Thesis (M. Agricultural Management (Animal Production)) -- University of Limpopo, 2022 / Modern analytical techniques such as data mining algorithms are used to create a
model that accurately estimates continuous dependent variable from independent
variables of a given set of data. The present study used different data mining
algorithms to assess the association between body weight (BW) and morphological
characteristics such as body length (BL), heart girth (HG), withers height (WH), rump
height (RH), and rump length (RL) of South African non-descript indigenous goats.
The research was carried out in the Lepelle-Nkumbi Local Municipality, Capricorn
District in the Limpopo province of South Africa. The study used 700 non-descript
indigenous goats which include 283 bucks and 417 does with age ranged from one
to five years old. The morphological characteristics were taken with a tailor measuring
tape and a wood ruler calibrated in centimetres (cm), while the BW was taken with a
balanced animal scale calibrated in kilograms (kg). Before the goats were allowed to
go for grazing, the following body measurements (BW, BL, HG, WH, RH and RL) was
taken once in the morning. Data was analyzed using descriptive statistics, Pearson
correlation, various data mining algorithms (Chi-square automatic interaction
detector, Classification, and regression tree), analysis of variance and goodness of
fit equations (Coefficient of determination (R2), adjusted coefficient of determination
(Ajd.R2), root mean square error (RMSE), relative approximate error (RAE), standard
deviation ratio (SD. ratio) and coefficient of variance (CV)). The result showed that,
BW and HG had higher mean values in does than bucks, BL and WH had higher
mean values in bucks than does, and RH and RL had equal mean values in bucks
and does, according to descriptive statistics. Furthermore, our findings showed that
the BW of does had positive significant correlation (P < 0.01) with BL (r = 0.65), and
positive significant correlation (P < 0.05) with HG (r = 0.28), but non-significant
correlation (P > 0.05) with WH (r = 0.21), RH (r = 0.23) and RL (r = 0.23). However,
the result for bucks indicated that BW had positive significant correlation (P < 0.01)
with BL (r = 0.65) but non-significant correlation with HG (r = 0.22), WH (r = 0.07),
RH (r = 0.14) and RL (r = 0.12). The chi-square automatic interaction detector and
classification and regression tree results indicated that BL in bucks and does had
statistical significance (P < 0.01) on BW followed by age, HG, and villages where the
animals were raised. Goodness of fit results indicated there was high R2 = 0.58, Adj.
R2 = 0.58, and low SD. Ratio = 0.65, RAE = 0.02, RMSE = 5.53) and CV = 14.49 in
CHAID model and low R2 = 0.51, Adj. R2 = 0.46 and high SD. Ratio = 0.70, RAE =
0.20, RMSE = 5.95 and CV = 15.49 in CART model. Analysis of variance results
indicated that age had significant difference (P < 0.01) on BW and some
morphological traits including BL, HG, WH and RH. Sex only revealed significant
difference (P < 0.01) in RL. It was concluded that BL alone in both sexes can be used
as a selection criterion when determining body weight of goats. Both CHAID and
CART suggest that BL alone can be used as a predictor of body weight in goats.
Goodness of fit calculations suggest that CHAID is the best model due to its high R2,
Adj. R2 and low RAE and RMSE. Findings suggest that age can be used as deciding
factor for the measured traits including BW, BL, HG, WH and RH in both does and
bucks. Findings suggest that sex can only be used as a deciding for RL only in the
current study. / National Research Foundation (NRF)
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:ul/oai:ulspace.ul.ac.za:10386/3909 |
| Date | January 2022 |
| Creators | Mathapo, Madumetja Cyril |
| Contributors | Tyasi, T. L., Mugwabana, T. J. |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | x, 52 leaves |
| Relation |
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