农业工程学报

阶段 Stage	泌乳日龄 Lactation day/d	F1/ (kg·d^-1)	F2/ (kg·d^-1)	F3+/ (kg·d^-1)
注：F1、F2、F3+分别代表头胎、二胎及三胎及以上母猪。递增升料阶段，系统以前一日基础饲喂量为基数，结合前一日采食完成度与料槽剩料量，在各胎次对应增量区间内上调当日饲喂量：前一日采食充分、剩料少时取区间上限增量，剩料较多、采食不足或存在拒食倾向时，降低增量或暂停升料。 Note: F1, F2 and F3+ stand for first-parity, second-parity and third-parity and above sows respectively. During the ramp-up feed escalation period, the daily feeding amount is adjusted upward from the previous day's baseline, according to the previous day's intake completion and residual feed in the trough, within the parity-specific increment range: the upper limit of the increment is used when feed intake is sufficient with little leftover; while a reduced increment or suspended escalation is adopted when there is excessive residual feed, insufficient intake or anorexia tendency.
产后适应期 Postpartum adaptation	1～2	1.5～2.3	1.5～2.5	1.5～2.5
递增升料期 Ramp-up feeding	3～7	每日递增 0.4～0.7	每日递增 0.5～0.8	每日递增 0.8～1.0
高峰期 Peak	8～14	5.0～6.0	5.5～6.5	6.5–7.5
高峰维持期 Peak maintenance	15～断奶	6.0～6.5	6.5～7.0	7.5～8.0

阶段
Stage

泌乳日龄
Lactation day/d

F1/
(kg·d^-1)

F2/
(kg·d^-1)

F3+/
(kg·d^-1)

注：F1、F2、F3+分别代表头胎、二胎及三胎及以上母猪。递增升料阶段，系统以前一日基础饲喂量为基数，结合前一日采食完成度与料槽剩料量，在各胎次对应增量区间内上调当日饲喂量：前一日采食充分、剩料少时取区间上限增量，剩料较多、采食不足或存在拒食倾向时，降低增量或暂停升料。
Note: F1, F2 and F3+ stand for first-parity, second-parity and third-parity and above sows respectively. During the ramp-up feed escalation period, the daily feeding amount is adjusted upward from the previous day's baseline, according to the previous day's intake completion and residual feed in the trough, within the parity-specific increment range: the upper limit of the increment is used when feed intake is sufficient with little leftover; while a reduced increment or suspended escalation is adopted when there is excessive residual feed, insufficient intake or anorexia tendency.

产后适应期
Postpartum adaptation

1～2

1.5～2.3

1.5～2.5

递增升料期
Ramp-up feeding

3～7

每日递增
0.4～0.7

每日递增
0.5～0.8

每日递增
0.8～1.0

高峰期
Peak

8～14

5.0～6.0

5.5～6.5

6.5–7.5

高峰维持期
Peak maintenance

15～断奶

6.0～6.5

6.5～7.0

7.5～8.0

阶段 Stage	泌乳日龄 Lactation day/d	F1/ (kg·d^-1)	F2/ (kg·d^-1)	F3+/ (kg·d^-1)
注：F1、F2、F3+分别代表头胎、二胎及三胎及以上母猪。递增升料阶段，系统以前一日基础饲喂量为基数，结合前一日采食完成度与料槽剩料量，在各胎次对应增量区间内上调当日饲喂量：前一日采食充分、剩料少时取区间上限增量，剩料较多、采食不足或存在拒食倾向时，降低增量或暂停升料。 Note: F1, F2 and F3+ stand for first-parity, second-parity and third-parity and above sows respectively. During the ramp-up feed escalation period, the daily feeding amount is adjusted upward from the previous day's baseline, according to the previous day's intake completion and residual feed in the trough, within the parity-specific increment range: the upper limit of the increment is used when feed intake is sufficient with little leftover; while a reduced increment or suspended escalation is adopted when there is excessive residual feed, insufficient intake or anorexia tendency.
产后适应期 Postpartum adaptation	1～2	1.5～2.3	1.5～2.5	1.5～2.5
递增升料期 Ramp-up feeding	3～7	每日递增 0.4～0.7	每日递增 0.5～0.8	每日递增 0.8～1.0
高峰期 Peak	8～14	5.0～6.0	5.5～6.5	6.5–7.5
高峰维持期 Peak maintenance	15～断奶	6.0～6.5	6.5～7.0	7.5～8.0

阶段
Stage

泌乳日龄
Lactation day/d

F1/
(kg·d^-1)

F2/
(kg·d^-1)

F3+/
(kg·d^-1)

产后适应期
Postpartum adaptation

1～2

1.5～2.3

1.5～2.5

递增升料期
Ramp-up feeding

3～7

每日递增
0.4～0.7

每日递增
0.5～0.8

每日递增
0.8～1.0

高峰期
Peak

8～14

5.0～6.0

5.5～6.5

6.5–7.5

高峰维持期
Peak maintenance

15～断奶

6.0～6.5

6.5～7.0

7.5～8.0

分组 Grouping	总产仔数 Total born	每窝总产仔数 Total born per litter	断奶–发情间隔 Weaning-to-estrus interval /d	断奶配种率 Wean-to-service rate /%
注：同一指标数据肩标相同或无字母表示差异不显著（P＞0.05）；不同小写字母表示显著差异（P＜0.05）；不同大写字母表示极显著差异（P＜0.01）。下同。 Note: The same indicator values with no letter or the same letter superscripts mean no significant difference (P＞0.05); Different lowercase and uppercase indicate significant (P＜0.05) and remarkable difference (P＜0.01) among treatments, respectively. The same below.
TFG	509	12.82 ± 1.48^a	9.04 ± 1.21^A	85
IFG	502	12.59 ± 2.15^a	8.15 ± 1.60^B	90

分组
Grouping

总产仔数
Total born

每窝总产仔数
Total born per litter

断奶–发情间隔
Weaning-to-estrus
interval /d

断奶配种率
Wean-to-service
rate /%

注：同一指标数据肩标相同或无字母表示差异不显著（P＞0.05）；不同小写字母表示显著差异（P＜0.05）；不同大写字母表示极显著差异（P＜0.01）。下同。
Note: The same indicator values with no letter or the same letter superscripts mean no significant difference (P＞0.05); Different lowercase and uppercase indicate significant (P＜0.05) and remarkable difference (P＜0.01) among treatments, respectively. The same below.

TFG

509

12.82 ± 1.48^a

9.04 ± 1.21^A

IFG

502

12.59 ± 2.15^a

8.15 ± 1.60^B

分组 Grouping	总产仔数 Total born	每窝总产仔数 Total born per litter	断奶–发情间隔 Weaning-to-estrus interval /d	断奶配种率 Wean-to-service rate /%
注：同一指标数据肩标相同或无字母表示差异不显著（P＞0.05）；不同小写字母表示显著差异（P＜0.05）；不同大写字母表示极显著差异（P＜0.01）。下同。 Note: The same indicator values with no letter or the same letter superscripts mean no significant difference (P＞0.05); Different lowercase and uppercase indicate significant (P＜0.05) and remarkable difference (P＜0.01) among treatments, respectively. The same below.
TFG	509	12.82 ± 1.48^a	9.04 ± 1.21^A	85
IFG	502	12.59 ± 2.15^a	8.15 ± 1.60^B	90

分组
Grouping

总产仔数
Total born

每窝总产仔数
Total born per litter

断奶–发情间隔
Weaning-to-estrus
interval /d

断奶配种率
Wean-to-service
rate /%

TFG

509

12.82 ± 1.48^a

9.04 ± 1.21^A

IFG

502

12.59 ± 2.15^a

8.15 ± 1.60^B

指标 Index	TFG	IFG
初生个体体重均值 Mean birth weight/kg	1.21 ± 0.19^a	1.22 ± 0.20^a
断奶体重均值 Mean weaning weight/kg	7.30 ± 1.00^A	7.68 ± 1.05^B
断奶增重均值 Pre-weaning weight gain/kg 仔猪成活率	6.06 ± 0.92^a	6.47 ± 0.98^b
Pre-weaning survival rate/%	89.13	92.06

指标 Index

TFG

IFG

初生个体体重均值
Mean birth weight/kg

1.21 ± 0.19^a

1.22 ± 0.20^a

断奶体重均值
Mean weaning weight/kg

7.30 ± 1.00^A

7.68 ± 1.05^B

断奶增重均值
Pre-weaning weight gain/kg
仔猪成活率

6.06 ± 0.92^a

6.47 ± 0.98^b

Pre-weaning survival rate/%

89.13

92.06

指标 Index	TFG	IFG
初生个体体重均值 Mean birth weight/kg	1.21 ± 0.19^a	1.22 ± 0.20^a
断奶体重均值 Mean weaning weight/kg	7.30 ± 1.00^A	7.68 ± 1.05^B
断奶增重均值 Pre-weaning weight gain/kg 仔猪成活率	6.06 ± 0.92^a	6.47 ± 0.98^b
Pre-weaning survival rate/%	89.13	92.06

指标 Index

TFG

IFG

初生个体体重均值
Mean birth weight/kg

1.21 ± 0.19^a

1.22 ± 0.20^a

断奶体重均值
Mean weaning weight/kg

7.30 ± 1.00^A

7.68 ± 1.05^B

断奶增重均值
Pre-weaning weight gain/kg
仔猪成活率

6.06 ± 0.92^a

6.47 ± 0.98^b

Pre-weaning survival rate/%

89.13

92.06

指标 Index	五餐组 5-meal	四餐组 4-meal	其他传统饲喂组 Other TFG
窝均有效仔 Mean number of viable piglets per litter	13.90 ± 1.02^A	14.25 ± 0.98^A	12.69 ± 1.35^B
窝均断奶数 Mean number of weaned piglets per litter	12.39 ± 0.91^a	12.42 ± 0.88^a	11.28 ± 1.12^b
断奶数 Total number of weaned piglets	731	733	730
断奶体重均值 Mean weaning weight/kg	7.46 ± 0.52^a	7.44 ± 0.48^a	7.31 ± 0.59^a
断奶窝体重 Mean litter weaning weight/kg	90.65 ± 5.32^a	90.99 ± 5.48^a	89.66 ± 6.02a
成活率 Pre-weaning survival rate /%	92.32	91.98	90.21

指标
Index

五餐组
5-meal

四餐组
4-meal

其他传统
饲喂组
Other TFG

窝均有效仔
Mean number of viable
piglets per litter

13.90 ± 1.02^A

14.25 ± 0.98^A

12.69 ± 1.35^B

窝均断奶数
Mean number of weaned
piglets per litter

12.39 ± 0.91^a

12.42 ± 0.88^a

11.28 ± 1.12^b

断奶数
Total number of weaned piglets

731

733

730

断奶体重均值
Mean weaning weight/kg

7.46 ± 0.52^a

7.44 ± 0.48^a

7.31 ± 0.59^a

断奶窝体重
Mean litter weaning weight/kg

90.65 ± 5.32^a

90.99 ± 5.48^a

89.66 ± 6.02a

成活率
Pre-weaning survival rate /%

92.32

91.98

90.21

指标 Index	五餐组 5-meal	四餐组 4-meal	其他传统饲喂组 Other TFG
窝均有效仔 Mean number of viable piglets per litter	13.90 ± 1.02^A	14.25 ± 0.98^A	12.69 ± 1.35^B
窝均断奶数 Mean number of weaned piglets per litter	12.39 ± 0.91^a	12.42 ± 0.88^a	11.28 ± 1.12^b
断奶数 Total number of weaned piglets	731	733	730
断奶体重均值 Mean weaning weight/kg	7.46 ± 0.52^a	7.44 ± 0.48^a	7.31 ± 0.59^a
断奶窝体重 Mean litter weaning weight/kg	90.65 ± 5.32^a	90.99 ± 5.48^a	89.66 ± 6.02a
成活率 Pre-weaning survival rate /%	92.32	91.98	90.21

指标
Index

五餐组
5-meal

四餐组
4-meal

其他传统
饲喂组
Other TFG

窝均有效仔
Mean number of viable
piglets per litter

13.90 ± 1.02^A

14.25 ± 0.98^A

12.69 ± 1.35^B

窝均断奶数
Mean number of weaned
piglets per litter

12.39 ± 0.91^a

12.42 ± 0.88^a

11.28 ± 1.12^b

断奶数
Total number of weaned piglets

731

733

730

断奶体重均值
Mean weaning weight/kg

7.46 ± 0.52^a

7.44 ± 0.48^a

7.31 ± 0.59^a

断奶窝体重
Mean litter weaning weight/kg

90.65 ± 5.32^a

90.99 ± 5.48^a

89.66 ± 6.02a

成活率
Pre-weaning survival rate /%

92.32

91.98

90.21

智能分阶段饲喂系统对哺乳母猪生产性能的影响

PDF下载

丁元立 , 汤政 , 严泽 , 周梦婷 ^* , 熊本海 , 唐湘方

农业工程学报 | 智慧养殖技术与智能畜牧装备专题(2)：智能装备与环境工程 2026,42(12): 1-9

收起

农业工程学报 |智慧养殖技术与智能畜牧装备专题(2)：智能装备与环境工程 2026 , 42 (12) : 1 -9

智能分阶段饲喂系统对哺乳母猪生产性能的影响

全屏

[Author(id=1300032412432486651, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=18904588663@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1300032412499595517, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032412432486651, language=EN, stringName=Yuanli DING, firstName=Yuanli, middleName=null, lastName=DING, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1300032412575092990, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032412432486651, language=CN, stringName=丁元立, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国农业科学院北京畜牧兽医研究所，北京 100083, bio={"content":"

丁元立，研究方向为智慧畜牧。Email：18904588663@163.com

"}, bioImg=null, bioContent=

丁元立，研究方向为智慧畜牧。Email：18904588663@163.com

, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1300032412336017655, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, xref=null, ext=[AuthorCompanyExt(id=1300032412348600568, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China), AuthorCompanyExt(id=1300032412356989177, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国农业科学院北京畜牧兽医研究所，北京 100083)])]), Author(id=1300032412633813248, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1300032412705116418, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032412633813248, language=EN, stringName=Zheng TANG, firstName=Zheng, middleName=null, lastName=TANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1300032412789002499, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032412633813248, language=CN, stringName=汤政, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国农业科学院北京畜牧兽医研究所，北京 100083, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1300032412336017655, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, xref=null, ext=[AuthorCompanyExt(id=1300032412348600568, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China), AuthorCompanyExt(id=1300032412356989177, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国农业科学院北京畜牧兽医研究所，北京 100083)])]), Author(id=1300032412864499973, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1300032412935803143, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032412864499973, language=EN, stringName=Ze YAN, firstName=Ze, middleName=null, lastName=YAN, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1300032413028077832, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032412864499973, language=CN, stringName=严泽, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国农业科学院北京畜牧兽医研究所，北京 100083, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1300032412336017655, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, xref=null, ext=[AuthorCompanyExt(id=1300032412348600568, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China), AuthorCompanyExt(id=1300032412356989177, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国农业科学院北京畜牧兽医研究所，北京 100083)])]), Author(id=1300032413095186698, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=zhoumengting@caas.cn, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1300032413162295564, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032413095186698, language=EN, stringName=Mengting ZHOU, firstName=Mengting, middleName=null, lastName=ZHOU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^*, address=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1300032413212627213, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032413095186698, language=CN, stringName=周梦婷, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^*, address=中国农业科学院北京畜牧兽医研究所，北京 100083, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1300032412336017655, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, xref=null, ext=[AuthorCompanyExt(id=1300032412348600568, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China), AuthorCompanyExt(id=1300032412356989177, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国农业科学院北京畜牧兽医研究所，北京 100083)])]), Author(id=1300032413279736079, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1300032413346844945, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032413279736079, language=EN, stringName=Benhai XIONG, firstName=Benhai, middleName=null, lastName=XIONG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1300032413418148114, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032413279736079, language=CN, stringName=熊本海, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国农业科学院北京畜牧兽医研究所，北京 100083, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1300032412336017655, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, xref=null, ext=[AuthorCompanyExt(id=1300032412348600568, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China), AuthorCompanyExt(id=1300032412356989177, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国农业科学院北京畜牧兽医研究所，北京 100083)])]), Author(id=1300032413502034196, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, orderNo=5, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1300032413564948758, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032413502034196, language=EN, stringName=Xiangfang TANG, firstName=Xiangfang, middleName=null, lastName=TANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1300032413632057623, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, authorId=1300032413502034196, language=CN, stringName=唐湘方, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中国农业科学院北京畜牧兽医研究所，北京 100083, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1300032412336017655, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, xref=null, ext=[AuthorCompanyExt(id=1300032412348600568, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China), AuthorCompanyExt(id=1300032412356989177, tenantId=1146029695717560320, journalId=1296125453100220459, articleId=1297211712873189655, companyId=1300032412336017655, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=中国农业科学院北京畜牧兽医研究所，北京 100083)])])]

丁元立, 汤政, 严泽, 周梦婷^*, 熊本海, 唐湘方

作者信息

中国农业科学院北京畜牧兽医研究所，北京 100083

通讯作者:

周梦婷，博士，助理研究员，研究方向为智慧畜牧工程。Email：zhoumengting@caas.cn

作者简介:

丁元立，研究方向为智慧畜牧。Email：18904588663@163.com

Effects of intelligent phased feeding system on the productive performance of lactating sows

Yuanli DING, Zheng TANG, Ze YAN, Mengting ZHOU^*, Benhai XIONG, Xiangfang TANG

Affiliations

Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100083, China

出版时间: 2026-06-30 doi: 10.11975/j.issn.1002-6819.202511127

文章导航

摘要

收起

针对哺乳母猪饲喂过程中普遍存在的采食控制粗放，以及因拱食行为导致的饲料浪费严重等问题，该研究采用“两阶段递进式”试验设计，系统评估智能分阶段饲喂系统对母猪采食、体况、繁殖效率及仔猪生长性能的影响，并筛选系统关键运行参数。首先，选取94头经产母猪随机分为智能饲喂组与传统饲喂组，探究智能饲喂器的优势；其次，在两个智能饲喂单元中设置不同“餐次×水料比”参数组合（“五餐制×水料比1.3:1”和“四餐制×水料比1.5:1”），比较不同“餐次×水料比”组合对系统运行效果的影响，探究不同能量供给模式的影响。试验结果显示：与传统组（背膘损失2.61 mm）相比，智能饲喂组（背膘损失1.69 mm）在泌乳后期（分娩15 d后）日采食量提高约5%～10%；背膘损失极显著降低（P＜0.01），平均减少0.92 mm，降幅达35.2%；繁殖性能方面，断奶—发情间隔由传统组的9.04 d缩短至智能饲喂组的8.15 d（P＜0.01），缩短了0.89 d；断奶配种率由85%提升至90%，提高了5个百分点。仔猪方面，断奶当日体重均值由7.30 kg增至7.68 kg（P＜0.01），断奶增重均值由6.06 kg增至6.47 kg（P＜0.05），均显著提高；相较于“四餐制×水料比1.5:1”组合，“五餐制×水料比1.3:1”组合在泌乳中后期（12～21 d）维持了更高、更持久的采食平台，回落更缓，且母猪背膘损失分布更集中、极端流失风险更低。综上所述，智能饲喂系统通过其“个体触发补料”机制，在“分阶段供给”的基础上实现了精准的个体化饲喂，有效提升了母猪采食量、体况维持能力和繁殖表现，并带动仔猪生长性能的提升。其中，“五餐制×水料比1.3:1”是泌乳中后期的优选参数组合。该智能饲喂系统通过精准匹配母猪个体营养需求，能有效提升采食效率、维持母猪体况、改善繁殖性能与仔猪生长表现。研究结果可为规模化猪场实现节本增效与动物福利提升提供关键技术支撑。

关键词

智能饲喂 / 哺乳母猪 / 采食行为 / 生产性能 / 精准营养

Abstract

收起

Conventional feeding of lactating sows in commercial farrowing units was often constrained by coarse feed control, fixed meal timing, and feed losses caused by rooting and manipulation at the trough. These limitations frequently resulted in unstable feed intake during mid- to late lactation, which in turn increased the likelihood of excessive body-reserve mobilization and delayed reproductive recovery after weaning. To address these problems, this study adopted a two-stage progressive experimental design to systematically evaluate the effects of an intelligent precision feeding system on sow feed intake, body condition, reproductive efficiency, and piglet growth performance, and to identify key operating parameters. The study was conducted in a commercial farrowing facility in Shaanxi, China, from March to June 2025. The intelligent feeding unit integrated controlled-dose dispensing with event-based data logging and a trigger mechanism that delivered small top-up portions when trough residual feed and short-window interaction signals indicated persistent feeding motivation; a water–feed mixing option was implemented through a water-control module. Daily feed intake and daily water consumption were recorded automatically. Sow body condition was assessed using backfat thickness measured at entry to the farrowing crate and at weaning. Reproductive recovery and piglet performance traits were obtained from the farm production-record system. In Experiment I, ninety-four multiparous sows were allocated to an Intelligent Feeding Group (IFG) or a Traditional Feeding Group (TFG) (47 sows per unit) housed in environmentally comparable units. IFG sows were managed using the hybrid logic combining a stage-wise baseline allowance with sow-initiated triggered top-ups, whereas TFG sows were fed with a conventional dry-feed feeder at fixed times (three meals per day). The intelligent system produced more stable intake trajectories, and the clearest separation between treatments emerged during mid- to late lactation. From approximately day 15 postpartum onward, daily feed intake in IFG exceeded that of TFG by about 5%-10%, reflecting a more sustained intake plateau and a later decline toward the end of lactation. Consistent with improved intake stability, body-reserve mobilization was reduced in IFG as indicated by backfat change: mean backfat loss decreased from 2.61 mm in TFG to 1.69 mm in IFG (P<0.01), corresponding to a 35.2% reduction. Reproductive recovery was accelerated in IFG. The weaning-to-estrus interval (WEI) shortened from 9.04 days (TFG) to 8.15 days (IFG) (P<0.01), and the wean-to-service rate increased from 85% to 90%. Piglet outcomes also improved in association with the stabilized maternal intake pattern: average weaning weight increased from 7.30 kg (TFG) to 7.68 kg (IFG) (P<0.01), pre-weaning weight gain rose from 6.06 to 6.47 kg (P<0.05), and pre-weaning survival increased from 89.13% to 92.06%. Together, these results indicated that the intelligent feeding approach supported higher and more persistent feed intake during late lactation and aligned with improved body-condition preservation and superior reproductive and litter performance. In Experiment II, parameter screening was performed within two units equipped with the intelligent feeding system to compare two deployable “meal frequency × dilution” strategies under identical hybrid logic. A five-meal strategy with a water-to-feed ratio of 1.3:1 during mid- to late lactation was compared with a four-meal strategy with a water-to-feed ratio of 1.5:1. The five-meal strategy with a water-to-feed ratio of 1.3:1 maintained a higher and more persistent intake plateau between days 12 and 21 postpartum and delayed the late-lactation decline compared with the four-meal strategy with a water-to-feed ratio of 1.5:1. Daily water consumption showed a similar temporal pattern, with a sharper late-lactation decline under the four-meal strategy with a water-to-feed ratio of 1.5:1. Backfat-change outcomes during parameter screening were consistent with these temporal intake differences. The five-meal strategy with a water-to-feed ratio of 1.3:1 showed a more favorable backfat-loss profile, with smaller loss and a more concentrated distribution with fewer extreme negative values. Because meal frequency and water-to-feed ratio were coupled in this screening comparison, mechanistic interpretation was limited to the combined strategy rather than isolated main effects. In conclusion, a sensor-based, trigger-activated phased precision feeding approach provides a practical and traceable framework for stabilizing feed and water intake during mid- to late lactation in commercial farrowing systems. This approach reduces body-reserve mobilization, as indicated by lower backfat loss, supports faster post-weaning reproductive recovery, and improves piglet growth and survival under the tested conditions. Within the evaluated operating settings, the five-meal strategy with a water-to-feed ratio of 1.3:1 represents a promising deployable configuration for sustaining the late-lactation intake plateau and mitigating the end-of-lactation decline in intensive swine production.

Key words

intelligent feeding / lactating sows / feeding behavior / productive performance / precision nutrition

引用本文

丁元立, 汤政, 严泽, 周梦婷, 熊本海, 唐湘方. 智能分阶段饲喂系统对哺乳母猪生产性能的影响. 农业工程学报, 2026 , 42 (12) : 1 -9 . DOI: 10.11975/j.issn.1002-6819.202511127

Yuanli DING, Zheng TANG, Ze YAN, Mengting ZHOU, Benhai XIONG, Xiangfang TANG. Effects of intelligent phased feeding system on the productive performance of lactating sows[J]. Transactions of the Chinese Society of Agricultural Engineering, 2026 , 42 (12) : 1 -9 . DOI: 10.11975/j.issn.1002-6819.202511127

正文

收起

0　引言

收起

哺乳期是母猪一生中营养需求最为旺盛、体况损失风险最高的关键阶段，直接关系到母猪繁殖效率、仔猪生长性能与猪场经济效益^[1-3]。受分娩应激、激素波动及胃肠功能不稳等影响，哺乳母猪普遍存在采食不足与负能量平衡，加剧背膘流失并延长断奶至发情间隔，进一步降低配种成功率与使用年限^[4-5]。KOKETSU和DIAL^[6]的长期跟踪数据早已证实，哺乳期背膘损失每增加1 mm，断奶发情延迟约1 d，每头母猪年提供断奶仔猪数（piglets per sow per year，PSY）下降0.6头，凸显了体况维持对繁殖性能的有效作用。因此，如何在真实生产场景下实现“按阶段—按个体”的营养精准匹配，已成为现代规模化养猪的核心技术难题之一。

母猪精准饲喂技术最早源于20世纪90年代欧美国家对妊娠母猪群养系统的探索^[7]。早期的电子饲喂站（electronic sow feeding，ESF）主要应用于妊娠母猪的个体识别与定量饲喂，通过射频识别（radio frequency identification，RFID）实现母猪身份识别，根据胎次和体况设定固定饲喂曲线^[8]。进入21世纪后，随着传感器技术和数据分析能力的提升，精准饲喂理念逐渐从妊娠期延伸至哺乳期。DOURMAD等^[9]开发的InraPorc模型首次建立了基于母猪营养需求动态预测的决策支持系统，为后续精准饲喂技术奠定了理论基础。

近年来，智能分阶段饲喂系统在装备研发与策略优化上均取得显著进展。在装备研发方面，熊本海等^[10-11]与王美芝等^[12]均已成功研发了精确下料的智能装备。其中，熊本海团队研发的智能饲喂系统可使哺乳母猪日采食量提高7.8%、断奶仔猪窝重增加11.2%，并有效降低母猪背膘损失；王美芝团队的相关研究也验证了智能饲喂装备在提升母猪采食性能、维持体况方面的应用价值。然而，现有研究多聚焦于装备本身的应用效果验证，对系统内部多参数（如餐次、水料比、饲喂时间分布等）的交互效应缺乏系统评价^[13]。在精准饲喂策略方面，GAUTHIER等^[14]已开发出先进的决策支持系统，该系统能结合机器学习算法实时预测采食量并动态调整日粮。尽管如此，这类精准饲喂模型多基于群体平均数据建立，对个体差异（如初产与经产、高低采食母猪）的适应性仍需完善^[15-16]。此外，尽管最新研究显示电子饲喂器能显著提高断奶仔猪体重均值并降低单位饲料消耗（P＜0.05），但大多数研究仍局限于评估母猪泌乳期表现，而对后续母猪繁殖周期及仔猪后期生长性能的长期追踪研究较为有限^{[10, 17]}。

现有研究多以验证装备功能为目标，鲜少围绕运行参数开展系统优化。因此，针对当前哺乳母猪智能饲喂研究多聚焦装备效果验证、缺乏系统参数优化的问题，本研究基于现有智能饲喂平台，采用两阶段递进式试验设计，系统评估智能饲喂模式在全繁殖周期的长期效果，并探究关键运行参数对不同胎次及采食水平母猪的适配规律。第一阶段通过与传统饲喂模式对比，明确智能饲喂系统对母猪采食、体况、泌乳及繁殖性能的改善作用；第二阶段设置不同餐次频率与水料比组合，解析关键参数对饲喂系统稳定性及生产效益的影响，筛选适配规模化猪场的最优参数组合。

1　材料与方法

收起

1.1　试验猪舍基本情况

本研究于 2025年3月26日至6月10日在陕西某规模化猪场开展，试验一数据采集时间为3月26日到4月25日，共30 d；试验二数据采集时间为5月10日到6月9日，共30 d。

如图1所示，试验猪舍为轻钢结构密闭式建筑，长轴近南北，单栋外檐约78.0 m×16.0 m，檐高与脊高约3.2 m与4.8 m；侧墙设0.90 m×1.20 m高窗（间距约6.0 m，常闭为主），地面为防滑处理混凝土，猪栏靠墙为钢铁漏缝地板，宽1.2 m。夏季采用“湿帘–负压风机”纵向通风：进风端布置3片纤维湿帘（高1.8 m、宽3.0 m、厚150 mm），排风端配置直径1.4 m负压风机8台。产栏规格为2.25 m×1.80 m，列间通道0.80 m，母猪限位架前端设置饲槽；场内常规饲喂设备为干料自动投喂器，用于对照组的定时投喂（每日3餐，分别于08:00、12:00、17:00投喂）；智能饲喂器安装在限位架前端中央，饲槽中心距地约0.42 m，距限位架前端约0.35 m。试验一在同栋分娩舍内选择环境条件一致的2个单元，各配47头经产母猪；试验二在同类型分娩舍内选择2个单元，每单元各57头，其余建筑、通风、清粪与基础设施设置均保持一致。

1.2　智能饲喂器整体结构

1.2.1　智能饲喂器硬件组成与单栏协同控制

智能饲喂器由上置透明料筒、定量下料驱动单元FD-1、料路与防堵结构、控水组件（流量计+电磁阀）、供电与人机交互模块以及清洗与防护结构集成构成，总体结构与现场安装如图2所示。FD-1内置微控制单元（microcontroller unit，MCU）一体化控制板，配合24位称重采样与电机驱动，实现“称重反馈—电机驱动—闸板投料”的闭环定量下料；系统支持低采食报警与异常自检（如堵料/缺料/超时等），并可按设定饲喂逻辑执行餐次、单次配给量与（可选）水料比等参数。料路采用“上置料筒—定量机构—落料口”的封闭式通道，并配置破拱/振动、防回流与防潮设计，以适配颗粒/粉料并降低架桥与粉尘外溢风险。除饲喂外，该装置可与单栏饮水与保温设备联动，形成“饲喂—饮水—保温”协同控制的单栏微环境单元。整机采用AC110–264 V、50 Hz供电，投料功率约120 W，可在−10～50 ℃环境下稳定运行；关键电气部件达到IP67防护等级，支持高压水清洗，便于猪舍日常维护。

1.2.2　个体识别与数据闭环

为实现母猪个体化、可追溯管理，系统通过RFID耳标读头读取耳标号作为个体索引，将投料、饮水与设备状态等运行事件与时间戳绑定记录，并在网页端提供按耳号/栏位/日期的检索与汇总展示（图3）。平台记录字段包括日/次级采食目标与实际采食量、饮水目标与实际饮水量及达标率，并支持“详情”追溯与数据导出，用于远程巡检与后续统计分析。通过“个体索引—事件记录—平台查询/导出”的链路，使装置不仅实现精准下料与协同控制，也具备数据闭环与可追溯能力。

1.3　智能饲喂器工作原理

本系统采用“分阶段基础方案”与“个体触发补料”相结合的混合饲喂逻辑运行，其核心决策机制如下：

分阶段基础方案：系统内置“四段式”的基础饲喂方案，用于在泌乳进程中提供与生理需求相匹配的基础供给：产后适应期（受控低基础量），递增升料期（基础量逐日上调），高峰期（高基础供给并允许个体触发补充）以及高峰维持期（维持高基础供给并允许个体触发）。系统根据母猪胎次分组头胎（F1）、二胎（F2）、三胎及以上（F3+），并结合泌乳日龄自动匹配相应阶段的基础供给范围（表1），并据此生成当日基础供给量及日内投喂调度参数。

个体触发补料：在“基础方案”设定的定时餐次之外，系统以触发式小剂量补料为辅，以满足高产或高采食个体的额外需求。其核心判据为“当料槽剩余低于阈值（如料槽剩余小于100 g）且母猪短时间内（如2 min内）触碰传感器达到设定次数（如大于3次）”，即触发补料（如250～300 g/次）。同时设置冷却时间（如超过15 min）与当日补料占比上限（如基础量的15%）以抑制下料过量。上述参数为本研究场景下的工程化配置：剩料阈值用于识别“接近采食完成/出现缺料”状态，并为料面堆积与称重波动预留余量以降低误判；时间窗与触碰次数用于筛选短时连续行为、过滤偶发触碰，从而抑制误触发；以小剂量方式补足需求并减少堆料拥塞；冷却时间与补料上限用于限制触发频率与累积补料量，避免异常工况下触发放大并提升运行安全性。

辅助调度与保护：系统可依据泌乳阶段动态调整水料比，兼顾饲料适口性与采食效率。当系统判定出现母猪拒食、分娩当日等生理异常，或设备离线、通信中断等工况异常时，自动切换至保护运行模式（仅保留“基础方案”中的定时餐次，暂停补料与水比上调）。

数据闭环：所有投喂、补料、饮水及个体触发事件均记录完整时间戳，每日结束时根据剩料与行为数据对次日基础方案的供给量进行动态调整，从而实现“分阶段足量供给、个体化差异补偿”的控制目标。

1.4　试验猪只及其饲喂管理

本研究选用体重为（234.80 ± 16.21） kg、生理状态良好、采食量正常的同一猪场同批次经产母猪作为试验对象。试验一共纳入94头分娩期经产母猪，于预产前4 d转入分娩舍内限位栏，分配至智能饲喂组（intelligent feeding group，IFG）与传统饲喂组（traditional feeding group， TFG）各 1 个单元，每个单元各47头；试验二在同类型分娩舍内另选2个环境条件相近的单元，每个单元各 57 头，均配备智能饲喂系统，但实施不同的“餐次×水料比”参数组合，为进一步评估系统优势，试验同期亦收集了舍内采用传统饲喂器的其他单元生产数据作为对照。

具体试验参数如下：试验一（基础验证试验）： IFG组母猪应用 1.3 节所述的“混合饲喂逻辑”，其具体的补料判据参数设置为：“料槽残量小于100 g且2 min内触碰大于3次”即补料250～300 g/次，冷却时间超过15 min，当日补料不超过基础量15%。餐次由2餐过渡至3餐、4餐；为排除料型影响，水料比固定1:1。试验二（参数优化试验）中两单元均采用与试验一IFG组完全相同的核心饲喂逻辑，仅改变“餐次×水料比”组合，五餐组（5-meal）投喂时间及对应饲喂量分配比例分别为03:00（10%）、07:15（30%）、11:00（15%）、17:00（30%）、21:00（15%），泌乳中后期（分娩后第9天到断奶）水料比调整为1.3:1；四餐组（4-meal）投喂时间及对应饲喂量分配比例分别为07:15（30%）、11:00（20%）、17:00（20%）、21:00（30%），泌乳中后期水料比调整为1.5:1。需要说明的是，试验二的目的为在商业化条件下对“餐次×水料比”的可部署策略组合进行对比筛选，而非开展完整的因子设计。受限于同期生产安排与可用于对照的独立单元数量，本轮仅选取两种兼具现场代表性与可操作性的组合（较高餐次/较低水料比与较低餐次/较高水料比）进行对比，以在可比性与统计效力之间取得平衡；其余餐次或水料比组合将在后续试验中通过更系统的设计进一步验证。

1.5　数据监测

试验过程中各项数据均通过智能饲喂与环境监测系统自动采集，并辅以人工复核。采食数据由饲喂器自带称重与料盒质量检测模块按投喂/采食事件记录，字段包括母猪耳号、栏位号、采食开始与结束时间、单次下料量、餐次编号、下料次数及料盒前后质量等；在此基础上，系统将每头猪每日采食事件汇总为日采食量（kg/d）。为保证可追溯性与运行一致性核验，平台/设备端同时保存系统自动生成的当日投喂计划参数（如当日目标供给量及相关阈值、单次下料量与水料比等），并与耳号及时间戳绑定，可在平台端查询与导出（图3）。饮水数据由流量传感器记录进水与溢流量，按24 h汇总为每头猪日饮水量（L/d）。背膘厚度采用超声背膘仪（GDF-C50）在上床及断奶时各测一次，计算背膘损失。繁殖性能数据（总产仔数、断奶活仔数、断奶－发情间隔、断奶配种率）及仔猪生长性能（初生重、断奶重、增重、成活率）由生产记录系统导出。

数据清洗过程中剔除了采食量、饮水量或背膘为 0 或负值的异常记录。料盒前后质量差异与下料量不符、同一时刻多猪共食、秤体漂移等异常事件通过“事件持续时长 × 进食速率”阈值法及“体重突变检测”规则识别并剔除。对连续变量采用四分位距法（interquartile range，IQR）标记极端值，经复核后删除或限幅（winsorize）处理^[18-19]。缺测日龄数据以相邻有效值线性插补，仅用于连续性曲线，不参与显著性分析^[20]。主要指标计算如下：

1）采食与体况指标

$ \mathit{A}=\sum\limits_{i=1}^n\, W_i $

(1)

式中A为每头猪每日采食量，单位：kg/d；n为当日有效下料次数；

$ {W}_{i} $

为第i次有效下料量（kg）。背膘损失为断奶时背膘厚度与上床时背膘厚度之差，单位为mm，背膘减少记为负值、增加记为正值。

2）仔猪生长性能指标

本研究从生产记录中计算母猪繁殖性能及仔猪生长性能指标。仔猪生长性能指标包括：窝均有效仔数、初生头体重均值、断奶体重均值、断奶增重、窝均断奶数、断奶窝重及成活率。窝均有效仔数为每窝活产仔猪数的平均值；初生头体重均值和断奶体重均值分别为各窝活产仔猪和断奶仔猪的平均体重；断奶增重为断奶体重均值与初生头体重均值之差；窝均断奶数为每窝断奶仔猪数的平均值；断奶窝重为每窝断奶仔猪的总质量；成活率为断奶仔猪数占活产仔猪数的百分比。

母猪繁殖性能指标包括：窝均总产仔数、断奶—发情间隔及断奶配种率。窝均总产仔数为每窝仔猪总数的平均值（含活产、死胎及木乃伊胎）；断奶—发情间隔为母猪断奶至首次发情的天数；断奶配种率为断奶后7 d内配种母猪占断奶母猪总数的百分比。

1.6　数据分析

数据汇总按“分组或单元×分娩日龄”计算日均值及标准差。分布型指标（如背膘损失）采用核密度估计（kernel density estimation，KDE）与经验累积分布函数（empirical cumulative distribution function，CDF）呈现，时间序列型指标（如采食量、饮水量）采用日均曲线 ± SD 误差带展示。连续变量的显著性检验采用单因素方差分析。

2　结果与分析

收起

2.1　基础验证试验

2.1.1　不同饲喂器对分娩后母猪采食量的影响

试验期间母猪采食量变化如图4所示，两组母猪的日采食量均随分娩天数的增加而逐渐上升，并在分娩后第10～12 d趋于平缓。与传统饲喂组（traditional feeding group，TFG）相比，智能饲喂组（intelligent feeding group，IFG）在整个泌乳期表现出略高的平均采食量，差异主要体现在分娩后期阶段。到泌乳后期（约15 d后），IFG猪只的平均采食量比TFG高 5%～10%且采食平台维持时间更长、回落更晚。这可能是因为智能饲喂系统通过稳定的定量下料减少了栏内竞争，使母猪在泌乳中后期仍能保持较高采食水平，从而维持了更长的采食平台期并延缓了采食量的回落。该变化趋势与GAUTHIER等^[14]的研究结果一致，即在商业化生产条件下，采用电子母猪饲喂系统（electronic sow feeding，ESF）可通过实时感知与个体化精准供给，提高泌乳期母猪整体采食量，并缓解泌乳后期采食量下降幅度。

2.1.2　不同饲喂器对分娩后母猪背膘的影响

背膘损失是评估母猪泌乳期能量负平衡和后续繁殖潜力的关键外在指标，可用于解释母猪断奶后繁殖恢复过程中所呈现的能量状态差异^[21-22]，但该指标并不完全覆盖体重变化、肢体健康及步态特征等物理体况要素^[23]。本研究中背膘变化定义为断奶时背膘厚度与转入产房时背膘厚度之差，其中负值表示背膘损失，正值表示背膘增加。从背膘变化的概率密度曲线（图5a）可以看出两组核密度分布均呈单峰，但IFG相较于TFG整体左移，中心更靠近较小损失区间；其均值为−1.69 mm，显著低于TFG的−2.61 mm（P＜0.01），即平均损失减少约0.92 mm，相对降低 35.2%。经验累积分布（图5b）进一步印证了这一差异：在中位数水平（y=0.50）处，TFG背膘损失约为2.50 mm，IFG背膘损失约为2.00 mm；在背膘变化阈值−2.00 mm和−3.00 mm处，TFG累积概率曲线均高于IFG，表明TFG达到较大背膘损失的个体比例更高。上述结果表明，智能饲喂系统可有效缓解泌乳期能量负平衡，使群体背膘变化分布整体向较小损失区间偏移。本研究结果与APARICIO-ARNAY等^[17]的研究结论一致：母猪电子饲喂对断奶阶段的母猪无体况不利影响，并伴随更低的母猪体重损失、饲料利用率更高。需要说明的是，背膘损失主要表征哺乳期脂肪动员这一能量代谢维度，虽能高度预测繁殖性能，但并不完全覆盖体重变化、肢体健康及步态特征等物理体况要素。受限于商业化猪场生产条件的客观限制，本研究未能同步采集上述多维指标，这将在后续研究中予以完善。

2.1.3　不同饲喂器对分娩后母猪繁殖性能表现

TFG和IFG试验期内母猪的繁殖性能和仔猪生长性能如表2和表3所示，每窝总产仔数两组无显著差异（P＞0.05）；IFG组母猪断奶—发情间隔平均为8.15 d，较TFG组9.04 d平均缩短了0.89 d（P＜0.01）；断奶配种率提高了5个百分点。上述对于繁殖性能的显著改善，与 2.1.2 节中观察到的背膘维持情况（平均少损失0.92 mm）密切相关。背膘是母猪能量平衡的直观指标，过度动员体脂会抑制GnRH/LH等生殖激素分泌，这是导致断奶-发情间隔（weaning-to-estrus interval，WEI）延长的主要生理原因^{[21, 24-26]}。

在仔猪生长性能方面，初生头体重均值无显著差异（P＞0.05）；断奶体重在IFG显著提高（P＜0.01），平均增加0.38 kg；断奶增重亦显著提高（P＜0.05），平均增加0.41 kg；成活率提高了2.93个百分点。上述差异主要归因于IFG组在泌乳期，特别是泌乳后母猪采食与饮水节律更为稳定，能量摄入更充足且波动更小，得以维持较高且稳定的泌乳量^[27-29]，从而为仔猪提供了更持续的营养供给，最终表现为更高的断奶体重、更大的断奶增重及更低的仔猪死亡率。与此同时，IFG组母猪背膘损失显著低于TFG（平均减少0.92 mm，P＜0.01），表明其在保障泌乳输出的同时体组织动员程度较低，能量分配策略更为合理，这也间接支持了泌乳中后期乳量的稳定性。

2.2　智能饲喂参数优化验证

2.2.1　不同“餐次×水料比”对采食量与饮水量的影响

试验期间，不同参数组的日采食量和日饮水量如图6所示。

“五餐组”（5-meal；W_R = 1.3:1）和“四餐组”（4-meal；W_R = 1.5:1）的采食量均在分娩后1～6 d持续上升，6 d左右趋于平缓（7.00～7.50 kg/d）。此后，五餐组在12～21 d的采食量略高于四餐组，峰值约9.30～9.60 kg/d，而四餐组峰值略低（8.80～9.20 kg/d），且在21～24 d出现更早、幅度更大的回落。饮水量随泌乳进程同步增加，12～20 d的饮水量维持在11.50～12.50 L/d；21～24 d，四餐组的饮水量明显下滑（9.00～10.00 L/d），而五餐组的饮水量仍维持在11.00～12.00 L/d。

在核心饲喂逻辑一致的前提下，仅调整“餐次×水料比”参数即可改变哺乳母猪采食与泌乳相关表现：五餐组在泌乳中后期维持了更高、更加持久的采食平台，采食量回落时间更晚。相比之下，四餐组（W_R = 1.5:1）对应更高的水料比，意味着单位湿料的干物质比例更低，可能降低单位体积饲料的营养密度并加快母猪采食速度；同时，较少的餐次也可能限制母猪在日内可利用的采食机会，从而在泌乳中后期更难充分满足其能量与水分需求，表现为采食与饮水同步下降^[30-32]。已有研究显示，餐次减少或水料比升高可能降低单位时间的干物质摄入能力，使泌乳中后期更易出现采食下滑^[32]。总体而言，“五餐制×水料比1.3:1”可使母猪泌乳中后期采食量峰值稳定期延长、采食量下降节点推迟，为母猪背膘维持与仔猪能量供给提供更稳定的营养与水分保障。这一时序差异在背膘变化中亦得到呼应：五餐组背膘损失更小，分布更集中（图7），提示泌乳中后期营养供给更稳定。需要指出的是，试验二旨在评估不同营养供给策略的整体效能，其中餐次频率与水料比采用了耦合设置。尽管本试验设计尚未能完全解耦单一因素的主效应及其交互作用，但“多餐次、较低水料比”组合展现出的采食优势，揭示了营养浓度与进食节律在提升母猪泌乳后期采食稳定性的协同潜力。

2.2.2　不同“餐次×水料比”对母猪背膘变化的影响

由背膘分布曲线（图7a）可见，五餐组与四餐组的背膘变化分布高度重叠，总体以轻度下降为主，均值分别约为−0.69 mm与−0.65 mm。但两组的离散程度存在差异：四餐组在两侧尾部更饱满，背膘极端增加或极端损失的个体比例稍高；五餐组分布则更集中。CDF（图7b）进一步验证：在累积概率水平（y=0.50）附近，两组均落在轻度负向（−0.30～0 mm）区间且几乎重合；在损失超过−3.00 mm的较大损失区间，四餐组曲线略高，表明达到较大流失阈值的累计概率更大；而在正向增厚端超过1.00～2.00 mm，五餐组曲线相对偏低，显示获得较大增厚的比例略高。

在饲喂算法与基础饲养条件保持统一的前提下，仅调整“餐次×水料比”参数，两组背膘变化均值差异较小，但概率密度分布形态存在一定差异。这表明五餐组更有利于收敛个体差异、降低极端背膘流失风险；四餐组则表现为波动性更大。这与前述采食/饮水节律结果一致：更高饲喂频率与较低水料比供应有助于母猪在泌乳中后期维持更稳定的能量平衡，使母猪背膘厚度仅出现小幅波动^{[10, 33]}。

2.2.3　不同“餐次×水料比”对繁殖性能的影响

两组智能饲喂母猪及同批次常规饲喂母猪的生产性能数据如表4所示，五餐组和四餐组窝均有效仔数分别为13.90与14.25，两组均显著高于常规饲喂单元的12.69（P＜0.01）；两组智能饲喂母猪窝均断奶仔猪数无显著差异，但均显著优于常规饲喂单元（P＜0.05）。尽管五餐组与四餐组在“餐次×水料比”配置上存在差异，但两者在窝均断奶数、断奶体重、成活率等生产性状上均无显著差异；整体来看，两类智能饲喂处理的生产性能均优于同批次传统饲喂模式。

值得注意的是，尽管五餐组在采食模式和背膘分布上表现更优，但这并未转化为本胎次仔猪生长性能的显著提升。这可能表明，四餐组的能量供给已基本满足了仔猪的生长阈值。因此，“五餐制×水料比1.3:1”策略的真正优势，可能并非体现在短期的饲料转化效率上，而是体现在对母猪长期繁殖效率的保障上。“多餐少食”通过降低采食热增耗、保持饲料新鲜度，帮助母猪在泌乳后期维持了更稳定的能量平衡^[34-35]，如图7所示，背膘分布更集中、极端流失风险更低。这种更优的体况维持，是缩短断奶发情间隔、提升母猪终生繁殖性能的更可靠保障。

结果表明，在不改变整体饲养环境和管理条件的情况下，智能饲喂策略显著提升了母猪的繁殖效率，仔猪存活数量与窝断奶仔猪数提升效果最为突出。推测其原因在于智能饲喂器系统可精准匹配母猪所需的日粮与饮水供给，提升泌乳母猪能量利用效率，更好的维持母猪的体况、优化采食哺乳行为，从而提高改善仔猪成活率与生长性能。已有多项研究表明，泌乳阶段更高且平稳的能量摄入，与母猪配种成功率、产仔性能及仔猪断奶生长表现呈正相关^[36-37]。

3　结论

收起

1）与传统饲喂器相比，智能饲喂器在泌乳后期（分娩15 d后）将母猪日采食量提高5%～10%，背膘损失极显著降低（P＜0.01）；

2）智能组断奶发情间隔极显著缩短（P＜0.01），母猪断奶配种率由85%提升至90%，仔猪断奶体重极显著提高（P＜0.01），断奶增重显著提高（P＜0.05）；初生重无显著差异，成活率由89.13%提升至92.06%；

3）在核心饲喂逻辑不变的情况下，仅调整"餐次×水料比"各组即表现出差异：五餐组在12～21 d维持更高、更持久的采食平台，并在21～24 d回落更缓；饮水量曲线更平稳。背膘损失均值由0.65 mm增至0.69 mm，两组接近，但相较于四餐组，五餐组的背膘损失分布更集中、极端流失概率更低。

综上所述，智能饲喂系统在不改变饲料配方与基础环境的前提下，实现了采食曲线稳定—背膘保稳—繁殖与哺乳协同提升；其中“五餐制×水料比1.3∶1”表现更佳，建议作为泌乳中后期智能饲喂器的优选参数，为规模化猪场的精准饲喂与效益提升提供数据依据与技术支撑。

参考文献

收起

文献

收起

参考文献引证文献

排序方式：

TOKACH M D, MENEGAT M B, GOURLEY K M, et al. Nutrient requirements of the modern high-producing lactating sow, with an emphasis on amino acid requirements[J]. Animal, 2019, 13(12): 2967-2977.

HUMPHREY D C, GREINER L L. Adjustment of branched-chain amino acid balance fails to prevent feed intake decline in lactating sows fed high soybean meal diets[J]. Journal of Animal Science, 2025, 103: skaf072.

RODRIGUEZ M, DIAZ-AMOR G, MORALES J, et al. Feed intake patterns of modern genetics lactating sows: Characterization and effect of the reproductive parameters[J]. Porcine Health Management, 2023, 9(1): 6.

COSTERMANS N G J, TEERDS K J, MIDDELKOOP A, et al. Consequences of negative energy balance on follicular development and oocyte quality in primiparous sows[J]. Biology of Reproduction, 2020, 102(2): 388-398.

TAYLOR V J. Lactation from the inside out: Maternal homeorhetic gastrointestinal adaptations regulating energy and nutrient flow into milk production[J]. Molecular and Cellular Endocrinology, 2023, 559: 111797.

KOKETSU Y, DIAL G D. Factors influencing the postweaning reproductive performance of sows on commercial farms[J]. Theriogenology, 1997, 47(7): 1445-1461.

赵一广, 杨亮, 郑姗姗, 等. 家畜智能养殖设备和饲喂技术应用研究现状与发展趋势[J]. 智慧农业, 2019, 1(1): 20-31.

ZHAO Yiguang, YANG Liang, ZHENG Shanshan, et al. Advances in the development and applications of intelligente quipment and feeding technology for livestock production[J]. Smart Agriculture, 2019, 1(1): 20-31. (in Chinese with English abstract)

BRESSERS H P M. Monitoring Individual Sows in Group-Housing: Possibilities for Automation[D]. Wageningen: Wageningen University and Research, 1993.

DOURMAD J, ETIENNE M, NOBLET J, et al. InraPorc: A model and decision support tool for the nutrition of sows[J]. Animal Feed Science and Technology, 2008, 143(1-4): 372-386.

熊本海, 杨亮, 郑姗姗, 等. 哺乳母猪精准饲喂下料控制系统的设计与试验[J]. 农业工程学报, 2017, 33(20): 177-182.

XIONG Benhai, YANG Liang, ZHENG Shanshan, et al. Designand test of precise blanking control system for lactatingsows[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2017, 33(20): 177-182. (in Chinese with English abstract)

熊本海, 杨亮, 曹沛, 等. 哺乳母猪自动饲喂机电控制系统的优化设计及试验[J]. 农业工程学报, 2014, 30(20): 28-33.

XIONG Benhai, YANG Liang, CAO Pei, et al. Optimal designand test of electromechanical control system of automatic feeder for nursing sow[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(20): 28-33. (in Chinese with English abstract)

王美芝, 安涛, 刘继军, 等. 智能饲喂器对哺乳母猪采食量体况和生产性能的影响[J]. 农业工程学报, 2019, 35(6): 190-197.

WANG Meizhi, AN Tao, LIU Jijun, et al. Effect of smart feeder on feed intake, body condition and production performance of lactating sows[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(6): 190-197. (in Chinese with English abstract)

李保明, 王阳, 郑炜超, 等. 畜禽养殖智能装备与信息化技术研究进展[J]. 华南农业大学学报, 2021, 42(6): 18-26.

LI Baoming, WANG Yang, ZHENG Weichao, et al. Research progress on intelligent equipment and information technology for livestock and poultry breeding[J]. Journal of South China Agricultural University, 2021, 42(6): 18-26. (in Chinese with English abstract)

GAUTHIER R, LARGOUET C, BUSSIERES D, et al. Precision feeding of lactating sows: Implementation and evaluation of a decision support system in farm conditions[J]. Journal of Animal Science, 2022, 100(9): skac222.

DURAND M, LARGOUET C, BONNEAU de Beaufort L, et al. Prediction of the daily nutrient requirements of gestating sows based on sensor data and machine-learning algorithms[J]. Journal of Animal Science, 2023, 101: skad337.

SPINLER M S, WOODWORTH J C, TOKACH M D, et al. Evaluation of precision feeding standardized ileal digestible lysine and other amino acids to determine and meet the lactating sow’s requirement estimates[J]. Journal of Animal Science, 2024, 102: skae285.

APARICIO-ARNAY M, YESTE-VIZCAINO N, SORIA N, et al. Precision feeding in lactating sows improves growth performance and carcass quality of their progeny[J]. Agriculture, 2025, 15(8): 887.

THERIAULT R, BEN-SHACHAR M S, PATIL I, et al. Check your outliers! An introduction to identifying statistical outliers in R with easystats[J]. Behavior Research Methods, 2024, 56(4): 4162-4172.

ABUZAID A, ALKRONZ E. A comparative study on univariate outlier winsorization methods in data science context[J]. Statistica Applicata-Italian Journal of Applied Statistics, 2024, 36(1): 85-99.

JARADAT Y, MASOUD M, MANASRAH A, et al. Review of data imputation techniques in time series data: Comparative analysis[J]. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 2024, 27: 122-129.

YE H, SOEDE N M, KEMP B, et al. Lactation body condition loss impaired conceptus development and plasma progesterone concentration at day 8 post-ovulation in primiparous sows[J]. Theriogenology, 2024, 218: 174-182.

GASA J, CAPALBO S, SCHIAVON S, et al. The effect of tissue mobilization and stage of lactation on energy partitioning in lactating sows: An analysis of commercial data[J]. The Journal of Agricultural Science, 2023, 161(6): 847-856.

CLOUTIER L, GAUTHIER R, GUAY F, et al. Impact of precision feeding during gestation on the reproductive performance of sows monitored over three reproductive cycles[J]. Animals, 2024, 14(23): 3513.

MUN H S, AMPODE K M B, LAGUA E B, et al. Backfat thickness at pre-farrowing: Indicators of sow reproductive performance, milk yield, and piglet birth weight in smart farm-based systems[J]. Agriculture, 2024, 14(1): 24.

LIU K, ZHANG L, XU X, et al. Lactational high weight loss impairs follicular development by causing mitochondrial dysfunction of ovarian cells in sows and mitigated by butyrate supplement[J]. Journal of Advanced Research, 2025, 78: 11-28.

郑良焰, 杨敏, 米万程, 等. 山花黄芩提取物对妊娠母猪繁殖性能及哺乳仔猪生长性能的影响[J]. 黑龙江畜牧兽医, 2024(8): 92-96.

ZHENG Liangyan, YANG Min, MI Wancheng, et al. Effects of Lonicera flots and Scutellariae radix extracts on reproductive performance of gestating sows and growth performance of lactating piglets[J]. Heilongjiang Animal Science and Veterinary, 2024(8): 92-96. (in Chinese with English abstract)

郭大伟, 侯思鲁, 池宇佳, 等. 芪英汤和子甘汤中药复方促进母猪繁殖性能和断奶仔猪生长性能的临床研究[J]. 畜牧兽医学报, 2022, 53(6): 1994-2004.

GUO Dawei, HOU Silu, CHI Yujia, et al. Clinical research of qiying decoction and zigan decoction on promoting reproductive performance of sow and growth performance of weaned piglets[J]. Acta Veterinaria et Zootechnica Sinica, 2022, 53(6): 1994-2004. (in Chinese with English abstract)

ESTRADA J, JOHNSON D C, KYLE K L, et al. Characterizing sow feed intake during lactation to explain litter and subsequent farrowing performance[J]. Journal of Animal Science, 2024, 102: skae093.

APARICIO M, YESTE-VIZCAINO N, MORALES J, et al. Use of precision feeding during lactation improves the productive yields of sows and their piglets under commercial farm conditions[J]. Animals, 2024, 14(19): 2863.

刘龙申, 柳荦, 周杰, 等. 母猪精准养殖智能感知技术研究进展[J]. 华南农业大学学报, 2024, 45(5): 635-648.

LIU Longshen, LIU Luo, ZHOU Jie, et al. Research progress on precision breeding and intelligent sensing technologies for sows[J]. Journal of South China Agricultural University, 2024, 45(5): 635-648. (in Chinese with English abstract)

GU F, HOU L, GAO K, et al. Effects of dietary net energy concentration on reproductive performance, immune function, milk composition, and gut microbiota in primiparous lactating sows[J]. Animals, 2024, 14(20): 3044.

AMPODE K M B, MUN H S, LAGUA E B, et al. Hourly feeding regime of modern genetics lactating sows: Enhancing productive performance, welfare, and piglet growth in smart farm-based systems[J]. Agriculture, 2024, 14(5): 740.

张银银, 陈昭辉, 陈建伟, 等. 夏季不同饲喂方式对两广小耳花猪哺乳母猪生产性能的影响[J]. 中国畜牧杂志, 2019, 55(8): 135-139.

ZHANG Yinyin, CHEN Zhaohui, CHEN Jianwei, et al. Effect of different feeding methods in summer on the performance of Liangguang small ear sows[J]. Chinese Journal of AnimalHusbandry, 2019, 55(8): 135-139.

OH S M, HOSSEINDOUST A, MUN J, et al. Importance of dietary supplementation of soluble and insoluble fibers to sows subjected to high ambient temperatures during late gestation and effects on lactation performance[J]. Animal Nutrition, 2024, 17: 73-83.

ANTANAITIS R, DZERMEIKAITE K, KRISTOLAITYTE J, et al. The impacts of heat stress on rumination, drinking, and locomotory behavior, as registered by innovative technologies, and acid–base balance in fresh multiparous dairy cows[J]. Animals, 2024, 14(8): 1169.

SEO Y J, JO H, KIM J H, et al. The effect of feed intake during lactation on the wean-to-estrus interval of sows[J]. Animal Industry and Technology, 2023, 10(1): 45-50.

SU J, KONG X, WANG W, et al. Weaning performance prediction in lactating sows using machine learning, for precision nutrition and intelligent feeding[J]. Animal Nutrition, 2025, 21: 222-233.

2026年第42卷第12期

PDF下载

234

102

引用本文

BibTeX

文章信息

doi: 10.11975/j.issn.1002-6819.202511127

接收时间：2025-11-18
首发时间：2026-08-20
出版时间：2026-06-30

补充材料

相关文章

文章信息

作者

出版历史

收稿日期：2025-11-18
修回日期：2026-06-05

基金

作者信息

中国农业科学院北京畜牧兽医研究所，北京 100083

通讯作者:

周梦婷，博士，助理研究员，研究方向为智慧畜牧工程。Email：zhoumengting@caas.cn

参考文献

分享链接

https://castjournals.cast.org.cn/joweb/nygcxb/CN/10.11975/j.issn.1002-6819.202511127

分享至

全文二维码

扫描看全文

引用本文

BibTeX

本文的引用情况

2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

关闭全屏

BibTeX
EndNote
RefWorks
TxT

阶段 Stage	泌乳日龄 Lactation day/d	F1/ (kg·d^-1)	F2/ (kg·d^-1)	F3+/ (kg·d^-1)
注：F1、F2、F3+分别代表头胎、二胎及三胎及以上母猪。递增升料阶段，系统以前一日基础饲喂量为基数，结合前一日采食完成度与料槽剩料量，在各胎次对应增量区间内上调当日饲喂量：前一日采食充分、剩料少时取区间上限增量，剩料较多、采食不足或存在拒食倾向时，降低增量或暂停升料。 Note: F1, F2 and F3+ stand for first-parity, second-parity and third-parity and above sows respectively. During the ramp-up feed escalation period, the daily feeding amount is adjusted upward from the previous day's baseline, according to the previous day's intake completion and residual feed in the trough, within the parity-specific increment range: the upper limit of the increment is used when feed intake is sufficient with little leftover; while a reduced increment or suspended escalation is adopted when there is excessive residual feed, insufficient intake or anorexia tendency.
产后适应期 Postpartum adaptation	1～2	1.5～2.3	1.5～2.5	1.5～2.5
递增升料期 Ramp-up feeding	3～7	每日递增 0.4～0.7	每日递增 0.5～0.8	每日递增 0.8～1.0
高峰期 Peak	8～14	5.0～6.0	5.5～6.5	6.5–7.5
高峰维持期 Peak maintenance	15～断奶	6.0～6.5	6.5～7.0	7.5～8.0

阶段
Stage

泌乳日龄
Lactation day/d

F1/
(kg·d^-1)

F2/
(kg·d^-1)

F3+/
(kg·d^-1)

产后适应期
Postpartum adaptation

1～2

1.5～2.3

1.5～2.5

递增升料期
Ramp-up feeding

3～7

每日递增
0.4～0.7

每日递增
0.5～0.8

每日递增
0.8～1.0

高峰期
Peak

8～14

5.0～6.0

5.5～6.5

6.5–7.5

高峰维持期
Peak maintenance

15～断奶

6.0～6.5

6.5～7.0

7.5～8.0

分组 Grouping	总产仔数 Total born	每窝总产仔数 Total born per litter	断奶–发情间隔 Weaning-to-estrus interval /d	断奶配种率 Wean-to-service rate /%
注：同一指标数据肩标相同或无字母表示差异不显著（P＞0.05）；不同小写字母表示显著差异（P＜0.05）；不同大写字母表示极显著差异（P＜0.01）。下同。 Note: The same indicator values with no letter or the same letter superscripts mean no significant difference (P＞0.05); Different lowercase and uppercase indicate significant (P＜0.05) and remarkable difference (P＜0.01) among treatments, respectively. The same below.
TFG	509	12.82 ± 1.48^a	9.04 ± 1.21^A	85
IFG	502	12.59 ± 2.15^a	8.15 ± 1.60^B	90

分组
Grouping

总产仔数
Total born

每窝总产仔数
Total born per litter

断奶–发情间隔
Weaning-to-estrus
interval /d

断奶配种率
Wean-to-service
rate /%

TFG

509

12.82 ± 1.48^a

9.04 ± 1.21^A

IFG

502

12.59 ± 2.15^a

8.15 ± 1.60^B

指标 Index	TFG	IFG
初生个体体重均值 Mean birth weight/kg	1.21 ± 0.19^a	1.22 ± 0.20^a
断奶体重均值 Mean weaning weight/kg	7.30 ± 1.00^A	7.68 ± 1.05^B
断奶增重均值 Pre-weaning weight gain/kg 仔猪成活率	6.06 ± 0.92^a	6.47 ± 0.98^b
Pre-weaning survival rate/%	89.13	92.06

指标 Index

TFG

IFG

初生个体体重均值
Mean birth weight/kg

1.21 ± 0.19^a

1.22 ± 0.20^a

断奶体重均值
Mean weaning weight/kg

7.30 ± 1.00^A

7.68 ± 1.05^B

断奶增重均值
Pre-weaning weight gain/kg
仔猪成活率

6.06 ± 0.92^a

6.47 ± 0.98^b

Pre-weaning survival rate/%

89.13

92.06

指标 Index	五餐组 5-meal	四餐组 4-meal	其他传统饲喂组 Other TFG
窝均有效仔 Mean number of viable piglets per litter	13.90 ± 1.02^A	14.25 ± 0.98^A	12.69 ± 1.35^B
窝均断奶数 Mean number of weaned piglets per litter	12.39 ± 0.91^a	12.42 ± 0.88^a	11.28 ± 1.12^b
断奶数 Total number of weaned piglets	731	733	730
断奶体重均值 Mean weaning weight/kg	7.46 ± 0.52^a	7.44 ± 0.48^a	7.31 ± 0.59^a
断奶窝体重 Mean litter weaning weight/kg	90.65 ± 5.32^a	90.99 ± 5.48^a	89.66 ± 6.02a
成活率 Pre-weaning survival rate /%	92.32	91.98	90.21

指标
Index

五餐组
5-meal

四餐组
4-meal

其他传统
饲喂组
Other TFG

窝均有效仔
Mean number of viable
piglets per litter

13.90 ± 1.02^A

14.25 ± 0.98^A

12.69 ± 1.35^B

窝均断奶数
Mean number of weaned
piglets per litter

12.39 ± 0.91^a

12.42 ± 0.88^a

11.28 ± 1.12^b

断奶数
Total number of weaned piglets

731

733

730

断奶体重均值
Mean weaning weight/kg

7.46 ± 0.52^a

7.44 ± 0.48^a

7.31 ± 0.59^a

断奶窝体重
Mean litter weaning weight/kg

90.65 ± 5.32^a

90.99 ± 5.48^a

89.66 ± 6.02a

成活率
Pre-weaning survival rate /%

92.32

91.98

90.21