Glycerin is a by-product from biodiesel production, an important alternative fuel. It is also a low-cost source of carbohydrates. This study was conducted to determine the optimal amount of glycerin to include in the diets of lambs. Forty-four crossbreed male lambs (23.9 ± 3.4Kg) were distributed in a completely randomized design, and fed with a TMR that contained 50% Cynodon sp. chopped hay and 50% concentrate composed of corn bran, soybean meal, mineral premix, and the amounts of glycerin: 0; 7; 14 and 21% of total DM. Treatments varied in the amount of glycerin included. During the performance trial the animals were fed ad libitum (diet was offered to allow 10% of orts). The feed and orts were weighed daily. The feedlot trial lasted 78 d, and on the last day the animals were weighed, submitted to feed fasting, and slaughtered. A general linear model was used to perform linear and quadratic regression. Significance was declared as P < 0.05. The glycerin inclusion promoted increase in final BW, BW gain, and gain:feed ratio up to 5.8, 3.8, and 2.75% of inclusion respectively (Table 1). After that, glycerin inclusion reduced those parameters. The initial increase can be related to the increment on energy intake, because the glycerin used in this study contained 30% of lipids. However, the increase in lipid intake can also reduce fiber digestibility, and then cause decrease in the DM intake, which is related to reduction in productive performance parameters. Glycerin, from biodiesel production, can be added between amounts of 2.75% and 5.8% without compromising the productive performance of lambs. Table1. Productive performance of lambs fed diets containing glycerin from biodiesel production

Item	Glycerin amount (%DM)				SEM	P-value
0	7	14	21	Lin	Quad
Final BW, kg	37.87	40.45	35.98	32.26	1.21	<0.001	0.00071
BW Gain, kg	14.91	15.58	12.34	8.00	0.65	<0.001	0.00072
ADG, g/d	191.24	199.83	158.28	102.62	0.85	<0.001	0.00073
Gain:Feed	0.155	0.149	0.141	0.102	0.01	<0.0001	0.0254

¹Y = −0.0321X² + 0.3707X + 38.26. ²Y = −0.0256X² + 0.1944X + 15.051. ³Y = −0.3278X² + 2.4924X + 193.04. ⁴Y = −0.0002X² + 0.0011X + 0.1541.