Response of Haricot Bean ( Phaseolus vulagris L.) Varieties to Different Growth Parameters at Hawassa, Southern Ethiopia

Full text

Journal of Chemical, Environmental and Biological Engineering
2021; 5(1): 1-4
http://www.sciencepublishinggroup.com/j/jcebe
doi: 10.11648/j.jcebe.20210501.11
ISSN: 2640-2645 (Print); ISSN: 2640-267X (Online)
Research Article
Response of Haricot Bean (Phaseolus vulagris L.) Varieties
to Different Growth Parameters at Hawassa, Southern
Ethiopia
Dasta Tsagaye
1, *
, Nimona Fufa
1
, Desta Bekele
2
1
Ethiopian Institute of Agricultural Research, Kulumsa Agricultural Research Center, Assella, Ethiopia
2
Ethiopian Institute of Agricultural Research, Asossa Agricultural Research Center, Asossa, Ethiopia
Email address:
*
Corresponding author
To cite this article:
Dasta Tsagaye, Nimona Fufa, Desta Bekele. Response of Haricot Bean (Phaseolus vulagris L.) Varieties to Different Growth Parameters at
Hawassa, Southern Ethiopia. Journal of Chemical, Environmental and Biological Engineering. Vol. 5, No. 1, 2021, pp. 1-4.
doi: 10.11648/j.jcebe.20210501.11
Received: December 8, 2020; Accepted: December 28, 2020; Published: March 17, 2021
Abstract:
Haricot bean (Phaseolus vulagris L), locally known as ‘Boleqe’ is a very important legume crop grown worldwide.
The study was initiated to assess the performance of haricot bean cultivars in relation to growth parameters and to estimate the
analysis of growth characteristics. The experiment was conducted during November 2016 up to January 2017 at the compound of
Hawassa University in the College of Agriculture during of season. The treatment consists of three Haricot varieties namely;
Hawassa Dume, Omo-95 and Red Wolayta were used for test. The experiment was arranged in RCBD with four replications. The
data were collected are Days to 50% emergence, Leaf area (cm
2
), Stem and leaf dry weight (gm) and calculated on Specific leaf
area, leaf area ratio, net assimilation ratio and relative growth rate and Biomass dry weight were collected. Analysis of variance
showed that the collected data were significantly different with respect to varieties. From the result in terms of (specific leaf area
and leaf area ratio) the varieties which show higher value at the first sampling will show also increased value at the second
sampling and vice versa. Growth parameters showed increment from the first sampling to the last sample which indicates
difference varieties in growing environment. Generally growth parameters showed an increment from emergency to maturity.
Keywords:
Growth Parameters, Different Haricot Bean Varieties, Haricot Bean
1. Introduction
Haricot bean (Phaseolus vulagris L.) is an annual crop
belonging to the family Fabaceae [1] which is grown
predominantly by smallholder producers as a source of food
and cash in Ethiopia [2]. Haricot bean (Phaseolus Vulagris L),
locally known as ‘Boleqe’ also known as dry bean, common
bean, kidney bean and field bean is a very important legume
crop grown worldwide. It is an annual crop which belongs to
the family Fabaceae. It grows best in warm climate at
temperature of 18°C to 24°C [3]. The adaptability of this crop
can range up to 3000 meters above sea level depending on the
selected variety and does not grow well below 600 meters
above sea level [4]. It is source of protein and energy in human
diets [5]
In our country Ethiopia it is grown under smallholder
farmers and important crops for the daily diet and foreign
earnings [6].
According Zelalem [7] reported that haricot bean stands out
among the pulses and is also known as “the poor man’s meat”
due to
its high protein content, which compensates for the
deficiency that could have occurred in a
population with low
income. Different types of haricot beans are grown in Ethiopia.
These
include white pea beans, grown in the central Ethiopia
(Shoa) as cash crop, colored beans
grown in the southern part
of Ethiopia for local consumption and climbing beans grown
in the
northwest (Metekel) and western Ethiopia (Wollega).
Climbers are planted along fences and
on the borders of maize
fields. The productivity of the crop around the study area (15.7

2 Dasta Tsagaye et al.: Response of Haricot Bean (Phaseolus vulagris L.) Varieties to Different
Growth Parameters at Hawassa, Southern Ethiopia
kg ha
-1
) is reported to be below the national average
productivity (17.0 kg ha
-1
) [8].
It covers the dominant pulses export. However, the share
has been limited by external demand for quality [9]. Its
production was limited because of lack of high yielding
varieties which have high resistance to disease and other biotic
and abiotic factors [10].
Plant growth analysis is approach to interpreting plant form
and function. It uses simple primary data to investigate
processes within and involving the whole plant [11]. Plant
growth analysis first illuminated plant physiology, then
agronomy and now physiological and evolutionary plant
ecology [12].
The relative contribution of different growth parameters to
change growth of the crops depends on the genetic contents of
the crops. Therefore the significance of the study was to
estimate how different varieties of haricot bean can response
to different to growth parameters. The study was designed or
proposed to know the response of haricot bean varieties to
different growth parameters.
2. Materials and Methods
2.1. Description of the Study Site
The experiment was conducted during November 2016 up
to January 2017 at the compound of Hawassa University in the
College of Agriculture. Hawassa is the regional capital of
Southern Nation Nationalities and People’s Regional State
(SNNPRs), which is found 275 km south of the capital Addis
Ababa. The site is located 6°42’N and 38° 29’E of latitude at
an altitude of 1650 m.a.s.l with mean annual rainfall of 900
mm, mean annual temperature maximum and minimum of
13°C and 27°C respectively. The soil of the experimental site
is sandy loam with pH of 5.5. The research was done under
controlled irrigation since it off cropping season. The lab
experiment was conducted at the department of plant and
horticultural Sciences in the Physiology laboratory.
2.2. Treatment and Experimental Design
Hawassa Dume, Omo-95 and Red wolayta haricot bean
varieties were used for test crop to compare its response to
growth parameters. The treatments were arranged in RCBD
with four replications. A Spacing of 40 cm between rows and
plants were spaced 10 cm apart. To ascertain full stand in a
plot, two seeds per hill were planted and thinned to
appropriate stand after emergence. A plot of five rows each 2
m long (2m x 2m) was used, and 50 kg/ha DAP fertilizer was
applied at the time of planting. All necessary agronomic
practices have been done uniformly as per the
recommendations. The experiment was planted on Nov 9,
2016 and harvested on Jan20, 2017. The correct stand count
(20 plants per row) was maintained after thinning. Data on
date of emergence was recorded on plot bases when 50% of
plants in the plot are emerged the first leaf. Two consecutive
destructive sampling at 20 and 33 days after emergence was
taken by randomly selecting three plants per plot to measure
leaf area, leaf dry weight, and stem dry weight. During
sampling, a representative row from the plot was selected and
all above ground part was harvested. After separating leaf and
stem, the leaf area was measured by portable leaf area meter.
Leaf and stem dry weight was separately obtained after dried
in oven dry for 48 hour at 70°C and recorded as biomass dry
weight during both sampling. Final sampling was taken at 72
day after emergence; sun dried and recorded as total biomass.
2.3. Data Collected
1. Days to 50% emergence were recorded as the number of
days from sowing to when 50% of the plants emerged in
each plot.
2. Leaf area (cm
2
) was recorded by taking a destructive
sample of three plants from the second and fourth row
per plot. Leaf area was measured just before flowering
using leaf area meter. The average leaf area of the three
plants was taken for statistical analysis.
3. Stem and leaf dry weight (gm): - The average of three
randomly taken plants measured in gram and average
weight of the three plants were taken for statistical
analysis.
4. Biomass dry weight: it was measure the central rows
taken per plot and the converted biomass weight (gm
-2
)
used for statistical analysis.
Methods of computing certain parameters that describe
growth parameters that are commonly used in agricultural
research are measured as follows:
Leaf Area is the area of photosynthetic surface produced by
the individual plant over a period of interval of time and
expressed in cm
2
plant
-1
.
Specific leaf area (SLA) is a measure of the leaf area of the
plant to leaf dry weight and expressed in cm
2
g
-1
[13].
 =


[13]
Leaf Area Ratio (LAR) was suggested by [14], expresses the
ratio between the areas of leaf lamina to the total plant
biomass or the LAR reflects the leafiness of a plant or amount
of leaf area formed per unit of biomass and expressed in
cm
-2
g
-1
of plant dry weight.



[14]
Net Assimilation Rate (NAR) is defined as dry matter
increment per unit leaf area or per unit leaf dry weight per unit
of time. The NAR is a measure of the average photosynthetic
efficiency of leaves in a crop community [15].
 = 





 [15]
Where, W1and W2 is dry weight of whole plant at time t1
and t2 respectively
L1 and L2 are leaf weights or leaf area at t1 and t2
respectively; t1 – t2 are time interval in days
NAR is expressed as the grams of dry weight increase per
unit dry weight or area per unit time (g g
-1
day
-1
)

Journal of Chemical, Environmental and Biological Engineering 2021; 5(1): 1-4 3
Relative Growth Rate (RGR) expresses the total plant dry
weight increase in a time interval in relation to the initial weight
or Dry matter increment per unit biomass per unit time or grams
of dry weight increase per gram of dry weight and expressed as
unit dry weight / unit dry weight / unit time (g g
-1
day
-1
)
 =


[15]
2.4. Statistical Analysis
All the measured parameters were subjected to analysis of
variance (ANOVA) using Mixed Model procedure of SAS
version 9.0 [16]. Coefficient of variation, least significance
difference (LSD) test at 5% probability level as described in
[17] and the mean were compared with standard error.
3. Result
Table 1. Mean of days to 50% emergence of three haricot bean varieties.
Varieties Days to 50% emergence
Awassa Dume 11.25a
Omo-95 9.25b
Red Wolayta 9b
LSD 0.05 0.9564
CV 5.621398
CV=Coefficient of variation, least significance difference (LSD) test at 5%
probability level as described in [17]
Table 2. Growth analysis on the specific leaf area (SLA), leaf area ratio (LAR) net assimilation rate (NAR) and Relative growth rate (RGR).
Variety SLA
1
(cm
2
g
-
1
) SLA
2
(cm
2
g
-
1
) LAR
1
(cm
2
g
-
1
)
LAR
2
(cm
2
g
-
1
)
NAR (mgdm
-
2
) RGR (mg g
-
1
day
-
1
)
Omo 95 219.1 278.55 143.74 185.56 0.4146 0.0824
Red wolayta 214.63 264.69 140.01 177.29 0.4458 0.01853
Hawassa Dume 197.88 259.76 134.19 173.16 0.435 0.08185
SE (±) 6.1855 9.9185 7.4289 5.6465 0.01853 0.01337
Where, SpLA1=specific leaf area first harvest, SpLA2=specific leaf area second harvest, LAR1=first harvest leaf area ratio, LAR2=second harvest leaf area ratio,
NAR=net assimilate rate, RGR=relative growth rate.
Table 3. ANOVA for final biomass dry weight.
Treatments Mean (g/m
2
) Letter Group
Hawassa Dume 266.81 A
Omo 95 215.22 B
Red woliata 187.97 B
LSD 0.05 49.342
CV 12.76896
CV=Coefficient of variation, least significance difference (LSD) test at 5%
probability level as described in [17].
4. Discussion
4.1. Days to 50% Emergency
From the above table it shows that there is significant
difference between the haricot bean three varieties (Hawassa
Dume, and Omo 95). Red Wolayta shows the least mean
comparative the other two varieties whereas Hawassa Dume
showed the highest mean of 50% emergency date.
4.2. Specific Leaf Area
According to Wallace et al. [18] genetically different crops
plant show different leaf area and this parameter is an important
physiological parameter because it associated with crop yield.
Yield increament can be achieved by extending
photosynthesis per unit land area [19]. From the above table it
shows that there is mean difference between the haricot bean
varieties (Hawassa Dume, and Omo 95). At the first sample
variety one (Omo 95) show high specific leaf area (219.1)
while cultivar Hawassa Dume show the lowest (197.88). At
the second sample and also variety Omo 95 scores the highest
(278.55) as compare to the other two varieties as shown (Table
2).
4.3. Leaf Area Ratio (LAR)
From the above table it shows that there is mean difference
between the haricot bean varieties (Hawassa Dume, and Omo 95).
At the first sample variety one (Omo 95) show high specific leaf
area ratio (143.74) while variety Hawassa Dume shows the
lowest (134.19) as compared to other. At the second sample
cultivar (Omo 95) scores the highest (185.56) leaf area ration
(Red Wolayta (177.29) and Hawassa Dume score the lowest
(173.16) as compared to Omo 95 as shown on the above table
(Table 2). Highest leaf area ratio of a crop indicates that it has
larger leaf area and this helps the crop to have highest efficiency
of light harvesting which means higher photosynthetic rate.
4.4. Net Assimilation Rate (NAR)
Studies on field crops Watson [20] showed that E differed
from species to species with respect to growing condition and
in controlled environments [21]. Net assimilation rate
indicates that the increment of plant material per its
assimilatory material in a given time. So the cultivar with
highest NAR will tend to have highest plant material in a
given area and time and it have high assimilate rates.
Therefore cultivar (Red Wolayta) have greater assimilate rates
(0.4458). Rakesh et al. [22] reported that higher RGR
indicates increment in dry matter per unit leaf area.
4.5. Relative Growth Rate
From the above table it shows that there is significant
difference between the haricot bean varieties (Hawassa Dume,
and Omo 95). The above table shows that Omo 95 has relative
growth rate (0.0824) as compared to the other varieties of
haricot bean. Rakesh et al. [22] Reported that higher RGR
indicates increment in dry matter per unit dry matter.

4 Dasta Tsagaye et al.: Response of Haricot Bean (Phaseolus vulagris L.) Varieties to Different
Growth Parameters at Hawassa, Southern Ethiopia
4.6. Biomass Dry Weight
According to Escalante et al. [23] the relationship between
the seed yield and biomass with growth parameters are have
directly proportional to each other; with respect to growing
environment and the fertility of the soil. From the above table
it shows that there is significant difference between the haricot
bean three varieties (Hawassa Dume, and Omo 95) in terms of
biomass dry weight. The above ANOVA (table 3) of biomass
dry weight shows that there is no significant difference
between the three varieties and Omo 95 show Hawassa Dume,
Omo 95 and Red Wolayta).
5. Conclusion
For the specific leaf area and leaf area ratio as the plants
continue its growing they did not show constant performance.
The varieties which show higher value at the first sampling
show also increased value at the second sampling and vice
versa. So it is fair to say that these Haricot bean varieties
perform differently across their growing period. As it is shown
on the result, when relative growth rate increase, leaf area ratio
and specific leaf area also increases. So we can conclude that
both leaf area ratio and specific leaf area affect the Haricot
bean growth rate. Regarding to total biomass it is observed
that some variety show significant difference while some
varieties show no significant difference between them. This
indicates that total biomass is not always dependent only on
varieties difference rather there is some other factors.
References
[1] Mohammed, H. 2015. Improving Snap Bean (Phaseolus
vulgaris L.) Production under reduced Input Systems. M. Sc.
Thesis, University of Saskatchewan, Saskatoon.
[2] Abebe, G. 2009. Effect of NP Fertilizer and Moisture
Conservation on the Yield and Yield Components of Haricot
Bean (Phaseolus vulgaris L.) in the Semi-Arid Zones of the
Central Rift Valley in Ethiopia. Advances in Environmental
Biology, 3, 302-307.
[3] Teshale, Assefa, Girma, Abebe, Chemeda, Fininsa, Bulti, Tesso
& Abdel-Rahman M. Al-Tawaha. 2005. Participatory Bean
Breeding with Women and Small Holder Farmers in Eastern
Ethiopia. World Journal of Agricultural Sciences, 1: 28-35.
[4] Dev, J & Gupta, V. P. 1997. Common bean historic view and
breeding strategy. Annals of Biology, 13: 213-219.
[5] Walelign Worku, 2002. Growth and Productivity of Haricot Bean
(Phaseolus vulgaris L.) under Different Moisture and Light
Regimes. Ph. D. Thesis. Agricultural University of Norway.
[6] Girma Abebe. 2009. Effect of NP Fertilizer and Moisture
Conservation on the Yield and Yield Components of Haricot
Bean (Phaseolus vulgaris L.) In the Semi-Arid Zones of the
Central Rift Valley in Ethiopia. Advances in Environmental
Biology, 3: 302-307.
[7] Zelalem Fisseha, 2002. Report on informal survey of major
bean diseases in Metekel Zone. Pawe agricultural research
center. pp. 14-19 (Unpublished).
[8] CSA (Central Statistics Agency).2018. Report on Area and
Crop Production of Major Crops (Private Peasant Holdings,
Maher Season). Statistical Bulletin 586. Issue I. Addis Ababa,
Ethiopia, 19.
[9] Gezahegn Ayele and Dawit Alemu, 2006. Marketing of Pulses
in Ethiopia. pp. 346 -351. presented on Food and Forage
Legumes of Ethiopia: Progress and Prospects.
[10] Teshale Adugna, Mulat Demeke and bezabhe Emana. 2006.
Determinants of fertilizer adoption in Ethiopia. Agricultural
economics society of Ethiopia, Addis Ababa. Ethiopia.
[11] Evans GC. 1972. The quantitative analysis of plant growth.
Oxford: Blackwell Scientific Publications.
[12] GarnierE, Farrar JF, Poorter H, Dale JE, eds. 1999. Variation in
leaf structure: an ecophysiological perspective. New
Phytologist (special issue) 143: 1–221.
[13] Kvet, J., Ondok, J. P., Necas, J., Jarvis, P. G. 1971. Methods of
Growth Analysis. In: Sestak, Z.; Catsky, J.; Jarvis, P. G. (Eds.),
Plant Photosynthetic Production: manual and methods. The
Hague: The Hague Publisher, p. 343-384.
[14] Radford, P. J. 1967. Growth analysis formulae-their use and
abuse. Crop Sci. 7: 171-175.
[15] Williams, R. F. 1946. The physiology of plant growth with
special reference to the concept of. net assimilation rate. Ann.
Bot., Lond., N. S. 10, 41.
[16] SAS Institute Inc. 2008. Statistical analysis software version
9.0. Cary, NC, USA: SAS Institute Inc.
[17] Gomez and Gomez. 1984. Statistical procedures for
agricultural research, 2nd ed. New York: John Wiley and
Sons.
[18] Wallace, D. H., Ozbun, J. L. & Munger, H. M. 1972.
Physiological Genetics of Crop Yield. Adv. Agron., 24:
97-146.
[19] Richards, R. A. 2000. Selectable traits to increase crop
photosynthesis and yield of grain crops. J. Exper. Bot., 51:
447-458.
[20] Watson, D. J. 1947. Comparative physiological studies on the
growth of field crops. I. Variation in net-assimilation rate and
leaf area between species and varieties and within and between
years. Ann. Bot., N. S., II, 41.
[21] Thorne, G. N. I960. Variations with age in net assimilation rate
and other growth attributes of sugar beet, potato and barley in a
controlled environment. Ann. Bot., N. S., 24, 356.
[22] Rakesh P., Vijay P., Madurima D., Mahesh M. and Ramesh C.
M. 2017. “Physiological Techniques to Analyze the Impact of
Climate Change on Crop Plants”. Division of Plant Physiology,
IARI, New Delhi.
[23] Escalante Estrada J. Alberto and Ma. Teresa Rodriguez G.
2008. Phenology, growth and analysis and yield of beans in
alkaline soils, Armual Report of the bean Improvement
Cooperative, 51: 238-239.