雙低菜籽粕生長(zhǎng)豬凈能值測(cè)定及實(shí)驗(yàn)方法對(duì)能值的影響

J W Kim, B Koo, C M Nyachoti

翻譯：李平 校對(duì)： 上海亙泰實(shí)業(yè)集團(tuán)

本試驗(yàn)測(cè)定了雙低菜籽粕（CM）的消化能（DE）、代謝能（ME）和凈能（NE）含量，并且研究了基礎(chǔ)日糧[玉米日糧和玉米-豆粕（SBM）日糧]，及不同測(cè)定方法（替代法和回歸法）對(duì)雙低菜籽粕能值的影響。

將36頭生長(zhǎng)期去勢(shì)公豬（初始體重20.8±1.0kg）單獨(dú)飼養(yǎng)在代謝籠中，并隨機(jī)分配到6種日糧處理中，每個(gè)處理6個(gè)重復(fù)。6種試驗(yàn)日糧包括玉米日糧，玉米-豆粕日糧，含15％或30％雙低菜籽粕的玉米日糧，和含15％或30％雙低菜籽粕的玉米-豆粕日糧。雙低菜籽粕的DE、ME和NE由玉米日糧或玉米-豆粕日糧作為基礎(chǔ)日糧來(lái)測(cè)定。在每種基礎(chǔ)日糧中配制2種包含15％或30％雙低菜籽粕的日糧，以通過(guò)替代法和回歸法來(lái)測(cè)定和估算能值。飼喂水平設(shè)定為每天550 kcal ME/kg BW^0.6。豬飼喂試驗(yàn)日糧共16天，包括10天適應(yīng)期和6天全部糞便和尿液收集期。 然后將豬移入間接測(cè)熱室以測(cè)定24小時(shí)產(chǎn)熱量（HP），和12小時(shí)禁食產(chǎn)熱量。

無(wú)論采用何種基礎(chǔ)日糧，替代法測(cè)定雙低菜籽粕的DE、ME和NE均在回歸法測(cè)定DE、ME和NE估計(jì)的95％置信區(qū)間內(nèi)，這表明替代法和回歸法可以得出基本相同的雙低菜籽粕DE、ME和NE值。 然而，當(dāng)比較線性模型的擬合優(yōu)度時(shí)，玉米-豆粕日糧回歸分析的相關(guān)系數(shù)r²（0.78）相對(duì)于玉米日糧的（0.40）更高。根據(jù)玉米日糧和玉米-豆粕日糧做出的預(yù)測(cè)方程，所得到雙低菜籽粕的預(yù)測(cè)NE值分別為2,096 kcal/kg和1,960kcal/kg（飼喂基礎(chǔ)），而用替代法測(cè)定的NE值分別為2,233kcal/kg和2,106 kcal/kg（飼喂基礎(chǔ)）。

總之，在此次研究中測(cè)定的雙低菜籽粕的NE值平均為2,099 kcal/kg（飼喂基礎(chǔ)）。在生長(zhǎng)豬階段，使用替代法和回歸法來(lái)測(cè)定雙低菜籽粕的NE值，并沒(méi)有得出明顯不同的結(jié)果。雖然使用玉米日糧或玉米-豆粕日糧測(cè)定的雙低菜籽粕的NE值沒(méi)有差異，但玉米-豆粕日糧回歸分析的相關(guān)系數(shù)r²比玉米日糧中的r²值更大，這表明玉米-豆粕日糧是用于NE測(cè)定更合適的基礎(chǔ)日糧。

關(guān)鍵詞：雙低菜粕，產(chǎn)熱量，間接測(cè)熱，凈能，豬

Net energy content of canola meal fed to growing pigs and effect of experimental methodology on energy values

J W Kim, B Koo, C M Nyachoti

An experiment was conducted to determine the digestible energy (DE), metabolizable energy (ME), and netenergy (NE) contents of canola meal (CM) and to investigate the effects of basal diet [corn diet vs. corn-soybean meal (SBM) diet] and methodology (difference method vs. regression method) on energy values of CM. Thirty-six growing barrows (20.8 ± 1.0 kg initial body weight [BW]) were individually housed in metabolism crates and randomly allotted to one of six dietary treatments to give six replicates per treatment. The six experimental diets included a corn diet, a corn-SBM diet, a corn diet with 15 or 30% of CM, and acorn-SBM diet with 15 or 30% of CM. The DE, ME, and NE of CM were determined using the corn diet or the corn-SBM diet as a basal diet. In each basal diet, two additional diets containing 15 or 30% of CM were formulated to compare the determined energy values by the difference method and estimated energy values from the regression method. Feeding level was set at 550 kcal ME/kg BW^0.6 per day. Pigs were fed experimental diets for 16 d including 10 d for adaptation and 6 d for total collection of feces and urine. Pigs were then moved into indirect calorimetry chambers to determine 24 h heat production (HP) and 12 h fasting HP. The DE, ME, and NE of CM determined by the difference method were within the 95% confidence intervals estimated for the DE, ME, and NE of CM by the regression method regardless of the basal diets used, which indicates that the difference and regression methods give equivalent DE, ME, and NE of CM. However, when the goodness of fit for the linear model was compared, the r² of the regression analysis from the corn-SBM diet (0.78) was relatively greater than that from corn diet (0.40). The estimated NE of CM by the prediction equations generated by either the corndiet or corn-SBM diets were 2,096 kcal/kg and 1,960 kcal/kg (as-fed basis), respectively, whereas those values determined by the difference method were 2,233 kcal/kg and 2,106 kcal/kg (as-fed basis), respectively. In conclusion,the NE of CM determined in the current study was, on average, 2,099 kcal/kg (as-fed basis). The difference and regression methods do not give different NE value of CM fed to growing pigs. Although the NE values of CM determined using either the corn diet or the corn-SBM diet were not different, the greater r² of the regression analysis from the corn-SBM diet than that from the corn diet suggests that the corn-SBM diet is a more appropriate basal diet for NE determination of ingredients.

Key words: canola meal, heat production, indirectcalorimetry, net energy, pig