动物营养学报 >

2024 , Vol. 36 >Issue 11: 7003 - 7014

DOI: https://doi.org/10.12418/CJAN2024.597

研究论文

湘黄鸡生长及体成分沉积规律研究

  • 陈凯 , 1 ,
  • 张旭 2, * ,
  • 吴聪 1 ,
  • 罗志嘉 1 ,
  • 文野 3 ,
  • 谭智阳 2 ,
  • 张慧 2 ,
  • 马玉勇 , 1, ** ,
  • 戴求仲 2
展开
  • 1 衡阳市农业科学院,衡阳 421001
  • 2 湖南省畜牧水产研究所,长沙 410128
  • 3 湖南环境生物职业技术学院,衡阳 421005
** 马玉勇,畜牧师,E-mail:

* 同等贡献作者

陈 凯(1996—),男,湖南湘乡人,硕士,从事家禽营养与家禽育种研究。E-mail:

Copy editor: 陈鑫

收稿日期: 2024-05-06

  网络出版日期: 2024-11-09

基金资助

现代农业产业技术体系专项资金(湘农发[2022]31)

衡阳市科技创新项目(202250045207)

收起

Study on Rule of Growth and Body Composition Deposition of Hunan Yellow Chicken

  • CHEN Kai , 1 ,
  • ZHANG Xu 2, * ,
  • WU Cong 1 ,
  • LUO Zhijia 1 ,
  • WEN Ye 3 ,
  • TAN Zhiyang 2 ,
  • ZHANG Hui 2 ,
  • MA Yuyong , 1, ** ,
  • DAI Qiuzhong 2
Expand
  • 1 Hengyang Academy of Agricultural Sciences, Hengyang 421001, China
  • 2 Hunan Institute of Animal and Veterinary Science, Changsha 410128, China
  • 3 Hunan Polytechnic of Environment and Biology, Hengyang 421005, China
** livestock engineer, E-mail:

* Contributed equally

Received date: 2024-05-06

  Online published: 2024-11-09

Fold

摘要

本试验旨在充分利用各曲线模型载荷信息,对家禽生长发育过程进行深入研究,对3种生长模型曲线进行求导解析,为湘黄鸡生长阶段划分和精准营养调控提供参考。本试验选用健康、体重相近的1日龄湘黄鸡300只,分为6个组,每组50只。试验期为20周,每周抽取12只鸡测定体重,抽取6只鸡麻醉致死后粉碎待测体成分干物质(DM)、粗蛋白质(CP)、粗脂肪(EE)、粗灰分(Ash)含量和总能(GE),并使用Logistic、Gompertz和Bertalanffy 3种生长模型对湘黄鸡体重和体成分沉积进行拟合分析,计算出各个拐点周龄(IPA)以及对应的拐点体重(IPW)和拐点体成分(IPBC)。结果表明: 湘黄鸡体重生长曲线最佳拟合模型为Gompertz(R2>0.99),其IPA公母混合分别为2.16、8.28和14.40周龄;公鸡分别为2.51、8.01和13.50周龄;母鸡分别为1.68、8.72和15.77周龄。IPW公母混合分别为116.80、588.59和1 091.17 g;公鸡分别为123.72、623.47和1 155.83 g;母鸡分别为111.89、563.88和1 045.35 g。湘黄鸡体成分沉积曲线最佳拟合模型是Logistic(0.96<R2<0.97),其IPA分别为4.91~5.58周龄、9.30~9.61周龄和13.65~13.74周龄。根据体重生长曲线拟合结果可知,湘黄鸡生长阶段可划分为0~2周龄、3~8周龄、9~14周龄和15周龄至上市4个阶段;而根据体成分沉积曲线拟合结果可知,湘黄鸡生长阶段可划分为0~5周龄、6~9周龄、10~13周龄和14周龄至上市4个阶段;但是根据拟合度结果来看,体重拟合曲线阶段划分更具有可信度。

关键词： 湘黄鸡; 生长曲线拟合; 体成分沉积

本文引用格式

陈凯 , 张旭 , 吴聪 , 罗志嘉 , 文野 , 谭智阳 , 张慧 , 马玉勇 , 戴求仲 . 湘黄鸡生长及体成分沉积规律研究[J]. 动物营养学报, 2024 , 36(11) : 7003 -7014 . DOI: 10.12418/CJAN2024.597

Abstract

This experiment fully utilizes the load information of each curve model to conduct in-depth study on the growth and development process of poultry, and analyzes the derivation of the three growth model curves to obtain the three inflection points of the curves, which can provide references for the division of growth stages and the precise nutritional regulation of Hunan yellow chickens. A total of 300 one-day-old healthy Hunan yellow chickens with similar body weight were selected and divided into 6 goups with 50 chickens per group. The experiment lasted for 20 weeks. Twelve chickens were selected weekly for body weight measurement, and 6 chickens were anesthetized to death and crushed for body composition—dry matter(DM), crude protein(CP), ether extract (EE), crude ash (Ash) and gross energy (GE). Three growth models, Logistic, Gompertz and Bertalanffy were used to fit the body weight and body composition deposition of Hunan yellow chickens, and to calculate inflection point weeks of age (IPA), inflection point weight (IPW) and inflection point body composition (IPBC). Results showed that the optimal fitting model for the body weight growth curve of Hunan yellow chickens was Gompertz (R2>0.99), with IPA for male+female at 2.16, 8.28 and 14.40 weeks of age; for males at 2.51, 8.01 and 13.50 weeks of age; and for females at 1.68, 8.72 and 15.77 weeks of age. The IPW for male+female was 116.80, 588.59 and 1 091.17 g; for males was 123.72, 623.47 and 1 155.83 g; and for females was 111.89, 563.88 and 1 045.35 g. The best fitting model for the body composition deposition curve of Hunan yellow chicken was Logistic (0.96<R2<0.97), with IPA of 4.91 to 5.58 weeks of age, 9.30 to 9.61 weeks of age and 13.65 to 13.74 weeks of age, respectively. According to the fitting results of body weight curve, it can be concluded that the growth stages of Hunan yellow chickens can be divided into four stages: 0 to 2 weeks of age, 3 to 8 weeks of age, 9 to 14 weeks of age and 15 weeks of age to market. And according to the fitting results of body composition deposition curve, it can be concluded that the growth stages of Hunan yellow chickens can be divided into four stages: 0 to 5 weeks of age, 6 to 9 weeks of age, 10 to 13 weeks of age and 14 weeks of age to market. But according to the fitting degree results, the stage division of body weight fitting results is more credible.

Key words： Hunan yellow chicken; growth curve fitting; composition deposition

湘黄鸡又称黄郎鸡,以毛黄、嘴黄、脚黄为主要标志,肉蛋兼用,曾作为“贡品鸡”和“名贵项鸡”誉满全国,是国家农产品地理标志产品,主要产于衡阳及周边永州、郴州、邵阳、长沙等地区[1-2]。湘黄鸡具有肉质细嫩、味道鲜美、营养价值高等优点,具有较高的开发价值[1,3-4]。但是近些年来湘黄鸡种质资源质量退化杂化,湘黄鸡养殖业发展萎靡,其主要原因一是湘黄鸡品种杂乱,二是湘黄鸡养殖饲料成本过高。如何提高湘黄鸡饲粮营养利用率、探究湘黄鸡的营养需要、制定湘黄鸡饲养标准、降低饲料成本尤为重要。
家禽饲养过程中,体重和机体营养物质沉积会随着禽类生长过程发生规律性变化,生长和体成分沉积曲线用于描述动物体重和机体营养物质沉积随年龄增长而发生的规律,可反映个体在整个生长发育过程中的规律性变化,反映内部和所处外部环境之间的联系[5]。理想的生长和机体营养物质沉积曲线模型,可以分析禽类生长过程的体重和营养物质沉积动态变化,预测畜禽的生长规律,从而指导禽类饲养管理和育种实践,为禽类营养需要和饲养标准制定提供参考[6]。畜禽的生长发育规律具有稳定的特征,可用1条拉长的“S”型曲线来表示,有匀速生长期、加速生长期及稳定期3个阶段,通过函数模型对其生长曲线进行拟合与分析是研究畜禽生长规律的一种主要方法[7],目前禽类生长曲线拟合模型主要有Logistic、Gompertz和Bertalanffy[8]。本试验旨在使用这3种生长曲线模型对湘黄鸡生长和体成分沉积曲线进行拟合,找出最合适的模型,以期为湘黄鸡的不同阶段划分和饲养标准制定提供参考。

1 材料与方法

1.1 试验设计与饲粮

本试验地点是衡山华隆生态农业科技有限公司黄郎鸡原种场,黄郎鸡原种由该公司提供。选用健康、体重相近的1日龄湘黄鸡共300只,分为6个组,每组50只。0~10周龄湘黄鸡采用3层层叠式网上笼养育雏,规格为100 cm×38 cm×66 cm,密度约为10只/笼,11~20周龄之后采用3层立体式单笼饲养方式,单笼规格为22 cm×24 cm×55 cm。参考农业部颁布的《黄羽肉鸡饲养管理技术规程》(NY/T 1871—2010),分为2个阶段饲喂,0~10周龄饲喂肉小鸡料,11~20周龄饲喂肉中鸡料,自由饮水和自由采食。基础饲粮组成及营养水平见表1。
表1 基础饲粮组成及营养水平(干物质基础)

Table 1 Composition and nutrient levels of basal diets (DM basis) %

项目
Items		 0~10周龄
0 to 10
weeks
of age		 11~20周龄
11 to
20 weeks
of age
原料Ingredients
玉米Corn 57.20 62.85
豆粕Soybean meal 35.45 28.14
玉米蛋白粉Corn protein meal 1.50 3.05
大豆油Soybean oil 1.89 2.00
磷酸氢钙CaHPO4 1.20 1.20
石粉Limestone 1.30 1.30
食盐NaCl 0.30 0.30
L-赖氨酸盐酸盐L-Lys·HCl 0.16 0.16
预混料Premix1) 1.00 1.00
合计Total 100.00 100.00
营养水平Nutrient levels2)
代谢能ME/(MJ/kg) 12.04 12.31
粗蛋白质CP 21.30 19.22
钙Ca 0.91 0.94
总磷TP 0.55 0.61
赖氨酸Lys 0.99 1.00
蛋氨酸Met 0.31 0.35

1)0~10周龄预混料为每千克饲粮提供The premix provided the following per kg of diets in 0 to 10 weeks of age:VA 10 000 IU,VD3 1 000 IU,VE 20 IU,VK3 0.5 mg,VB1 2.0 mg,VB2 8.0 mg,泛酸 pantothenic acid 10.0 mg,烟酸 nicotinic acid 35.0 mg,VB6 3.5 mg,生物素 biotin 0.05 mg,叶酸 folic acid 0.55 mg,VB12 0.01 mg,胆碱 choline 1 300 mg,Fe (as ferrous sulfate) 100 mg,Cu (as copper sulfate) 8.0 mg,Zn (as zinc sulfate) 100 mg,Mn (as manganese sulfate) 120 mg,I (as potassium iodide) 0.7 mg,Se (as sodium selenite) 0.3 mg;11~20周龄预混料为每千克饲粮提供The premix provided the following per kg of diets in 11 to 20 weeks of age:VA 8 000 IU,VD3 750 IU,VE 15 IU,VK3 0.5 mg,VB1 2.0 mg,VB2 5.0 mg,泛酸 pantothenic acid 10.0 mg,烟酸 nicotinic acid 30.0 mg,VB6 3.5 mg,生物素 biotin 0.05 mg,叶酸 folic acid 0.55 mg,VB12 0.01 mg,胆碱 choline 1 000 mg,Fe (as ferrous sulfate) 80 mg,Cu (as copper sulfate) 8.0 mg,Zn (as zinc sulfate) 80 mg,Mn (as manganese sulfate) 100 mg,I (as potassium iodide) 0.7 mg,Se (as sodium selenite) 0.3 mg。

2)代谢能参考《中国饲料成分及营养价值表(2020年第31版)》计算得到,其余营养水平均为实测值,其中干物质、粗蛋白质、钙、总磷、氨基酸测定方法分别参照国标GB/T 6435—2014、GB/T 6432—2018、GB/T 6436—2018、GB/T 6437—2018和GB/T 18246—2019。ME was calculated with reference to Tables of Feed Composition and Nutritive Values in China (31st ed, 2020), while other nutrient levels were measured values, and DM, CP, Ca, TP and amino acid determination methods were based on GB/T 6435—2014, GB/T 6432—2018, GB/T 6436—2018, GB/T 6437—2018 and GB/T 18246—2019, respectively.

1.2 体重与常规营养物质体成分测定

1.2.1 体重

试验期为20周,前6周每周随机抽取12只鸡,每组2只,第7周开始每周抽取12只鸡,每组公母各1只,空腹停料12 h后测量体重。

1.2.2 常规营养物质与体成分测定

试验期前6周每周随机抽取6只鸡,每组1只鸡,第6周后每周抽取6只鸡,公母各1只,翅静脉注射30 mg/kg戊巴比妥钠麻醉后致死,去除消化道内容物后称重,用骨糜机粉碎后混匀,取100 g冷冻保存备测。采用105 ℃恒重法测定干物质(DM)含量,采用凯氏定氮法测定粗蛋白质(CP)含量(FOSS 8400全自动定氮仪),采用索氏抽提法测定粗脂肪(EE)含量(海能SOX406脂肪测定仪),采用高温灼烧法测定粗灰分(Ash)含量(上海力辰箱式电阻炉),以上指标测定分别参照国标GB/T 6435—2014、GB/T 6432—2018、GB/T 6433—2006和GB/T 6438—2007。采用全自动氧弹式量热仪(湖南开元仪器有限公司)测定总能(GE)。每只鸡营养物质沉积计算公式如下:
营养物质沉积(g)=每只鸡营养物质含量(%)× W(g)。
式中:W为鸡麻醉致死去除消化道内容物后的体重。

1.3 生长模型的选择

本试验采用的生长模型为Logistic、Gompertz和Bertalanffy模型,在3种模型中,参数A表示极限生长量,K为瞬时相对生长率,B为常数,t为周龄。为充分利用各曲线模型载荷信息,对家禽生长发育过程进行深入研究,对3种生长模型曲线进行求导解析,进而得到曲线的3个拐点[9]。各表达式的二阶导函数值为0时得到拐点周龄(inflection point weeks of age, IPA)为IPA_T2,三阶导函数值为0时得到IPA_T1和IPA_T3,对应拐点体重(inflection point weight,IPW)分别为IPW_Y2、IPW_Y1和IPW_Y3,拐点体成分(inflection point body composition, IPBC)分别为IPBC_Y2、IPBC_Y1和IPBC_Y3,对应的表达式和相关参数见表2。
表2 生长模型表达式

Table 2 Growth model expression1)

模型
Model		 表达式
Expression2)		 拐点体重(拐点体成分) IPW (IPBC) 拐点周龄IPA
IPW_Y1
(IPBC_Y1)		 IPW_Y2
(IPBC_Y2)		 IPW_Y3
(IPBC_Y3)		 IPA_T1 IPA_T2 IPA_T3
Logistic Y=A/(1+Be-Kt) A/4.732 A/2 A/1.268 (lnB-1.317)/K (lnB)/K (lnB+1.317)/K
Gompertz Y=Ae-Bexp(-Kt) 0.073A A/e 0.682A (lnB-0.962)/K (lnB)/K (lnB+0.962)/K
Bertalanffy Y=A(1-Be-Kt)3 0.018A 0.296A 0.613A (ln1.354B)/K (ln3B)/K (ln6.646B)/K

1) 表达式的二阶导函数值为0时得到拐点周龄IPA_T2,三阶导函数值为0时得到拐点周龄IPA_T1和IPA_T3,对应拐点体重和拐点体成分值分别为IPW_Y2(IPBC_Y2)、IPW_Y1(IPBC_Y1)和IPW_Y3(IPBC_Y3)。下表同。When the second derivative of the expression is 0, the inflection point cycle age IPA_T2 is obtained, and when the third derivative is 0, the inflection point cycle age IPA_T1 and IPA_T3 are obtained. By substituting the expression, the inflection point body weight and the inflection point body component are IPW_Y2(IPBC_Y2), IPW_Y1(IPBC_Y1) and IPW_Y3(IPBC_Y3), respectively. The same as below.

2) A:极限生长量;K:瞬时生长速度;B:常数,t:周龄。A: limited growth value; K: instantaneous growth rate; B: constant; t: weeks of age.

1.4 统计与分析

所有数据用Excel 2019进行初步处理,由于生长模型非线性回归分析迭代数据量过大,数据分析采用频率数据进行分析,将每项原数据与该项最大值的比值作为待分析数据,之后使用SPSS 26.0非线性回归方法进行体重和体成分沉积非线性模型拟合,并计算出模型参数的最优估计值A、B、K。根据Logistic、Gompertz和Bertalanffy模型计算出IPW、IPBC和IPA的频率值并换算回真实值,使用模型计算出每周的实测值和3种模型的估计值,并计算每周实测值与估计值的相差绝对值,相差绝对值最小的用“*”标记;使用GraphPad Prism 8软件绘制3种模型估计值与实测值曲线图。

2 结果与分析

2.1 生长曲线拟合结果

通过3种生长曲线模型对湘黄鸡公母的体重进行拟合,可得拟合结果(表3):3种模型均能很好地拟合湘黄鸡的体成分沉积曲线(R2>0.99)。根据IPA和IPBC结果,3种模型IPA_T1和IPW_Y1的差异较大,其中Logistic模型拟合结果IPW_Y1和IPA_T1最大,而Bertalanffy模型拟合结果最小,母鸡拟合结果IPA_T1显示为-0.27,与实际不符。3种模型中公鸡拐点IPA_T1与IPA_T3相差值均小于母鸡。
表3 湘黄鸡生长曲线拟合结果

Table 3 Fitting results of growth curve of Hunan yellow chicken(n=12)

模型
Model		 模型参数
Model parameter		 拟合度
Degree of
fitting
(R2)		 拐点体重IPW/g 拐点周龄IPA
IPW_Y1 IPW_Y2 IPW_Y3 IPA_T1 IPA_T2 IPA_T3
A B K
公母混合Male+female
Logistic 1.05 16.08 5.75 0.997 296.49 701.49 1 106.45 5.08 9.67 14.25
Gompertz 1.19 3.68 3.15 0.998 116.80 588.59 1 091.17 2.16 8.28 14.40
Bertalanffy 1.33 0.78 2.25 0.997 31.65 520.39 1 077.70 0.44 7.50 14.56
公Male
Logistic 1.03 19.04 6.25 0.997 318.01 752.42 1 186.77 5.21 9.43 13.64
Gompertz 1.16 4.06 3.50 0.997 123.72 623.47 1 155.83 2.51 8.01 13.50
Bertalanffy 1.26 0.84 2.57 0.995 33.14 544.89 1 128.45 1.00 7.19 13.38
母Female
Logistic 1.06 12.95 5.12 0.992 276.90 655.14 1 033.34 4.86 10.00 15.15
Gompertz 1.24 3.29 2.73 0.996 111.89 563.88 1 045.35 1.68 8.72 15.77
Bertalanffy 1.41 0.72 1.91 0.996 31.37 515.90 1 068.41 -0.27 8.06 16.39
由表4和表5可知,所有湘黄鸡及公母体重在大多数周龄的Gompertz模型估计值与实测值的相差绝对值最小,被标记的周龄(公母混合湘黄鸡为10周龄,公鸡为9周龄,母鸡为9周龄)大于其他模型。结合表3、表4和表5可知,湘黄鸡体重生长曲线Gompertz拟合估计值与实测值最为接近,拟合效果最佳。
表4 湘黄鸡体重实测值与拟合估计值比较(公母混合)

Table 4 Comparison of measured and fitted estimated body weight of Hunan yellow chicken(male+female) (n=12) g

周龄
Weeks of age		 公母混合Male+female
体重实测值
Body weight measured value		 Logistic Gompertz Bertalanffy
0 32.90±0.51 82.14 40.48* 20.03
1 78.49±8.65 107.39 69.12* 51.40
2 122.40±12.59 139.58 109.18* 98.21
3 160.54±20.38 180.08 161.36* 158.68
4 226.30±32.45 230.19 225.30* 230.20
5 303.00±36.47 290.93 299.67* 309.94
6 402.50±53.44 362.74 382.38 395.15*
7 470.37±54.41 445.17 470.92* 483.37
8 551.28±69.79 536.68 562.65* 572.53
9 625.75±80.29 634.53* 655.06 660.92
10 749.25±105.99 735.09 745.95 747.21*
11 825.12±116.09 834.28 833.55 830.38*
12 900.83±121.77 928.25 916.51 909.72*
13 1 039.50±177.15 1 013.94* 993.91 984.75
14 1 070.20±161.47 1 089.38 1 065.20* 1 055.18
15 1 139.50±205.51 1 153.79 1 130.16* 1 120.88
16 1 163.00±219.12 1 207.35 1 188.80 1 181.84*
17 1 261.20±226.58 1 250.91* 1 241.31 1 238.14
18 1 320.00±204.16 1 285.72 1 288.01 1 289.93*
19 1 290.70±219.75 1 313.13* 1 329.30 1 337.41
20 1 340.00±168.30 1 334.47* 1 365.64 1 380.80

*表示该周龄下拟合估计值与实测值的相差绝对值最小。下表同。

* indicates that the absolute difference between the fitted estimate and the measured value is the smallest under this week of age. The same as below.

表5 湘黄鸡体重实测值与拟合估计值比较(公和母)

Table 5 Comparison of measured and fitted estimated body weight of Hunan yellow chicken (male and female)(n=12) g

周龄
Weeks
of age		 公Male 母Female
体重实测值
Body weight
measured value		 Logistic Gompertz Bertalanffy 体重实测值
Body weight
measured value		 Logistic Gompertz Bertalanffy
0 32.84±0.96 75.09 29.23* 7.54 32.84±0.96 93.93 57.10 38.26*
1 78.49±8.54 100.79* 56.10 32.84 78.49±8.54 118.84 86.89* 70.01
2 122.40±12.43 134.46* 96.96 79.18 122.40±12.43 149.56 125.32* 115.94
3 160.54±20.13 177.96 153.48* 145.05 160.54±20.13 186.97 172.49 168.94*
4 228.51±34.52 233.12 225.69 226.81* 228.51±34.52 231.86 227.94* 229.31
5 303.00±36.01 301.51* 311.95 320.14 303.00±36.01 284.81 290.68 295.33*
6 410.50±62.13 383.90 409.34* 420.84 410.50±62.13 345.96 359.37 365.36*
7 516.31±35.01 479.82 514.21* 525.19 428.81±27.42 414.93 432.44* 437.92
8 615.00±53.64 587.16 622.73* 630.10 498.00±40.69 490.66* 508.21 511.69
9 688.57±39.00 702.06* 731.32 733.18 556.31±48.66 571.38* 585.08 585.53
10 827.62±71.19 819.37 836.96 832.62* 662.63±56.29 654.78 661.58* 658.53
11 924.44±77.95 933.49 937.34 927.18* 743.86±65.17 738.19* 736.45 729.93
12 1 007.92±43.70 1 039.41 1 030.83 1 016.03* 793.75±59.83 818.95 808.65 799.14*
13 1159.50±127.46 1133.50* 1116.49 1098.71 919.50±120.75 894.72* 877.39 865.72
14 1 191.50±77.46 1 213.89 1 193.86* 1 175.02 949.00±118.90 963.76 942.13* 929.36
15 1 264.50±112.83 1 280.32 1 262.93* 1 244.98 1 014.50±190.43 1 024.98* 1 002.49 989.85
16 1 337.60±128.35 1 333.73* 1 323.99 1 308.76 988.50±117.53 1 077.99 1 058.29 1 047.05*
17 1 435.50±129.81 1 375.71 1 377.53* 1 366.61 1 087.00±141.31 1 122.96 1 109.51 1 100.92*
18 1 450.00±139.64 1 408.13 1 424.13* 1 418.88 1 190.00±160.93 1 160.43 1 156.22* 1 151.45
19 1 388.00±177.07 1 432.84* 1 464.47 1 465.93 1 219.00±167.14 1 191.20 1 198.75* 1 198.71
20 1 461.00±109.26 1 451.48* 1 499.21 1 508.15 1 236.11±112.24 1 216.16 1 236.78* 1 242.76

2.2 体成分沉积拟合结果

通过3种生长曲线模型对湘黄鸡的体成分沉积进行拟合,可得拟合结果(表6):3种模型均能较好地拟合湘黄鸡的体成分沉积曲线(0.95<R2<0.98)。其中,DM含量3种模型(Logistic、Gompertz、Bertalanffy)拟合度分别为0.977、0.975和0.973,CP含量3种模型(Logistic、Gompertz、Bertalanffy)拟合度分别为0.974、0.974和0.972,Ash含量3种模型(Logistic、Gompertz、Bertalanffy)拟合度分别为0.968、0.963和0.959,GE 3种模型(Logistic、Gompertz、Bertalanffy)拟合度分别为0.967、0.967和0.965。根据IPA和IPBC结果发现:3种模型的IPA_T1和IPBC_Y1差异较大,其中Logistic模型拟合结果IPBC_Y1和IPA_T1最大(DM:92.9 g和4.93周龄;CP:58.39 g和5.09周龄;Ash:9.74 g和5.58周龄;GE:2 105.8 MJ/kg和4.91周龄),而Bertalanffy模型拟合结果IPBC_Y1和IPA_T1最小(DM:1.03 g和1.20周龄;CP:6.16 g和0.66周龄;Ash:9.74 g和5.58周龄;GE:221.16 MJ/kg和0.46周龄)。
表6 湘黄鸡体成分沉积曲线拟合结果

Table 6 Fitting results of body composition deposition curve of Hunan yellow chicken

模型
Model		 模型参数
Model parameter		 拟合度
Degree of
fitting (R2)		 拐点体成分IPBC 拐点周龄IPA
IPBC_Y1 IPBC_Y2 IPBC_Y3 IPA_T1 IPA_T2 IPA_T3
A B K
干物质DM
Logistic 1.07 16.40 6.00 0.977 92.90 219.80 346.69 4.93 9.32 13.71
Gompertz 1.21 3.69 3.30 0.975 36.29 182.88 339.03 2.08 7.91 13.74
Bertalanffy 1.33 0.78 2.38 0.973 9.84 161.74 334.95 0.46 7.14 13.83
粗蛋白质CP
Logistic 1.13 17.57 6.09 0.974 58.39 138.14 217.89 5.09 9.41 13.74
Gompertz 1.28 3.85 3.37 0.974 22.85 115.13 213.44 2.29 8.00 13.71
Bertalanffy 1.40 0.80 2.44 0.972 6.16 101.32 209.83 0.66 7.18 13.70
粗灰分Ash
Logistic 1.14 23.07 6.53 0.968 9.74 23.04 36.34 5.58 9.61 13.65
Gompertz 1.28 4.31 3.54 0.963 3.78 19.04 35.29 2.82 8.25 13.69
Bertalanffy 1.41 0.86 2.54 0.959 1.03 16.87 34.94 1.20 7.46 13.73
总能GE
Logistic 1.03 16.22 5.99 0.967 2 105.80 4 982.32 7 858.56 4.91 9.30 13.70
Gompertz 1.16 3.69 3.32 0.967 819.23 4 128.46 7 653.62 2.07 7.87 13.66
Bertalanffy 1.27 0.78 2.40 0.965 221.16 3 636.81 7 531.63 0.46 7.08 13.71

拐点体成分中干物质、粗蛋白质、粗灰分单位为g,总能单位为 MJ/kg。

The units of DM, CP and Ash in the composition of IPBC are g, and GE unit is MJ/kg.

由表7和表8可知,DM、CP、Ash和GE在大多数周龄的Logistic模型估计值与实测值的相差绝对值最小,被标记的周龄分别为11、8、11和13周龄,大于其他模型。结合表6、表7和表8可知,湘黄鸡体成分沉积曲线Logistic拟合估计值与实测值最为接近,拟合效果最佳。
表7 湘黄鸡体成分(干物质和粗蛋白质)沉积实测值与拟合估计值比较

Table 7 Comparison between measured and fitted estimated body composition (DM and CP) deposition of Hunan yellow chicken g

周龄
Weeks of
age		 干物质DM 粗蛋白质CP
干物质实测值
DM measured
value		 Logistic Gompertz Bertalanffy 粗蛋白质实测值
CP measured
value		 Logistic Gompertz Bertalanffy
0 8.68±0.40 25.26 12.41 5.82* 4.83±0.25 14.88 6.66* 2.74
1 28.22±0.71 33.43* 21.76 15.89 14.86±0.29 19.79 12.10* 8.51
2 42.95±0.88 43.96* 35.02 31.23 24.20±3.63 26.17* 20.04 17.79
3 56.68±2.05 57.33* 52.43 51.19 33.17±1.01 34.33* 30.68 30.20
4 85.48±5.35 74.01 73.82 74.82* 48.97±3.86 44.58 43.99 45.12*
5 111.09±15.07 94.35 98.67 101.08* 66.06±8.98 57.16 59.63 61.84*
6 106.24±10.61 118.46* 126.18 129.00 65.52±6.69 72.19* 77.11 79.72
7 148.33±29.12 146.13* 155.44 157.74 93.80±14.68 89.56 95.82* 98.16
8 170.57±23.25 176.70* 185.51 186.57 106.79±19.89 108.88* 115.12 116.68
9 165.74±24.73 209.12* 215.52 214.95 106.81±13.54 129.47* 134.44 134.90
10 317.24±62.17 242.00 244.73* 242.44 191.41±19.50 150.46 153.26* 152.54
11 246.54±28.38 273.91 272.59 268.72* 167.13±27.48 170.89 171.20 169.37*
12 300.89±52.67 303.57 298.67* 293.59 178.22±31.67 189.91 187.99 185.27*
13 321.03±58.99 330.04 322.74* 316.92 217.97±48.39 206.89* 203.45 200.15
14 348.90±40.78 352.83* 344.66 338.63 211.63±41.44 221.49 217.50 213.96*
15 366.06±28.90 371.85 364.40* 358.72 221.42±41.08 233.66 230.12 226.71*
16 389.33±81.58 387.32* 382.03 377.22 237.70±64.84 243.52 241.36 238.40*
17 391.28±73.05 399.64 397.64 394.16* 254.29±94.66 251.34* 251.28 249.08
18 432.60±69.96 409.28 411.38* 409.61 261.76±72.03 257.44 259.98* 258.80
19 414.68±159.85 416.73* 423.40 423.67 295.18±121.77 262.14 267.57 267.61*
20 410.84±59.92 422.43* 433.86 436.42 244.50±51.45 265.71* 274.15 275.57
表8 湘黄鸡体成分(粗灰分和总能)沉积实测值与拟合估计值比较

Table 8 Comparison between measured and fitted estimated body composition (ash and GE) deposition of Hunan yellow chicken

周龄
Weeks of
age		 粗灰分Ash/g 总能GE/(MJ/kg)
粗灰分实测值
Ash measured
value		 Logistic Gompertz Bertalanffy 总能实测值
GE measured
value		 Logistic Gompertz Bertalanffy
0 0.61±0.03 1.91 0.70* 0.16 213.00±12.37 578.67 280.24* 130.83
1 2.32±0.08 2.61* 1.40 0.81 634.98±15.24 765.21* 492.78 359.70
2 3.70±0.34 3.54* 2.51 2.10 947.89±160.01 1 005.45* 794.83 708.99
3 5.45±0.39 4.77* 4.10 4.00 1 255.92±46.79 1 310.37* 1 191.64 1 163.56
4 8.12±0.81 6.36 6.19 6.40* 1 880.95±146.32 1 690.31 1 679.23 1 701.29*
5 10.61±1.15 8.36 8.74 9.19* 2 518.32±355.43 2 153.02 2 245.40 2 298.53*
6 9.69±1.16 10.83* 11.66 12.22 2 429.16±305.14 2701.03* 2 871.94 2 932.94
7 14.33±3.56 13.77 14.85* 15.40 3 386.47±720.57 3 329.09* 3 537.61 3 585.02
8 15.39±2.93 17.11* 18.18 18.61 4 006.71±570.12 4 022.31* 4 220.82 4 238.59
9 16.21±2.36 20.74* 21.54 21.79 3 682.97±674.80 4 756.42* 4 901.79 4 880.85
10 30.85±4.46 24.49 24.83 24.87* 7 473.55±1 857.35 5 500.49 5 563.86* 5 502.11
11 24.54±3.90 28.17 27.97 27.81* 5 495.09±283.71 6 221.90 6 194.16 6 095.41*
12 28.62±6.54 31.59 30.90 30.59* 6 883.64±1 370.56 6 891.86* 6 783.59 6 656.03
13 38.91±12.55 34.62* 33.60 33.18 6 804.05±1 251.88 7 489.60 7 326.54 7 181.15*
14 35.44±10.82 37.20 36.04 35.58* 7 990.22±1 122.06 8 004.14* 7 820.30 7 669.38
15 42.15±11.34 39.31* 38.21 37.79 8 415.36±459.70 8 433.58* 8 264.49 8 120.51
16 41.19±11.73 40.99* 40.14 39.81 9 095.56±1 533.38 8 782.84* 8 660.41 8 535.13
17 39.56±16.94 42.29 41.83 41.65* 8 800.56±1 505.32 9 060.97 9 010.57 8 914.47*
18 44.24±8.38 43.28 43.29 43.31* 9 901.16±1 436.08 9 278.76 9 318.23* 9 260.18
19 47.16±22.40 44.02 44.56 44.81* 8 846.75±3 187.59 9 447.05* 9 587.04 9 574.17
20 40.42±12.50 44.58* 45.66 46.16 9 674.42±1 697.87 9 575.79* 9 820.79 9 858.53

2.3 体成分沉积曲线

湘黄鸡体重和体成分沉积生长曲线均呈近“S”型,基本符合正常生长规律,并且拟合曲线和实测值曲线基本吻合,拟合效果较好。由图1可知,体重生长曲线拟合效果比体成分沉积生长曲线拟合效果更好。图1中曲线F表示EE沉积随着时间的增长而增长,但图中显示每周EE沉积的个体差异很大。
图1 体成分沉积曲线

A~E分别代表体重、干物质、粗蛋白质、粗灰分、总能的实测值和拟合估计值曲线。F代表粗脂肪实测值曲线。

Fig.1 Curve of body composition deposition

A to E mean the curves of measured and fitting body weight, DM, CP, Ash and GE. F mean the curves of measured EE.

3 讨论

动物生长不仅是体重体尺的增加,从生理角度上讲,动物生长也是指机体细胞的增殖、组织器官的日趋完善,也是机体化学成分,即蛋白质、脂肪、矿物质和水等沉积的过程。所以动物生长规律的探究不但要研究体重的变化,也要探究各种营养物质在机体累积的过程[10]。动物的生长具有一定规律性,从生长曲线来看,前期生长缓慢,中期生长快速,后期生长缓慢到逐渐趋于平缓,整个过程呈现拉长的“S”形。一般动物生长采用非线性拟合曲线数学模型来描述其生长规律变化,Logistic、Gompertz和Bertalanffy 3种模型函数在家禽行业应用最广泛,可以描述并预测家禽各个生长阶段的体重和生长速度等情况[6,8,11-12]。
大量的研究表明,Gompertz模型计算的生长参数更符合实际,如杏花鸡与白洛克鸡杂交鸡[13]、海兰褐父母代种鸡[5]、略阳乌鸡[14]、黔东南小香鸡[15]、清远麻鸡[16]、香炉山鸡[17]、白羽雉鸡[18]、温州红母鸡[19]、火鸡[20]。伍维高等[2]研究的湘黄母鸡也发现Gompertz生长曲线的拟合效果最佳。这与本试验体重拟合曲线结果相符,通过对实测值与曲线估计值的比较发现Gompertz模型拟合效果最佳。但是通过比较体成分沉积实测值与曲线估计值结果,发现Logistic拟合效果最佳,这与部分学者的研究结果相同,其中包括温州红母鸡[19]、爱拔益加商品肉鸡[21]、桂香鸡[22]和贵州黄鸡慢羽系[23]等。也有少部分学者研究发现,娄门鸭[24]、东乡黑鸡[25]、新杨黑羽蛋鸡[25]、黑羽系雪峰乌骨鸡[26]等禽类Bertalanffy模型拟合效果最佳。上述研究结果表明,不同品种、物种、亲缘关系、性别、地域以及不同饲养管理方式下动物的生长发育规律都有较大差异,因此需要针对实际生长数据选择最佳的拟合模型[24]。
生长曲线拟合可以为家禽生长阶段划分和饲养标准制定提供参考,IPA是生长速率发生不同变化的转折点,根据这些转折点可分为若干生长阶段,拐点周龄IPA_T2是生长速率由快到慢的转折点,而IPA_T1和IPA_T3则表示生长速度增长和降低的转折点,0~IPA_T1时间段生长速度快速升高,是生长初期,IPA_T1~IPA_T2时期生长速度继续升高,一直到IPA_T2时期生长速率达到最高峰,之后IPA_T2~IPA_T3时期生长速率开始降低,但该时期生长速率仍相对较高,所以IPA_T1~IPA_T3时期是生长快速期,IPA_T1~IPA_T2、IPA_T2~IPA_T3时期分别是快速生长期的早期和晚期,快速生长期IPA_T1~IPA_T3时期越长,机体生长期越长,营养沉积越丰富,该时期应该尽可能地满足畜禽营养需要,促进畜禽快速增长育肥[24]。王婷等[26]首先对0~19周雪峰乌骨鸡生长曲线进行拟合,然后通过IPA分为前后2个阶段,再重新对这2个阶段分别进行拟合,得到2个拐点,最终被划分为3个阶段(公鸡:0~7周龄、8~13周龄和14周龄至上市;母鸡:0~6周龄、7~16周龄和17周龄至上市)。本试验中通过求导等数学运算,得到3个拐点,可分为4个阶段:第0~IPA_T1阶段为生长前期,第IPA_T1~IPA_T2阶段为生长快速早期,第IPA_T2~IPA_T3阶段为生长快速末期,第IPA_T3到最后为平缓期。本试验结果发现,公鸡拐点IPA_T1与IPA_T3相差值均小于母鸡,说明公鸡生长周期要小于母鸡生长周期,这可能是由于公鸡生长速度快于母鸡,但是公鸡生长速度快,而周期短,肉品质可能低于母鸡,所以在实际生产中以饲养散养湘黄母鸡为主[3]。本试验根据体重生长曲线拟合可大概分为0~2周龄、3~8周龄、9~14周龄和15周龄至上市,根据体成分沉积曲线拟合可大概分为0~5周龄、6~9周龄、9~13周龄和14周龄至上市。但是体成分沉积曲线拟合度约为0.97,而体重曲线拟合度大于0.99,所以体重的拟合结果阶段划分(0~2周龄、3~8周龄、9~14周龄和15周龄至上市)似乎更加可靠。本试验结果中发现,Bertalanffy模型拟合计算得到的拐点IPA_T1远远小于其他模型IPA_T1值,甚至湘黄母鸡IPA_T1值出现了负数。Bertalanffy模型中K为瞬时相对生长率,B可反映周龄为0时的初始值,当B越小,初始值越大,根据Bertalanffy模型拐点IPA_T1计算公式,只有当B足够大,而K足够小时,拐点周龄IPA_T1可信度最高,所以Bertalanffy模型在应用于初始值和初始速率都足够小的情况下可信度可能更高[27]。
脂肪和蛋白质是肌肉的基本营养成分,能够为生物提供必需的营养和热量。脂肪也是很多风味物质的载体,随着日龄的增长,脂肪、蛋白质等营养物质沉积含量也逐渐升高[14]。本试验结果显示,EE沉积随时间变化而缓慢增长,但是脂肪沉积极易受到外在环境、饲养管理等影响,导致个体差异太大,所以未进行曲线拟合。从生长速度上来看,一般慢速型肉鸡IPA越晚,生长周期越长;而快速型肉鸡IPA越早,生长周期越短。湘黄鸡是属于慢速型优质肉鸡,生长周期长,幼龄家禽所摄入的能量、蛋白质等用于机体的维持需要,所以体内能量、蛋白质等物质的沉积速度可能就会推迟,这与本试验结果相符,幼龄家禽的体成分沉积曲线IPA大于体重生长曲线IPA,这可能是由于幼龄家禽胃肠道发育不完全,对营养物质的消化能力弱,前期营养物质沉积速度慢于体重增长速度,所以体重增长要更快达到拐点[28]。从湘黄鸡实测值曲线和估计值拟合曲线变化得知,第9、10周时体成分沉积曲线波动较大,这可能与鸡群转笼造成的应激有关。

4 结论

根据体重生长曲线拟合结果可知:湘黄鸡生长阶段可划分为0~2周龄、3~8周龄、9~14周龄和15周龄至上市4个阶段;而根据体成分沉积曲线拟合结果可知:湘黄鸡生长阶段可划分为0~5周龄、6~9周龄、10~13周龄和14周龄至上市4个阶段;但是根据拟合度结果来看,体重拟合曲线阶段划分更具有可信度。

参考文献

原文顺序 | 文献年度倒序 | 文中引用次数倒序
[1]
马玉勇, 罗志嘉, 陈凯, 等. 乡村振兴视角下特色农业产业发展研究——以衡阳湘黄鸡产业为例[J]. 当代畜牧, 2022(1):113-116.

MA Y Y, LUO Z J, CHEN K, et al. Research on the development of characteristic agricultural industry from the perspective of rural revitalization-taking Hunan yellow chicken industry in Hengyang as an example[J]. Contemporary Animal Husbandry, 2022(1):113-116. (in Chinese)

[2]
伍维高, 曹忻, 许美解. 湘黄母鸡生长曲线拟合的研究[J]. 畜牧与饲料科学, 2010, 31(10):9-11.

WU W G, CAO X, XU M J. Analysis on growth curve fitting in Hunan yellow hens[J]. Animal Husbandry and Feed Science, 2010, 31(10):9-11. (in Chinese)

[3]
马玉勇, 陈凯, 胡小爱, 等. 不同饲养模式对湘黄母鸡生长性能、屠宰性能及肉品质的影响[J]. 饲料工业, 2023, 44(21):47-51.

MA Y Y, CHEN K, HU X A, et al. Effects of different feeding modes on growth performance,slaughter performance and meat quality of Hunan yellow hens[J]. Feed Industry, 2023, 44(21):47-51. (in Chinese)

[4]
许美解, 钟金凤, 胡国平, 等. 湘黄鸡生长发育规律及产肉性能分析[J]. 中国家禽, 2008, 30(9):58-59.

XU M J, ZHONG J F, HU G P, et al. Growth and development of Hunan yellow chickens and analysis of meat production performance[J]. China Poultry, 2008, 30(9):58-59. (in Chinese)

[5]
李岩, 詹凯, 马瑞钰, 等. 四层层叠本交笼种鸡生长曲线拟合模型研究[J]. 中国家禽, 2018, 40(23):32-36.

LI Y, ZHAN K, MA R Y, et al. Study on fitting of growth curve for layer breeders in natural mating cages with four overlap tiers[J]. China Poultry, 2018, 40(23):32-36. (in Chinese)

[6]
XIE W Y, PAN N X, ZENG H R, et al. Comparison of nonlinear models to describe the feather growth and development curve in yellow-feathered chickens[J]. Animal, 2020, 14(5):1005-1013.

DOI PMID

[7]
詹凯, 李俊营, 许月英, 等. 3个蛋鸡品种生长发育比较及生长曲线拟合研究[J]. 中国畜牧杂志, 2011, 47(11):9-11.

ZHAN K, LI J Y, XU Y Y, et al. Comparison of growth and development and fitting of growth curve of 3 laying hens[J]. Chinese Journal of Animal Science, 2011, 47(11):9-11. (in Chinese)

[8]
VAN DER KLEIN S A S, KWAKKEL R P, DUCRO B J, et al. Multiphasic nonlinear mixed growth models for laying hens[J]. Poultry Science, 2020, 99(11):5615-5624.

DOI PMID

[9]
崔党群. Logistic曲线方程的解析与拟合优度测验[J]. 数理统计与管理, 2005, 24(1):112-115.

CUI D Q. Analysis and making good fitting degree test for logistic curve regression equation[J]. Application of Statistics and Management, 2005, 24(1):112-115. (in Chinese)

[10]
李勇. 肉仔鸡生长机制性预测模型的研究[D]. 博士学位论文. 北京: 中国农业科学院, 2010.

LI Y. Study on the mechanistic prediction model of growth in broilers[D]. Ph.D.Thesis. Beijing: Chinese Academy of Agricultural Sciences, 2010. (in Chinese)

[11]
NARINÇ D, ÖKSÜZ NARINÇ N, AYGÜN A. Growth curve analyses in poultry science[J]. World’s Poultry Science Journal, 2017, 73(2):395-408.

[12]
PORTER T, KEBREAB E, DARMANI KUHI H, et al. Flexible alternatives to the Gompertz equation for describing growth with age in Turkey hens[J]. Poultry Science, 2010, 89(2):371-378.

DOI PMID

[13]
滕晖, 张梓豪, 张细权, 等. 杏花鸡与白洛克鸡杂交F2代的生长曲线拟合及体尺与屠宰性能的相关和回归分析[J]. 中国家禽, 2021, 43(7):28-36.

TENG H, ZHANG Z H, ZHANG X Q, et al. Growth curve fitting of F2 generation hybrid derived from Xinghua chicken and white Plymouth rock chicken and association,regression analysis between body size traits and slaughter performances[J]. China Poultry, 2021, 43(7):28-36. (in Chinese)

[14]
张淑雅, 张纪桥, 蔡瑛婕, 等. 不同日龄略阳乌鸡肉品质对比与最佳上市日龄分析[J]. 中国畜牧兽医, 2022, 49(6):2165-2175.

DOI

ZHANG S Y, ZHANG J Q, CAI Y J, et al. Comparison of meat quality and analysis of the best listing date of Lueyang black-bone chickens at different ages[J]. China Animal Husbandry & Veterinary Medicine, 2022, 49(6):2165-2175. (in Chinese)

[15]
肖涛, 李辉, 唐诗云, 等. 黔东南小香鸡生长曲线拟合研究[J]. 畜牧与兽医, 2021, 53(11):1-5.

XIAO T, LI H, TANG S Y, et al. Study on growth curve fitting for Qiandongnan Xiaoxiang chickens[J]. Animal Husbandry & Veterinary Medicine, 2021, 53(11):1-5. (in Chinese)

[16]
邹剑敏, 宋迟, 单艳菊, 等. 清远麻鸡体重和胫长生长曲线的拟合[J]. 江苏农业科学, 2012, 40(4):213-215.

ZOU J M, SONG C, SHAN Y J, et al. Fitting of body weight and tibial-length growth curve of Qingyuan spotty plumage[J]. Jiangsu Agricultural Sciences, 2012, 40(4):213-215. (in Chinese)

[17]
叶涛, 李辉, 李兴才, 等. 香炉山鸡体重生长曲线的拟合研究与体尺测定[J]. 畜牧与兽医, 2022, 54(10):26-30.

YE T, LI H, LI X C, et al. Research on fitting the body weight growth curve of Xianglushan chicken and measurement of its body size[J]. Animal Husbandry & Veterinary Medicine, 2022, 54(10):26-30. (in Chinese)

[18]
李先玉, 周瑾, 吴昊旻, 等. 白羽雉鸡生长曲线拟合及分析[J]. 中国畜牧杂志, 2024, 60(6):209-212.

LI X Y, ZHOU J, WU H M, et al. Fitting and analysis of growth curve of white feather pheasant[J]. Chinese Journal of Animal Science, 2024, 60(6):209-212. (in Chinese)

[19]
李紫薇, 张雅文, 宋斌, 等. 温州红鸡生长曲线拟合与最佳上市周龄分析[J/OL]. 浙江农业学报:1-14.(2024-04-22)[2024-05-01]. http://kns.cnki.net/kcms/detail/33.1151.S.20240420.1609.002.html.

LI Z W, ZHANG Y W, SONG B, et al. Growth curve fitting and the optimal marketing time of Wenzhou red chicken[J]. Acta Agriculturae Zhejiangensis:1-14.(2024-04-22)[2024-05-01]. http://kns.cnki.net/kcms/detail/33.1151.S.20240420.1609.002.html (in Chinese)

[20]
ZUIDHOF M J. Multiphasic poultry growth models:method and application[J]. Poultry Science, 2020, 99(11):5607-5614.

[21]
马猛, 王克华, 曲亮, 等. 不同品种鸡生长曲线拟合及分析[J]. 中国畜牧杂志, 2022, 58(1):129-132.

MA M, WANG K H, QU L, et al. Fitting and analysis of growth curves of different breeds of chickens[J]. Chinese Journal of Animal Science, 2022, 58(1):129-132. (in Chinese)

[22]
李莉, 许晟玮, 梁明振. 桂香鸡生长规律的研究[J]. 动物营养学报, 2014, 26(7):1787-1795.

DOI

LI L, XU S W, LIANG M Z. Study on growth law of Guixiang chicken[J]. Chinese Journal of Animal Nutrition, 2014, 26(7):1787-1795. (in Chinese)

[23]
李洪林, 李维, 饶永超, 等. 贵州黄鸡慢羽系生长曲线拟合研究[J]. 中国畜牧兽医, 2019, 46(7):2053-2058.

DOI

LI H L, LI W, RAO Y C, et al. Study on growth curve fitting of slow-feathering line of Guizhou yellow chickens[J]. China Animal Husbandry & Veterinary Medicine, 2019, 46(7):2053-2058. (in Chinese)

[24]
沈永杰, 张丹, 张丽华, 等. 娄门鸭生长发育规律及生长曲线拟合研究[J]. 中国家禽, 2022, 44(5):116-120.

SHEN Y J, ZHANG D, ZHANG L H, et al. Study on growth and development law and growth curve fitting of Lumen duck[J]. China Poultry, 2022, 44(5):116-120. (in Chinese)

[25]
牛建芹, 靳笑菊, 张同玉, 等. 东乡黑鸡生长曲线拟合与分析[J]. 中国家禽, 2018, 40(2):47-49.

NIU J Q, JIN X J, ZHANG T Y, et al. Fitting and analysis of growth curve of Dongxiang black chicken[J]. China Poultry, 2018, 40(2):47-49. (in Chinese)

[26]
王婷, 邓雨英, 姚亚铃, 等. 黑羽系雪峰乌骨鸡生长曲线拟合、肉用性能评价及其相关性分析[J]. 中国畜牧杂志, 2024, 60(2):231-237.

WANG T, DENG Y Y, YAO Y L, et al. Growth curve fitting,meat performance evaluation and correlation analysis of Xuefeng black-bone chicken with black feathers[J]. Chinese Journal of Animal Science, 2024, 60(2):231-237. (in Chinese)

[27]
高超, 徐乃忠, 孙万明, 等. 基于Bertalanffy时间函数的地表动态沉陷预测模型[J]. 煤炭学报, 2020, 45(8):2740-2748.

GAO C, XU N Z, SUN W M, et al. Dynamic surface subsidence prediction model based on Bertalanffy time function[J]. Journal of China Coal Society, 2020, 45(8):2740-2748. (in Chinese)

[28]
韩晴, 李军国, 葛春雨, 等. 饲料破碎粒度对肉小鸡生长性能、消化器官发育的影响[J]. 饲料工业, 2018, 39(21):43-47.

HAN Q, LI J G, GE C Y, et al. Effect of feed crushed particle size on growth performance and digestive organ development of broilers[J]. Feed Industry, 2018, 39(21):43-47. (in Chinese)

Options
文章导航

/

〈 〉

    联系我们

  • 地址：北京市海淀区圆明园西路2号
    　　　中国农业大学动科动医大楼153室
  • 邮编：100193
  • 电话：010－62817823
  • 网址：http://www.chinajan.com
  • E-mail：cjan@chinajan.com
京公网安备 11010802041926号    京ICP备17050989号-2