A.S. GHAI - DOWNLOAD

NDRI

GHAINDX

INPUT FILE : NDX.DAT

DATA :

1st record : Heading for the print out on top of results.

(30A4)

Parameter cards for selection indices

NC,(NCC(I),I=1,NC),IR,(NRR(I),I=1,IR)

(20I2)

NC : No of character

NCC(I) : Their location in the array.

IR : No. of restriction imposed

NRR(I) : Location of restriction in the array.

GENOTYPIC VAR‑COVR MATRIX

**************************

33.575 .080 ‑.006 68.123

.080 .238 ‑.033 .468

‑.006 ‑.033 .084 ‑.764

68.123 .464 ‑.764 205.144

PHENOTYPIC VAR‑COVR MATRIX

**************************

44.412 .238 ‑.027 93.128

.238 .427 ‑.193 .673

‑.027 ‑.193 .094 ‑.428

93.128 .673 ‑.428 224.099

A VECTOR MATRIX

**************************

1.000 1.000 1.000 1.000

CHARACTER NO. 1 2 3 4

RESTRICTED SELECTION INDEX b(i)

1= ‑2.3027641 2= 4.6273876 3= 11.127380 4= 2.1823885

VALUE OF VARIATE (V.V.)(i)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

1= 2.3327050 2= .52028890E‑01 3= .63192840E‑01 4= 11.178060

DELTAG(I)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

1= 1.3277110 2= .29112440E‑01 3= ‑.16147910E‑01 4= 5.2708710

b'pb = 356.83720 DELTAG = 6.6115470 rih = .97577770

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

CHARACTER NO. 1 2 3 4

RESTRICTION IMPOSED ON CHARECTER NO. 2

RESTRICTED SELECTION INDEX b(i)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

1= ‑1.8508996 2= ‑4.3571054 3= ‑7.7798548 4= 1.9836066

VALUE OF VARIATE (V.V.)(i)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

1= 1.5067280 2= .46306850E‑01 3= .31006340E‑01 4= 9.1737450

DELTAG(I)

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

1= 1.3493600 2= ‑.11213980E‑09 3= ‑.37391430E‑01 4= 5.2865080

b'pb = 355.42750 DELTAG = 6.5984750 rih = .97384850

GHAITRND

OBJECT : Estimation of Genetic Trends

INPUT FILE : trend.par - parameter file

1st record : Heading for the print out on top of results.

2nd record : NS, NC, NP, KD, IS, IP,(IX(I),I=1,NC),NYR,NMY

FORMAT(40I2)

NS : No of variable to be read from data

NC : No of character

NP : Progenies per sire

KD : Variable for end of data

IS : Variable for sire

IP : Variable for year

IX : Variables for character

NYR : No of years

NMY : No of years over which progenies to be distributed

DATA : trend.dat - data file

DATA should be sorted sire wise.

Test data format(f2.0,2f3.0,5f1.0,4f8.0,f8.1,5f8.0,2f8.3,f8.0,2f8.2,f8.1,2f8.3,3f8.1,f8.0)

OUTPUT : Trend.out

Test data

30 6 2 1 3 30 19 20 23 29 25 26 16 2 0

farm no= 0

********

xbar = 8.5277 s.e. = .0723 no.of obs. = 834. no. of sires = 89.

0 ch. no. = 10 Delta p = .0133 s.e. = .0176

0 Pooled intra‑sire regression of performence on time = .1613 s.e. = .0565

0 Genetic trend (GP) = ‑.2962 s.e. = .1183

0 Environment trend = .3094 s.e. = .1196

0‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

Sire Evaluation Method

While evaluation the sire in breed improvement programmes, the ranking of bulls in order of their merit or comparing their breeding values are important indicators to the breeders to select the best bulls. Therefore, it is necessary to compute an estimate of breeding worth of each sire i.e. the sire index. Different sire index methods based on the performance of adequate number of progeny records and mateds records have been proposed from time to time. These sire indices are generally classified either for the purpose of ranking bulls or in addition provide estimates of genetic merit of sire.

GHAISEVX

OBJECT : Estimation of Sire Indices on the basis of their daughters' and mates performance.

INPUT FILE : Any ascii file.

DATA :

1st record : Heading for the print out on top of results.

2nd record : NTVR, NS, KD, KM, H, MUD, MUM

FORMAT(4I2,F4.4,2F6.2)

NTVR : No of variable to be read from data

NS : Key for sire location

KD : Key for daughter's yield

KM : Key for mate's yield

H : Heritability

MUD :  for daughters

MUM :  for mates

3rd record : NOS, (IS(I),I=1,NOS)

(30I4)

NOS : Total No. of sires

Is : Sire code in data

DATA should be sorted sire wise .

OUTPUT

METHODS FOR SIRE EVALUATION:‑

******************************

1... DBAR

2... HA+(DBAR‑CD)

3... HA+Q(DBAR‑HA)

4... HA+Q(DBAR‑CD)

5... HA+R(DBAR‑CD)

6... HA+2*R(DBAR‑CD)

7... 2DABR‑MBAR

8... DBAR‑H(MBAR‑HA)/2

9... DBAR+DE‑ME

10... HA+Q(DBAR‑MBAR)

11... HA+Q(DBAR‑CD‑H(MBAR‑CM)/2)

12... HA+R(DBAR‑CD‑H(MBAR‑CM)/1)

13... HA+R(DBAR‑CD)‑H(MBAR‑CM)/2

DE = SQRT(DBAR*HA)

ME = SQRT(MBAR*DAMS HERD AV.)

Q = 2*N(I)*H/(4+(N(I)‑1)*H)

R = N(I)/(N(I)+12)

SIRE.SRT

SIRE NUMBERS........

4 22 39 54 68 148 246

MUE FOR DAUGHTERS = 3915.9420

MUE FOR MATES = 3348.7110

HERITABILITY = .2000

VALUES FOR INDICES FROM DIFFERENT METHODS→ OF SIRE EVAUATION

↓ SIRE NO. 1 2 3 4 5 6 7 8 9 10 11 12 13

‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑‑

1 12 3775.58 3733.48 3807.28 3774.68 3824.71 3733.48 4207.17 3832.78 4274.35 4250.07 3775.15 3825.01 3825.32

2 12 4145.83 4214.80 4093.92 4147.32 4065.37 4214.80 4877.67 4196.03 4793.88 4482.52 4140.72 4061.11 4056.86

3 7 3378.71 3295.15 3626.67 3581.67 3687.23 3458.51 3901.43 3484.71 3923.58 4197.40 3612.32 3708.20 3744.15

4 6 3663.67 3630.76 3794.85 3779.06 3820.88 3725.82 4143.33 3736.86 4186.05 4146.18 3787.99 3827.09 3839.50

Object : Estimation of EPA

Lush gave the formula for calculation of EPA of a production trait as under

nr _

MPPA = m + --------- ( X_i - m )

1 + (n – 1)r

Where m = Herd average

n = Number of lactations

r = repeatability

X_i = Average of all the lactations of i^th animal

The animal which produces less than average MPPA or below a certain level of MPPA is culled from the herd.

GHAIEPA

INPUT File : Any text file

INPUT DATA

1. 1st record : Heading (20A.4)

Data Data in following format

a. Cow No. : 1-4

b. Date of birth : 5-12

c. Sire No. : 13-20

d. Breed of Sire : 21- 22

e. Dam No. : 23-26

f. Breed of Dam : 27-28

g. Date of 1st calving : 29-36 (ddmmyyyy)

h. Date of last calving : 37-44

i. Lactation wise milk yield in the format of 14i4: 45-48,49-52………..

Object : Estimation of EPD

In order to select the young bulls/ male calves for putting under progeny – test, it is essential that they are selected on the basis of some scientific index based on genetic principles. For sex-limited trait like milk yield, the male calves are selected based o information on dam’s and paternal grand-dam’s performance and accordingly expected predicted difference (EPD) for young bulls/ male calves is computed. EPD is the measure of the deviation of the index (based on dam’s performance, paternal grand-dam’s performance and paternal half-sib performance)

from the mean of the population.

GHAIEPD

INPUT File : Any text file

Breed code:

01-Sahiwal

02-Tharparkar

03-Redsindhi

04-Karan Swiss

05-Karan Fries

06-Murrah

07-Holstien

08-BrownSwiss

INPUT DATA

1st record : Heading (20A.4)

2nd record :

a. Heritability. : 1-4

b. Repeatability : 5-8

01-Sahiwal : 9-12

02-Tharparkar 13-16

03-Redsindhi 17-20

04-Karan Swiss 21-24

05-Karan Fries 25-28

06-Murrah 29-32

07-Holstien 33-36

08-BrownSwiss 37-40

3rd record

1. Calf No.

2. Breed Code

3. Date of birth : 5-12

4. Sire No. : 13-20

5. Breed code : 21- 22

6. Dam No. : 23-26

7. Breed code : 27-28

8. Grand dam No.

9. Breed code

10. Dam’s best yield

4th record :Grand dam’s lactation wise milk yield in the format of (50x, 25I4)

5th record :1st lactation milk yield of paternal half-sib in the format of 50x,25I4)

Repeat 3rd to 5th records for all male calves. If yield of paternal grand dam or paternal half sibs are not available leave 3rd to 5th records blank.

GHAIPRNCPL

OBJECT :

INPUT FILE : Prncpl.mtx

: Prncpl.in

DATA :

1st record : Heading for the print out on top of results. (30A4)

2nd record : Array size (i2) P

PRNCPL.MTX Lower half matrix in format(11f7.4)

Data in format (6f7.0,f7.1,f7.0,2f7.1,f7.4)

OUTPUT

/u1/sondhi/gandhi.148

INPUT MATRIX FOR EIGEN VALUES AND VECTORS

.1000000E+01 .6880000E+00 .1000000E+01 .5190000E+00 .8760000E+00 .1000000E+01 .5180000E+00 .7480000E+00

.5940000E+00 .1000000E+01 .3980000E+00 .5860000E+00 .5160000E+00 .8200000E+00 .1000000E+01 .2050000E+00

.3680000E+00 .4100000E+00 .6250000E+00 .8900000E+00 .1000000E+01 .6000000E-01 .4720000E+00 .4700000E+00

.4320000E+00 .2540000E+00 .8800000E-01 .1000000E+01 .4530000E+00 .4450000E+00 .4990000E+00 .1660000E+00

.1170000E+00 .6000000E-01 .1200000E+00 .1000000E+01 .1800000E+00 .1590000E+00 .2620000E+00 .9200000E-01

.1970000E+00 .1770000E+00 .5100000E-01 .5890000E+00 .1000000E+01 .1400000E-01 .3100000E+00 .3120000E+00

.2560000E+00 .1560000E+00 .9400000E-01 .2630000E+00 .2150000E+00 .5790000E+00 .1000000E+01 -.1040000E+00

.4180000E+00 .4190000E+00 .3110000E+00 .1660000E+00 .5300000E-01 .7390000E+00 .1130000E+00 .2800000E-01

.4150000E+00 .1000000E+01

OUTPUT OF EIGEN VALUES & VECTORS

EIGEN VALUES

.4698149E+01 .1804647E+01 .1665666E+01 .1219469E+01 .5804412E+00 .3824764E+00 .2540058E+00 .1786650E+00

.1145968E+00 .6526446E-01 .3661691E-01

VECTOR 1

.2768010E+00 .4174176E+00 .3977780E+00 .3897700E+00 .3571208E+00 .2790729E+00 .2527685E+00 .2254960E+00

.1743038E+00 .2016456E+00 .2186213E+00

VECTOR 2

-.2338960E+00 -.4235423E-02 .6571151E-01 -.2114621E+00 -.3564621E+00 -.3987390E+00 .3502846E+00 .1957078E+00

.2533187E+00 .4209762E+00 .4558398E+00

VECTOR 3

-.3034151E+00 .6239572E-02 -.3297022E-01 .1720235E+00 .1151053E+00 .9080502E-01 .3948044E+00 -.5078859E+00

-.5140706E+00 -.1154624E+00 .4053485E+00

&nbs