 × 1050, 21 d of age) 5 d on a common starter diet Pens were allotted to treatments according to BW

in a randomized complete block design. 7 treatment diets increasing in SID Val:Lys 50, 57, 63, 68, 73, 78, 85

1.24% SID Lys NRC requirement – 64%, PIC – 67% SID Val:Lys

Val experimental period performance

SID Val:Lys, % P <Item 50 57 63 68 73 78 85 SEM Lin Quadd 0 to 141

ADG, g 190 221 249 249 248 251 238 11.2 0.001 0.001ADFI, g 331 363 394 388 403 390 386 17.2 0.012 0.030G:F 0.579 0.612 0.635 0.646 0.614 0.645 0.617 0.0189 0.101 0.039F/G 1.74 1.65 1.60 1.56 1.63 1.56 1.64 0.050 0.084 0.036

1BW ≈ 6.5 to 9.8

Modeling Results: ADG (d 0 to 14; 6.5 to 9.8 kg BW)

Best Fit: Broken-Line Linear ModelBreakpoint: 62.9% SID Val:Lys

Modeling Results: ADFI (d 0 to 14; 6.5 to 9.8 kg BW)

Best Fit: QP ModelMaximum: 73.7% SID Val:Lys, 99% of Max: 68.0%

Modeling Results: G:F (d 0 to 14; 6.5 to 9.8 kg BW) Best Fit: Quadratic Polynomial Model

Max Performance: 71.7% SID Val:Lys, 99% of Max: 64.4%

Isoleucine

280 nursery pigs (PIC 327 × 1050, 21 d of age) 6 d on a common starter diet 12 d on experimental diets Pens allotted to treatments according to BW/location in

a randomized complete block design 7 treatment diets increasing in SID Ile:Lys 40, 44, 48, 52, 54, 58, 63

NRC requirement – 52%, PIC – 55%

Ile experimental period performance

SID Ile:Lys, % P <Item 40 44 48 52 54 58 63 SEM Lin Quadd 0 to 121

ADG, g 330 344 342 388 344 358 375 11.3 0.001 0.446ADFI, g 495 524 546 601 522 574 555 16.6 0.002 0.017G:F 0.669 0.657 0.628 0.648 0.658 0.625 0.676 0.0152 0.900 0.041F/G 1.50 1.53 1.60 1.55 1.52 1.61 1.49 0.037 0.812 0.059

1BW ≈ 6.8 to 11.0

Modeling Results: ADG (d 0 to 14; 6.8 to 11.0 kg BW) Best Fit: QP, BLL and BLQ Models

BLL Breakpoint: 52.0% [95% CI:51.96, 52.04 % ]BLQ Breakpoint: 52.0%, [95% CI:51.97, 52.03]

QP Maximum: 64.7%, 99% of Max: 57.0

Modeling Results: ADFI (d 0 to 14; 6.8 to 11.0 kg BW) Best Fit: QP and BLL Model

QP Maximum: 56.2 % SID Ile:Lys, 99% of Max: 51.6%BLL Breakpoint: 50.6% SID Ile:Lys, [41.99, 59.15%]

Summary Results heavily dependent on the model and criteria

evaluated

SID Lys – 1.45 to 1.60%

SID Val:Lys – 62.9 to 71.7%

SID Ile:Lys – 52.0 to 64.7%

Consider maximum of response vs 95 or 99% of max

Generating response surfaces allows producers to make decisions based on ingredient nutrient composition, availability, and economics

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