3rd International Plant Breeding Conference 2016: Strengthening Plant Breeding and Future Perspectives. 15-16 November 2016 Bangi-Putrajaya Hotel, Selangor, Malaysia

1. 15-16 November 2016
Bangi-Putrajaya Hotel,
Selangor, Malaysia
EVALUATION OF SWEET POTATO BASED ON AGRONOMIC
CHARACTERS AND BIOCHEMICAL CONTENT LEAVES AND
TUBERS AS BASIS FOR MULTI PURPOSE FOOD AND
BIOINDUSTRY IN INDONESIA
Budi Waluyo1*, Chindy Ulima Zanetta2, Agung Karuniawan3
1Faculty of Agriculture - Universitas Brawijaya, Jln. Veteran, Malang 65145, Indonesia
2School of Life Sciences and Technology - Institut Teknologi Bandung, Jln. Ganesha 10, Bandung, 40132, Indonesia
3Faculty of Agriculture - Universitas Padjadjaran, Jln. Raya Bandung-Sumedang Km 21 Jatinangor 45363, Indonesia
*Contact: budiwaluyo@ub.ac.id

2. INTRODUCTION
• Sweet potato potentially be used as food, feed, and bioethanol
industry
• As a food source, the variation of the tuber flesh can be directed
at the source of carbohydrates with a low glycemic index, source
of functional foods with high vitamin and mineral content, as well
as a source of antioxidants
• The content of starch and dry matter of sweet potato tubers
suitable to be used as industrial raw materials and bioethanol
• Stems, petioles and leaves of sweet potato potentially be used as
a functional food ingredient source of antioxidants and
antimutagenic. The leaves can also be used as a potential feed
sources

3. • Indonesia is a secondary center of sweet potato diversity in the world
because has a high genetic variability
• The variation of sweet potato is possible because Indonesia have high
geographical variation
• Utilization of this diversity can be done through the use of sweet potato raw
materials as well as a source of genetic improvement, and in addition to
increasing the value of sales and farmers' income
• The purpose of the research was to evaluate the variability of sweet potato
based on agronomic characters and biochemical content leaves and tubers
as basis for multipurpose food and bioindustry

4. • Materials used in this study were 11 genotypes of sweet potato
• The study was conducted using a randomized block design with
genotype as treatment, repeated two times.
• The experiments were performed at the Experimental Field of
Faculty of Agriculture, Universitas Padjadjaran in October 2012
until June 2014
• Data were collected for agronomic characters and biochemical
content of tubers and leaves by the proximate analysis
MATERIALS AND METHODS

5. • The variability measured: principal component analysis (PCA)
based on the type of the Pearson correlation coefficient (n-1)
• The main component (PC) meaningful: eigenvalue >1
• The characters are the main contributing on every PC: loading
factor > 0.6
• Agglomerative hierarchical clustering (AHC) was applied to the
grouping sweet potato genotypes based on Euclidean distance
dissimilarity and unweighted pair-group average
• Analysis of data using Microsoft® Excel 2007/XLSTAT Version
2009.3.02.

6. RESULTS AND DISCUSSION
• Sweet potato genotype has coefficient of variability of
traits between 0.92 % - 71.04 %.
• Proximate analysis on sweet potato leaves showed the
coefficient of variation between 0.92 % found in leaf moisture
to 10.80 % in dry matter content.
• Agronomic characters have variability between 37.66 % in
number of tubers per plant to 70.66 % in tuber yield per
hectare.
• Biophysical characteristics of tubers flesh show the variation
between 1.39 % in the specific gravity to 71.04 % on a reducing
sugar content.

7. Variable Min. Max. Mean
Std.
deviation
CV ( %)
Moisture content of leaves ( %) 91.09 93.95 92.15 0.85 0.92
Dry matter of leaves ( %) 6.05 8.91 7.85 0.85 10.80
Ash content of leaves ( %)# 1.21 1.33 1.26 0.04 2.83
Fiber content of leaves ( %)# 1.15 1.47 1.27 0.10 7.51
Crude protein content of leaves ( %)# 3.14 3.65 3.35 0.17 5.09
The number of tubers per plant 1.08 3.40 2.11 0.79 37.26
Tuber weight per plant (g) 135.00 1270.00 528.76 355.33 67.20
Weight of 10 tubers 0.67 4.92 2.56 1.35 52.85
Yield (t/ha) 4.08 28.33 14.30 10.10 70.66
Moisture content of tuber ( %) 60.83 81.96 66.87 6.52 9.75
Dry matter of tuber ( %) 18.04 39.17 33.13 6.52 19.68
Starch content of tuber ( %)# 4.80 19.25 13.96 4.14 29.69
Sugar reduction content of tubers ( %)# 0.13 1.72 0.65 0.46 71.04
Ash content of tuber ( %)# 0.63 10.63 5.63 3.32 58.91
Total soluble solid of fresh tuber (oBrix) 1.50 5.00 3.18 1.20 37.86
Total soluble solid steamed tuber (oBrix) 4.20 15.95 9.51 3.16 33.18
Total soluble solid baked tuber (oBrix) 6.00 14.90 11.12 2.49 22.41
Specific gravity 1.01 1.06 1.04 0.01 1.39
Ethanol yield (l/ha) 618.72 5364.50 2269.62 1293.88 57.01
Table 1. Description of agronomic, biochemical content leaves and
biochemical content tubers characters of sweetpotato

8. • Six principal components in the PCA had eigenvalue > 1 which
presenting maximum cumulative variability reached 90.13 %
• First principal component (PC1) contributes 25.74 % of total
variability. PC2 contributes to the total variability about 19.24 %.
PC3 contribute 18.80 % of total variability. PC4 contains variability
11.38 %. PC5 has contributed to total variability about 8.77 %. PC6
contributed 6.21 % to total variability.

9. Component and Characters PC1 PC2 PC3 PC4 PC5 PC6
Eigenvalue 4.89 3.65 3.57 2.16 1.67 1.18
Variability ( %) 25.74 19.24 18.80 11.38 8.77 6.21
Cumulative % 25.74 44.97 63.77 75.15 83.92 90.13
Moisture content of leaves ( %) -0.49 0.02 0.69 0.38 -0.26 0.01
Dry matter of leaves ( %) 0.49 -0.02 -0.69 -0.38 0.26 -0.01
Ash content of leaves ( %)# -0.02 0.63 -0.49 -0.10 -0.38 0.12
Fiber content of leaves ( %)# 0.76 -0.11 0.43 0.13 -0.03 0.22
Crude protein content of leaves ( %)# -0.17 -0.60 0.37 0.40 0.33 0.14
The number of tubers per plant 0.64 -0.43 0.27 0.08 -0.28 0.39
Tuber weight per plant (g) 0.84 -0.46 -0.03 -0.06 0.02 -0.11
Weight of 10 tubers 0.60 -0.31 -0.27 0.00 0.27 -0.49
Yield (t/ha) 0.90 -0.11 -0.01 -0.13 -0.11 0.27
Moisture content of tuber ( %) -0.10 -0.63 -0.54 0.45 -0.25 0.05
Dry matter of tuber ( %) 0.10 0.63 0.53 -0.45 0.25 -0.05
Starch content of tuber ( %)# -0.01 0.18 0.79 -0.52 -0.18 0.15
Sugar reduction content of tubers ( %)# 0.11 -0.09 0.50 0.15 0.76 0.17
Ash content of tuber ( %)# 0.53 0.56 -0.02 0.08 0.28 -0.17
Total soluble solid of fresh tuber (oBrix) -0.18 -0.14 -0.56 -0.35 0.25 0.64
Total soluble solid steamed tuber (oBrix) 0.32 0.54 -0.07 0.71 0.01 -0.02
Total soluble solid baked tuber (oBrix) 0.61 0.56 -0.09 0.46 0.12 0.17
Specific gravity -0.19 0.75 -0.30 0.32 0.12 0.28
Ethanol yield (l/ha) 0.81 0.20 0.24 -0.02 -0.46 -0.10
Table 2. Eigenvalue, first six principal component (PC) and factor loading
of agronomic, leaves biochemical content, and tuber biochemical
content of sweetpotato

10. • That sweet potato has variability in characters that can
be utilized by industry.
• Genetic variability is the basis for an increase in
production capacity for the industry that is based on true
varieties.
• Opportunities for improvement in the character of sweet
potatoes to be used as industrial raw materials for food,
feed and renewable energy sources is very large

11. • The 11 sweetpotato genotypes based on 19 characters were
classified in four groups
• Cluster 1 contained four genotypes namely Ayamurasaki, Nirkum,
Ciamis Jingga, and Menes
• Cluster 2 was composed five genotypes that were Jawer Kotok,
Ganola, Narutokintoki, Odos, and Shiroyutaka
• Cluster 3 included one genotype, which is Kuningan Merah.
• Cluster 4 has one genotype namely Menes Pandeglang.

12. Figure 1. Dendrogram of 11 sweet potato accessions using Euclidean distances
MenesPandeglang
Menes
CiamisJingga
Ayamurasaki
Nirkum
KuninganMerah
Ganola
Siroyutaka
Odos
JawerKotok
Narutokintoki
0
500
1000
1500
2000
2500
3000
3500
4000
Dissimilarity

13. Cluster 1 Cluster 2 Cluster 3 Cluster 4
Characters
Ayamurasaki
Nirkum
Ciamis
Jingga
Menes
JawerKotok
Ganola
Narutokintok
i
Odos
Siroyutaka
Kuningan
Merah
Menes
Pandeglang
Moisture content of leaves ( %) 91.1 94.0 92.0 92.0 92.2 93.4 92.0 91.7 92.0 91.2 92.0
Dry matter of leaves ( %) 8.9 6.0 8.0 8.0 7.8 6.6 8.0 8.3 8.0 8.8 8.0
Ash content of leaves ( %)# 1.2 1.2 1.3 1.3 1.3 1.2 1.3 1.3 1.2 1.2 1.3
Fiber content of leaves ( %)# 1.2 1.2 1.2 1.2 1.3 1.3 1.2 1.3 1.4 1.3 1.5
Crude protein content of leaves (%)# 3.2 3.6 3.3 3.2 3.4 3.4 3.3 3.2 3.4 3.6 3.1
The number of tubers per plant 1.5 1.9 1.2 1.8 3.0 2.3 1.1 2.1 1.8 3.4 3.2
Tuber weight per plant (g) 333.3 272.5 208.3 135.0 640.0 199.7 675.0 630.0 480.0 1270.0 972.5
Weight of 10 tubers 1.8 1.7 2.6 0.7 2.2 0.8 4.9 2.7 3.2 4.5 3.0
Yield (t/ha) 4.7 4.1 6.3 4.3 21.3 5.9 9.3 26.9 21.1 25.0 28.3
Moisture content of tuber ( %) 63.4 67.3 82.0 62.3 70.8 63.7 63.0 62.3 60.8 74.8 65.2
Dry matter of tuber ( %) 36.6 32.7 18.0 37.7 29.2 36.3 37.0 37.7 39.2 25.2 34.7
Starch content of tuber ( %)# 15.0 19.2 4.8 13.5 15.8 15.0 12.8 16.0 15.0 8.4 17.9
Sugar reduction content of tubers ( %)# 0.6 1.0 0.3 0.6 0.1 0.8 0.3 0.2 1.7 1.0 0.6
Ash content of tuber ( %)# 0.6 2.6 4.6 8.6 1.6 3.6 7.6 9.6 10.6 5.6 6.6
Total soluble solid of fresh tuber (oBrix) 5.0 2.8 4.0 2.5 4.0 2.0 1.5 4.5 3.8 3.5 1.5
Total soluble solid steamed tuber (oBrix) 5.9 4.2 10.5 10.8 6.2 16.0 10.2 10.5 9.7 10.8 10.0
Total soluble solid baked tuber (oBrix) 9.0 6.0 10.7 10.6 9.0 14.9 11.0 13.5 13.1 12.3 12.3
Specific gravity 1.0 1.0 1.0 1.0 1.0 1.1 1.0 1.1 1.0 1.0 1.0
Ethanol yield (l/ha) 618.7 861.8 1212.0 1730.7 2685.3 2349.0 2637.5 3108.9 2292.8 2104.6 5364.5
Table 3. Characters and grouping of sweet potato genotypes based on cluster analysis
Remark: # fresh basis

14. • Genotypes that are in the same cluster show the closeness of the
relationship.
• Genotypes that are in different clusters showed most of the
characters were observed to have a different appearance.
• For industrial use, genotypes that are in the same cluster can be
used as a complement to meet the needs of industrial raw
materials, sources of food, or feed.
• Genotypes that are in different clusters demonstrate the potential
use of raw materials for different purposes, and can be used as
the basis for new businesses based on the specific character
identifier genotype.

15. • There was variability in fiber content of leaves, number
of tuber per plant, tuber weight per plant, tuber yield,
degree of sweetness baked tuber and bioethanol yield,
ash content of leaves, protein content of leaves,
moisture of tuber, dry matter of tuber and specific
gravity of tuber, moisture of leaves, dry matter of leaves
and starch content of tuber, sweetness of steamed tuber,
reduction sugar content of tuber and degree of
sweetness fresh tuber. Genotypes divided into four
groups.
CONCLUSION