effects of climatic variation on yield of upcountry tea: a
TRANSCRIPT
RESEARCH POSTER PRESENTATION DESIGN © 2015
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‘Ceylon tea’ industry plays a vital role in relation to the economic sustainability in
Sri Lanka. Low productivity of tea growing areas in the country has been attributed
to climatic changes, ageing of tea fields, low replanting rate, land degradation,
worker shortage and high input cost. Climatic variability has direct and indirect
impacts on tea production in Sri Lanka.
Tea crop is highly sensitive for water adequacy and affect for plant growth and
development. Optimum rainfall required for tea varied from 350 ± 20 mm/month in
Up Country Wet Zone.(Amarathunga et al,2007) Photosynthesis rate is decreased
by 50%, when water is reduced by 10%. Lack of sunshine at high rainfall is affected
for the low yield. High rainfall is reduced the shoot growth of the tea plant due to
water logging condition of the soil. Tea plants are very sensitive for monthly rainfall
variations. Amount of rainfall in previous month was affected to productivity of
crop on next month. Climatic variations is a critical factor for yield variability of
upcountry tea industry.
Kelani Valley Plantations PLC(KVPL) is one of leading plantation company in Sri
Lanka. KVPL Upcountry tea saturated 8 estates in Hatton Region and 6 estates in
Nuwaraeliya Region.
Introduction
To identify impact of rainfall variation on productivity of upcountry tea lands
managed by Kelani Valley Plantations PLC in Sri Lanka
Objective
Results and Discussion
Conclusion
Vagaries in climate is a critical factor for yield variability of the upcountry tea
industry. Maintaining good agricultural practices (GAP) and choosing tea cultivars
more adaptable to varying climatic condition will mitigate the effects of climatic
variation on productivity of tea lands.
References
Liu, C. L., Zhang, Q., Singh, V.P and Cui, Y.(2011). Copula-based evaluations of
drought variations in Guangdong, South China. Natural Hazards, 59, 1533-1546
Poudel, S., and Shaw, R., (2016) Relationships between Climate Variability and
Crop Yield in a Mountainous Environment : A Case study in Lamjung District,
Nepal. Climate. 4,13
Preprah, K., (2014) Rainfall and Temperature Correlation with Crop Yield: The
Case of Asunafo Forest, Ghana. International Journal of Science and Research
(IJSR), 3, 784-789
Wijeratne, M.A., Anandacoomaraswamy, a., Amarathunga, M.KS.L.D., Rathnasiri,
J., Basnayake B.R.S.B., Kalva, N.,(2017) Assessement of impact of climatic
change on productivity of tea(Camelia Sinenssis L.) plantations in Sri Lanka.
Journal National Science foundation Sri Lanka. 35(2), 119-126
Acknowledgement
I wish to offer my deepest gratitude to Dr. Prasad Dharmasena, Director of NIPM,
Mr. Roshan Rajadurai, Managing Director of Kelani Valley Plantations PLC, Mr.
Maruday Kandasamy, Chief Clerk of General Manger Office, Mrs. Niluka
Amerasena and Ms. B.N Gayathri, Staff Members of General Mangers’office.
Manawasinghe, K.S.1, Abeysinghe, D.C.1, Weerakoon, A.2, Thennakoon, T.M.N.S.3
Department of Plantation Management, Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, Makandura, Gonawila (NWP), 60170, Sri Lanka1
Kelani Valley Plantations PLC, Dickoya, Hatton2
Faculty of Science, University of Peradeniya, Peradeniya, Sri Lanka3
Effects of Climatic Variation on Yield of Upcountry Tea: A Case Study based on Upcountry Tea Estates of Kelani Valley Plantations PLC in Sri Lanka
Methodology
Study Site
The Study was conducted in upcountry tea estates in Kelani Valley Plantations
PLC. Tea estates data of rainfall and yield from 2004 to 2015 was used.
Selected Indicators for the Study
Pearsons’Correlation Coefficient
Pearson’s Correlation Coefficient was used to determine the correlation between the
rainfall and the tea yield. (Poudel et al, 2016)
Where,
n = Number of Pairs of Scores
Ʃxy = Sum of the products of paired scores
Ʃx = Sum of x scores
Ʃy = Sum of y scores
Ʃx = Sum of squared x scores
Ʃy = Sum of squared y scores
Methodology Cont.
Standard Precipitation Index
Standard Precipitation index was used to identify Climatic condition within a year in
the regions(Table 1) (Liu et al.2011).
SPI = X1 –X
S
Where,
X1 – rainfall
X - mean value
S - Standard deviation
Table 1 :- SPI values and Climatic events
Precipitation Trend
Total annual rainfall was recorded the mean of 3044 mm in Hatton Region and 2606 mm in Nuwaraeliya Region, Standard deviation of 455mm in Hatton Region and
322mm in Nuwaraeliya Region. It reveals an ascending trend lines of annual rainfall from 2004 to 2015 in both regions, However the trend line in Nuwraeliya region
indicates slightly increasing.(Figure 1)
Figure 1:- Annual Precipitation trends in KVPL upcountry estates in Hatton and
Nuwaraeliya regions from 2004 to 2015
The maximum rainfall was recorded in month of June and the minimum rainfall was recorded in month of January (Figure 2). Standard deviation 121mm in Nuwaraeliya
region and 129mm in Hatton region.
Standardized Precipitation Index
Table 2 :- Variations of Climatic conditions across tea growing areas in Upcountry KVPL estates
FOE – Frequency of events, POC – Percentage of Occurrence
Monthly rainfall was highly fluctuated within the year. There were not any extremely dry or severely dry months both Hatton and Nuwaeaeliya tea growing regions.
extremely wet month was recorded in Hatton region and Severely wet month was recorded in Nuwaraeliya region (Table 2).
Rainfall- Crop Yield Relationship
Pearsons’Correlation Coefficient
There was weak Positive correlation between annual rainfall and yield, in Hatton Region (r = +0.12 ) and Nuwaraeliya Region ( r = +0.15).
Strong positive correlation is shown between previous month rainfall and following month yield, in Hatton Region ( r= +0.62) and Nuwaraeliya Region(+0.70). Tea plants
are very sensitive for monthly rainfall variation.
Climatic events Hatton Region Nuwaraeliya Region
FOE POC (%) FOE POC (%)
Extremely Wet 1 8.33 - -
Severely Wet - - 1 8.33
Moderately Wet - - 1 8.33
Mild Wet 1 8.33 4 33.33
Normal Wet 3 24.99 - -
Normal Dry 4 33.33 2 16.66
Mild Dry 1 8.33 1 8.33
Moderately Dry 2 16.66 3 24.99
Severely Dry - - - -
Extremely Dry - - - -
y = 15.655x + 2504.1R² = 0.0307
y = 82.461x + 2508.7R² = 0.4258
0
500
1000
1500
2000
2500
3000
3500
4000
4500
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Nuwaraeliya Hatton Linear (Nuwaraeliya) Linear (Hatton)
0.00
100.00
200.00
300.00
400.00
500.00
600.00
700.00
Nuwaraeliya Hatton
Figure 2 :- Monthly Precipitation trends in KVPL upcountry estates in Hatton and
Nuwaraeliya regions from 2013 to 2015
SPI Value Category
2.0+ Extremely Wet
1.5 to 1.99 Severely Wet
1.0 to 1.49 Moderately Wet
0.5 to 0.99 Mild Wet
0 to 0.49 Normal wet
-0.1 to -0.49 Normal dry
-0.5 to -0.99 Mild dry
-1.0 to -1.49 Moderately dry
-1.5 to -1.99 Severely dry
-2.0+ Extremely dry
SPI = X1–XS