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Yield variability at the Tea Research Foundation of Kenya
Agricultural and Forest Meteorology, 61 (1992) 237-252
237
Elsevier Science Publishers B.V., Amsterdam
Yield variability at the Tea Research Foundation of Kenya C.O. Othieno a, William Stephens b and M.K.V. Carr b aTea Research Foundation of Kenya, P.O. Box 820, Kericho, Kenya bDepartment of Agricultural Water Management, Silsoe College, Silsoe, Bedford MK45 4DT, ( UK) (Received 22 June 1991; revision accepted 18 April 1992)
ABSTRACT Othieno, C.O., Stephens, W. and Carr, M.K.V., 1992. Yield variability at the Tea Research Foundation of Kenya. Agric. For. Meteorol., 61: 237-252. The results of an experiment to monitor the effects of weather variability on the yield of tea (Camellia sinensis) under constant management over a 16 year period are reported. The overall yield potential was limited to about 2 t ha ~ by the low air and soil temperatures associated with the high altitude (2180m) which restricted shoot extension rates. The within-year yield distribution was determined by sometimes large potential soil water deficits (up to 400 mm) during the dry season (which restricted yields of made tea by about 1.3 kg ha- ~mm ~) and by the incidence of damaging hail storms throughout the rest of the year (which caused mean losses of 10% of the total annual yield). The implications of this analysis for tea research at Tea Research Foundation of Kenya (TRFK) and elsewhere are discussed.
INTRODUCTION
Tea is grown at latitudes ranging from the equator to 33°S in Natal, South Africa and 49°N in Georgia, Russia (Huang, 1989), and from sea level (for example in Bangladesh) to as high as 2500 m in Kenya (Carr and Stephens, 1992). It is an unusual crop in that the young shoots which form the useful product, are harvested at intervals throughout the growing season with the frequency of harvesting normally determined by the mean air temperature and/or the rainfall distribution (when irrigation is not practised). Various attempts have been made to relate yields to current and antecedent weather conditions using a range of empirical factors (e.g. Sen et al., 1966) but these have rarely been interpreted in terms of the processes controlling growth (Squire and Callander, 1981), and therefore have had only local significance. Correspondence to: C.O. Othieno, Tea Research Foundation of Kenya, P.O. Box 820, Kericho, Kenya.
0168-1923/92/$05.00 © 1992 Elsevier Science Publishers B.V. All rights reserved.
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Statistical analyses of this type have also been complicated by the effects of the stage in the pruning cycle, and the times after the application of fertilizer. In a renewed attempt to quantify the effects of the principal weather variables on the yield of tea, an experiment was initiated at the Tea Research Foundation of Kenya (TRFK) in 1970 in which the effects of time of pruning and/or fertilizer applications on sequential yields were minimised (Carr and Othieno, 1971). The climate at the headquarters of T R F K in Kericho is dominated by the effects of the high altitude and its proximity to Lake Victoria and the equator. This results in uniform, but relatively low prevailing air and soil temperatures throughout the year, and high total rainfall, though there are annual droughts of variable duration and intensity. In addition, the whole of 15000 ha of commercial tea in the district is subject to frequent hailstorms, perhaps the highest incidence in the world (Schnell and Tan-Schnell, 1978), which can cause considerable losses in yield. For example, it has been estimated that over the 5 year period 1977-1982 hail damage resulted in a loss of 14000 tonnes of tea in the Kericho and neighbouring Nandi Hills districts (Mwakha, 1983). This was equivalent to about 140kgha -~ per annum. The majority of the commercial estate and smallholders' tea in the Kericho district is planted at altitudes from about 1700-2100 m and the T R F K is at the extreme end of this altitude range. In a companion paper, the climate and weather variability at T R F K have been quantified using historical weather data (Stephens et al., 1992). In this paper the results of the weather-yield correlation experiment over the 16 year period December 1970 to September 1986 are presented. Attempts are made to derive empirical relationships between yields and measured or derived weather variables, and to interpret the results in terms of physiological processes. METHODS
Climate Climate and weather variability at the Tea Research Foundation of Kenya (0°22'S 35°2 I'E; altitude 2178 m) have been fully described elsewhere, but are summarised here for clarity.
Temperature Mean maximum temperatures range from around 21°C in June and July to about 25°C in March: minimum temperatures are close to 8-9°C throughout the year. Mean daily air temperatures range from about 15.5 to 18°C. The effective thermal time for shoot extension, above a base temperature of 12.5°C (Tanton, 1982a), is therefore only 3-5.5 day °C. Assuming that 475 day °C are
YIELD VARIABILITY AT THE TRFK
239
needed for an axillary bud released from apical dominance to grow to 3 leaves and a bud (Mkwaila, 1987) the length of the shoot replacement cycle should vary from about 95 days in February to 130 days in May. Soil temperatures, at 0.3 m depth beneath short grass, are usually in the range 17-19°C.
Saturation deficit Midday values rarely exceed the critical value of 2.3 kPa (Tanton, 1982b). The total annual saturation deficit time is analogous to thermal time and is defined as the sum of daily saturation deficits above 2.3 kPa (Stephens et al., 1992).
Radiation The mean daily solar radiation total is in the range 1 7 - 2 2 M J m -2, with annual receipts of about 67 TJ h a - t.
Wind Wind runs are generally low, ranging from 120 to 160 km per day.
Rainfall The mean annual rainfall is about 2150mm of which about 90% falls between mid March and mid November.
Evaporation The daily mean rates of potential evapotranspiration range from 3 m m per day in April to 4.5 m m per day in mid March.
Soil water deficit (SWD) The maximum potential soil water deficit during the long dry season varies widely from between 75 m m to more than 400 mm. The actual total soil water stress time, calculated by summing the potential soil water deficit on a daily basis above a limiting deficit of 5 0 m m (SWSTs0), ranges from 0.5 to more than 25 day m.
Hail At the experimental site there are on average 25 hail storms every year. Soi/s The soils are very deep, well drained volcanic clays with a water holding capacity of about 170-220 m m m - i (Scott, 1962). At T R F K roots of mature tea have been observed to extend to depths of 6 m (Cooper, 1979) but the effective rooting depth is normally about 1.5-3 m (Carr, 1977).
Field experiment The experiment was initiated in 1970 in an area of 8-year old unshaded
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C.O. OTHIENO ET AL.
Assam-type tea, originally propagated from seed which had been obtained from Ambangulu estate in Tanzania and planted at 1.5 m × 0.75 m spacing. The experiment was sited 200 m away from a standard agro-meteorological station. In order to isolate any effects of the time of pruning on yield distribution, one of the 156 bushes in each plot was pruned every week giving a staggered 3-year pruning cycle. Similarly, to avoid an uneven yield response to fertilizer applied infrequently, equal monthly applications were given totalling 222 kgN ha-I year -~ . Fertilizer was applied as NPKS 25:5:5:5 until 1978, and as N P K 20:10:10 c o m p o u n d thereafter. Shoots, mainly two leaves and a bud, were harvested at weekly intervals from each plot, except for the period from February 1972 to April 1973 when the harvest interval was increased to 10 days. The fresh weight of leaf tea was converted to the made tea equivalent using a constant value of 0.22.
Yield analysis Initially annual yields were examined to determine whether there was a year-to-year trend not accounted for by the meteorological variables. The year was then split into three periods, based on mean temperatures (Tmean)and rainfall; these were designed to correspond as closely as possible with the main seasons. First, (a) a warming period from September to November (Tme,n increasing from 15.3 to 16.0°C), which could be either wet or dry depending on whether or not there was a short dry season; then (b) a warm dry period from December to March (Tme~napprox. 16.5°C); and finally (c) a cooling wet period from April to August (Tm~, decreasing from 16.4 to 15.0°C). Year-toyear variations in seasonal yields were analysed by first identifying and removing any annual trend, and then relating the residual variation to measured climate variables, such as air and soil temperature, saturation deficit, solar radiation, wind and rainfall; and then to derived variables, such as evapotranspiration, soil water deficit, thermal time, soil water stress time and saturation deficit time, using stepwise multiple regression. The possible carry over effect of the yield obtained in the previous season was also included as a predictor variable. A preliminary examination of the data available suggested that hail was the most important determinant of within-season yield variation. Specific hailstorms classified as 'moderate' or 'severe' in the experimental record book were therefore examined to determine: (1) what proportion of yield was lost, (2) how long yields took to return to their pre-storm levels. These results were compared with yield losses estimated subjectively by experienced estate management staff, by considering yields in the 3 weeks following the hail storm with the yield in the week preceeding the storm. A frequency distribution of estimated monthly yield losses was calculated to assess whether most hail
241
YIELD VARIABILITY AT THE TRFK
2.5 due to hail coolin wet Apdl -g~gulrt wllrm dry December - March warrnln Sept ~lgber - November
," "" i
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i
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Harvest year Fig. 1. Annual yields at TRFK, Kericho showing the contribution of crop harvested in each of the three seasons (D warming period, [] warm dry period, [] cooling wet period), and ~:! the estimated annual yield loss owing to hail.
damage was caused by a few large storms, or whether each storm caused more or less equal damage. RESULTS
Year-to-year yield variation Annual yields of made tea averaged only 1.35tha -1 and showed wide year-to-year variation from less than 0 . 9 t h a -1 in 1982/1983 to just under 2.0tha -~ in 1972/1973 (Fig. 1). This was much greater than the annual variation in any of the meteorological variables except rainfall, soil water deficit and hail. There was no discernible increase in annual yields over time. Stepwise regression analysis on all variables showed that the maximum potential soil water deficit (SWDmax, mm) was the best predictor of yield explaining about 50% of the annual variation (Y~,n, kg ha -~) Yann
=
(1930
___
243) - - (2.01
___ 0 . S 5 ) S W D m a
x (n
=
15; R 2 =
0.45)
(1)
Figures following the coefficients are standard errors. For the range of SWDma x recorded this implies annual yield losses (estimated from the mean yield with zero SWD) of 0.15 to 0.80tha t with an average of 0.55tha -~. This relationship was not improved by including a
242
C.O. O T H I E N O E T AL.
"7
1000
e-
(o
800
600
E "O
400
tO
200
1O0
200
300
400
maximum potential soil water deficit (mm) F i g . 2 . Relationship between the dry season yields in the field experiment and the maximum potential soil water deficit at TRFK, Kericho. ( - fitted regression line; Y = 8 0 0 - 1 . 3 0 S W D m . x ; 9 5 % confidence limits for - - - m e a n ; • . • individual predicted values).
coded value for year (to represent a technology trend) or any other meteorological or derived variable. The yield loss owing to hail damage over the period 1970-1986 in the field surrounding the experiment, averaged about 0.22 t ha-~ year -l , corresponding to a mean annual yield reduction of about 16%. There was, though, a wide variation in the losses sustained, from less than 0.02 to almost 0.6 t ha ~ year- i (in 1970/1971), representing up to 45 % of the average annual yield. Between season yield variation
Annual yield totals can mask climate related fluctuations between seasons. The analysis was therefore extended to cover the warm dry, cooling wet and warming (wet or dry) periods defined on the basis of temperature and soil water deficits (see above). The relationships between warm dry season yields (Ydry) and all the meteorological and derived variables were analysed using stepwise multiple regression. There was a highly significant negative relationship (P < 0.001) between yield (kgha -I) and the maximum potential soil water deficit (mm) (Fig. 2). Incorporating a time trend in the regression equation did not improve the fit.
Ydry
=
(800 + 111) -- (1.30 ±
0.24)SWDma
x
(n = 16; R 2
=
0.68)
(2)
The total soil water stress time (SWST; day m), summed above a critical deficit (CD) of 50 mm, was also a good predictor explaining about 70% of the warm dry season yield variation. Ydry
----
(767 -I- 108) -- (1051 ___ 178)SWSTs0 (n
=
16; R 2 =
0.71)
(3)
YIELD VARIABILITY AT THE TRFK
243
The intercept and the slope of the relationship depend on the CD selected; when values of 0 and 100ram were substituted a similar proportion of the variation was estimated. The high level of year-to-year variation in yields precluded the accurate identification of a CD using the procedure developed by Stephens and Carr (1989). In the cooling wet period from April to August and the warming period from September to November there were no significant relationships between current yields and yields in the previous season, or with any of the actual or derived weather variables. The lack of any significant relationship is perhaps surprising, although throughout both these periods the irregular occurrence of damaging hail storms appeared to mask any weather related yield variation. Further analysis was therefore undertaken to investigate the within season variations in yield. Within season yield variation
On a week-to-week basis, yields fluctuated widely (Fig. 3) so part of the analysis involved searching for consistent patterns related to meteorological or derived variables. In particular, it is important to identify the critical SWD at which yields begin to decline to determine the sensitivity of the tea to short duration droughts. In eight of the 15 warm dry seasons analysed, weekly yields began to decline after a clearly defined break point in the latter half of December or early January. This change occurred at a critical deficit of about 85 mm (Fig. 4). Once the potential SWD exceeded 200 mm the rate of decline in weekly yields fell from 2 to 1 kg for every 10 mm increase in SWD. In years when the SWD did not exceed 100 mm no decline in yield owing to water stress was observed. When weather conditions such as drought, or cold weather, restrict shoot extension for a long time the removal of the limiting factors may result in a series of discrete yield peaks interspersed with deep troughs. This phenomenon, often known as the 'Fordham' cycle, is the result of rapid synchronised growth by the whole population of shoots (Fordham, 1970). The amplitude of the cycle depends on the duration and severity of the limiting period, and on the subsequent rates of shoot extension, which are largely controlled by the prevailing temperatures. Following the start of the rains in April there was often evidence of the beginning of a 'Fordham' cycle (e.g. in 1974, 1975, 1982, 1983, and 1984)but closer examination of the records suggested that the rapid decline in yields after the subsequent peak was the result of falling temperatures which increased the duration of the shoot replacement system to 130 days (Stephens et al., 1992). Hail damage was another confounding factor which limited the amplitude of the expected yield peak. Overall, only 20% of the recorded hail storms caused assessable yield losses
o
o
o
pote~lal soil water deficit (ram)
o
o
o o
rainfall (ram week 1) ~
° o
weekly yield of made tea (kg hd 1) o
o
o
o
potential soil water deficit (mm) o
~
rainfall (mm week 1) o
weekly yield of made tea (kg ha1 )
YIELD VARIABILITYAT THE TRFK
245
1
100 1 c) 1981-1986
| E~ 3, V
E
1°I ~,..,,. J ,,.
l,.,,,i,..,JL. JilL,i,,
(.1 "o
200 300
i
400
1981 I
1982
L
1983
I
1984
I
Fig. 3. Weekly variation in rainfall, soil water deficit and yield from the field experiment at T R F K , Kericho for the periods (a) 1971-1976; (b) 1976-1981; (c) 1981-1986.
t-40
~30
E .I
0
50
100
150
200
250
300
350
Potential soil water deficit (mm)
Fig. 4. Relationship between mean weekly yields and SWD in consecutive weeks during the dry season at T R F K , Kericho. (Bars represent standard error of the mean, n = 8).
246
C.O. OTH1ENO
ET AL.
100 A
v
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~
40 15.1
20
~
3.2
1.0
0.5
100
150
>200
j
0
50
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estimated yield loss (kg ha 1 ) Fig. 5. Frequency distribution of yield losses from individual storms on field adjacent to the experiment T R F K , Kericho: 1970-1986; [] non-damaging and II damaging storms.
and in three quarters of these the damage was estimated to be less than 5 0 k g h a -~ per event, which is equivalent to about 2.5% of the potential annual yield of around 2.0 t h a - i (Fig. 5). However, from April to November the damage caused by individual hail storms was considerable. The worst storms, recorded in October 1970 (shortly before the start of the experiment) and July 1982, caused yield losses of more than 0.3 t ha-f per event, equivalent to over 15% of the potential annual yield. Damage of this magnitude can be expected to occur about once in every 200 storms or once in every 8 years. In the field surrounding the experiment, the average yield losses resulting from storms classed in the experimental record book as 'moderate' and 'severe' were assessed as 4 0 k g h a -1 and 8 5 k g h a i, respectively. A more detailed analysis of records for individual storms showed that yields from the meteorological correlation plots were reduced after 'severe' hailstorms by approximately 80% for a period of 4 weeks before recovering rapidly over the next 4 weeks (Fig. 6). By contrast, hail storms classified as 'moderate' caused a 60% reduction in yield in the following week but yields then recovered steadily over the next 6 weeks. The yield lost as a result of each storm was estimated by accumulating the difference between the mean pre-storm yield and the mean yield for each subsequent week. On average 'moderate' storms caused a total estimated yield reduction of 50 kg ha -I , which is only slightly more than the field assessments. By contrast, the losses estimated for 'severe' storms were 130kgha -~ about 50% greater than the field estimates. This suggests that the method of field assessment may need revision when bushes take a long time to recover from the damage. No other short-term relationships between weather and yield were observed, presumably because of the overwhelming effects of erratic hail storms during the period April-November which disrupted any developing pattern.
YIELD VARIABILITY AT THE TRFK
E
247
120
0
.~ 1O0
~3
60
O3
,-
40
0
i
0
~ 20
sevo:
n
•~ "N,
0 w e e k s since hailstorm
Fig. 6. Relative yields p r e c e d i n g a n d f o l l o w i n g hail s t o r m s classified as m o d e r a t e + --t:3-- at T R F K , K e r i c h o .
a n d severe
DISCUSSION
A basis for comparison Squire (1985) suggested that the potential yield of tea (Ypo,; tha-~) is determined by: (1) the incoming photosynthetically active solar radiation (S; TJ ha-~ where 1TJ = 10 ~2J); (2) the proportion of radiation intercepted by the crop canopy (i; nondimensional); (3) the conversion efficiency of intercepted solar radiation to dry matter (e; tTJ-~); (4) the proportion of dry matter partitioned to harvestable shoots (the harvest index, HI; non-dimensional ratio), as follows rpot =
S.i.e.HI
(4)
At T R F K , the mean annual incident solar radiation is about 67 TJ h a - i of which slightly less than half is photosynthetically active. The canopy of well managed tea covers the ground within about three to four months after pruning (Othieno, 1983) and, thereafter, about 95% of the incoming radiation is intercepted by green leaves (Smith et al., 1992). Thus in the experimental area, where one bush was pruned every week over a 3 year pruning cycle, about 90% of the incoming radiation would be intercepted by the canopy throughout the year, so S x i = 30 TJ ha -I . Little work has been reported on conversion efficiencies or harvest indices in tea. However, in an experiment carried out at T R F K in 1977/1978, the total
248
C.O. OTHIENO ET AL,
dry matter production of clone 6/8, including roots, was 16.9tha ~year (Magambo and Cannell, 1981) which corresponds to a conversion efficiency of 0.6tTJ I photosynthetically active radiation (PAR). By contrast, many temperate C3 crops have considerably larger conversion efficiencies of about 1.4tTJ -I (Monteith, 1977) and in tropical perennial plantation crops the largest recorded values are in the range 1.0-1.7tTJ -~ (Corley, 1983). As photosynthesis is one of the most temperature-sensitive aspects of growth (Jones, 1983) the low conversion efficiency recorded at T R F K may be due in part, to the low ambient temperatures prevalent at this altitude (Stephens et al., 1992). The harvest index is also temperature dependent to a great extent since, in the absence of water stress, shoot extension is proportional to temperature above a base which is generally taken to be 12.5°C though there is evidence of clonal variations in base temperature from 7 to 15°C (Tanton, 1982a; Obaga et al., 1988; Stephens and Carr, 1990). During periods when shoot growth is restricted by low temperatures, dry matter production continues but a greater proportion is partitioned to the roots (Fordham, 1972). In the experiment on partitioning reported by Magambo and Cannell (1981), the annual yield of shoots (mainly two leaves and a bud) was 1.4 t ha ~, which is close to the mean yield from seedling tea in the experiment reported here. This corresponds to a harvest index of 0.08, which is only about one quarter of that recorded for other tropical perennial crops (Corley, 1983). The harvesting policy, (i.e. the guide lines on acceptable shoot size and stage of growth) and the method of harvesting are also important determinants of yield through their effect on the harvest index. For instance, increasing the proportion of shoots harvested with three leaves and a bud by extending the interval between harvests, increased yields from an irrigation experiment in Mulanje, Malawi by about 30% (Mkwaila and Grice, 1988). Similarly mechanical harvesting, which unselectively removes all shoots protruding above the plucking table, raised the annual yield of seedling tea at Chepgoiben Estate in Kericho (altitude approximately 2000m) from 2.5 t ha-~ when hand plucked to over 5.8 t ha-~ when machine harvested at 42 day intervals (Mwakha, 1988). The reasons for this remarkable increase with mechanical harvesting are not yet fully understood, but must be attributable in part to a larger harvest index rather than to any change in the proportion of solar radiation intercepted by leaves or converted to dry matter. The constant management imposed on the field experiment reported here allow the results to be considered in the absence of any management dependent changes in harvest index.
Year-to-year yield variation The mean annual yield of tea in the experiment was only 1.4 t ha ~but in
YIELD VARIABILITY AT THE TRFK
249
individual years yields varied around the mean by _+40%. Yield losses owing to drought were the major cause of this variation and averaged approximately 0.4 t ha -I . Hail damage reduced yields by, on average, a further 0.2 t ha I so that in the absence of hail and drought the potential yield for seedling tea at this site is around 2 t h a - ' . This value is consistent with estimates based on long term commercial yields from an estate in Kericho at a similar altitude. (Carr and Stephens, 1992). Intercepted solar radiation sets a limit on the total dry matter production whilst the conversion efficiency (e) and the harvest index (HI), which control the actual dry matter produced and the proportion allocated to the young shoots, are temperature dependent. At T R F K , the annual receipt of solar radiation, 6 years out of 10, is 6 5 - 7 0 T J h a ~, a variation around the mean of only _+4%. By contrast, because air temperatures are close to the base temperature for growth throughout much of the year, there are larger year-toyear fluctuations in the length of the potential shoot replacement cycle (Stephens et al., 1992). The responses however, are modified by dry weather during January to March when the critical soil water deficit may be exceeded in about 6 years in 10. The extent to which temperature dominates the yield potential in the Kericho district is well illustrated by the relationship between annual yield and altitude for 21 estates with similar management policies (Fig. 7). The fitted line represents the theoretical relationship between altitude and the duration of the shoot replacement cycle, assuming an adiabatic lapse rate of 6°C km-~; it suggests a decrease in yield of between 0.2 and 0.3 t for every 100m increase in altitude, with yields declining more rapidly above about 2200 m. Since yields on the high altitude (2200 m) estates have remained virtually constant at 2 t ha ' over the 15-year period since 1970, whilst yields on similar estates only 300-400m lower have doubled from 2.0 to 4.0 t ha -~ over the same time interval (Carr and Stephens, 1991), the rate of loss of yield per unit increase in altitude has been increasing with time, and is therefore now of greater commercial importance. The analysis of course ignores any effect on quality of the manufactured tea (Owuor et al., 1990). In summary, the overall ceiling to the annual yields of tea in high altitude (2000 m + ) areas of Kericho such as T R F K is determined by the ambient air (and soil) temperatures but within these constraints large soil water deficits (> 120mm) may reduce the yields by up to 20% whilst on average a further 10% will be lost because of hail damage. Between and within season yield variations
Yields in Kericho are more evenly distributed through the year than in the major tea growing areas of Tanzania and Malawi (Carr and Stephens, 1992). In these areas south of the equator the distribution between seasons is deter-
250
C.O. OTHIENO
•- 2 ,,C
~
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s
.~-
-
,
\
\ \
E
ET AL.
\
\ \
\
2
\ \
\
m
\ C ¢,,
\ \ \ \\
2000
2500
altitude (m) Fig. 7. Relationship between 1984/1985 a n n u a l yields and altitude for 21 estates in the Kericho district. The fitted lines represents - the predicted relationship between yield and s h o o t replacem e n t cycle duration, and the 95% confidence limits for - - - mean; • •. individual predicted values.
mined primarily by the occurrence of large seasonal differences in temperature and soil water status. By contrast, the fluctuations within seasons are caused by the rapid amelioration of limiting weather conditions such as low soil and air temperatures, and/or large saturation deficits, and/or large SWD leading to the initiation of synchronised shoot growth which results in a cyclical series of yield peaks. In Kericho, these cycles can be expected to develop at the beginning of the rains in April, and as temperatures rise in September and October. In April, however, they rarely occur because temperatures at this time are falling, and because developing yield peaks are disrupted by hail. In September and October hail is even more prevalent but it is doubtful whether the necessary conditions exist for the development of a 'Fordham' cycle since the increase in temperatures is gradual rather than rapid leading to a steady rise in shoot growth rates.
YIELD VARIABILITYAT THE TRFK
251
Implications The T R F K is sited close to the upper altitudinal limit for economic tea production. Effects of altitude on tea quality (Owuor et al., 1990) at present price differentials do not compensate for the relatively small yields. Low soil and air temperatures throughout most of the year restrict shoot growth rates, and can dominate the effects of other treatment variables (such as fertilizers) on yields recorded in experiments conducted on this site. Inconclusive results for a long term (30 year) shade experiment may perhaps be explained by the overriding influence of low temperatures on yield. By contrast increasing soil temperatures using plastic mulch in newly planted tea can increase shoot growth rates (Othieno and Ahn, 1980). It is essential that everyone is aware of these factors, otherwise scientists and the industry they serve can be misled. More experiments must be carried out in representative tea growing areas if results of general value are to be obtained. However, the immediate commercial implications of the results suggest that it would appear to be unwise to establish new tea areas at altitudes greatly in excess of 2200 m in Kenya if they are to be financially viable. Nevertheless, the main station does, in theory, allow clones to be selected which will grow at lower base temperatures, or which have a faster response in terms of shoot extension rates per °C. Indeed at least one clone with a low (7°C) base temperature may have already been identified (Obaga et al., 1988). Research organisations and growers should always exercise caution when attempting to extrapolate experimental results from one location to another. We await similar descriptions of the climate, weather and yield variability at the other major tea research stations so that the transfer of knowledge can be achieved with greater precision in the future. ACKNOWLEDGEMENTS
The design of the field experiment was based on an idea of the late J.C. Templer who initiated a similar experiment in Uganda at the same time. This analysis was undertaken as part of a research project sponsored by the UK Overseas Development Administration. REFERENCES Carr, M.K.V., 1977. Changes in the water status of tea clones during dry weather in Kenya. J. Agric. Sci., 89: 297-307. Carr, M.K.V. and Othieno, C.O., 1971. Weather and yields. In: Tea Research Institute of East Africa Annual Report 1971, Tea Research Institute of East Africa, Kericho, pp. 36-37. Carr, M.K.V. and Stephens, W., 1991. Climate, weather and the yield of tea. In: K.C. Willson and M.N. Clifford (Editors), Tea: Cultivation to consumption. Chapman and Hall, London, pp. 87135.
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Corley, R.H.V., 1983. Potential productivity of tropical perennial crops. Exper. Agric., 19: 217-237. Cooper, J.D., 1979. Water use of a tea estate from soil moisture measurements. East Afric. Agric. For. J., 43: 102-121. Fordham, R., 1970. Factors affecting tea yields in Malawi. PhD. Thesis, Bristol University, Bristol, UK, pp. 141-160. Fordham, R., 1972. Observations on the growth of roots and shoots of tea (Camellia sinensis, L.) in Southern Malawi. J. Hortic. Sci., 47: 221-229. Huang, S., 1989. Meteorology of the tea plant: A review. Agric. For. Meterol., 47: 19-30. Jones, H.G., 1983. Plants and microclimate. Cambridge University Press, Cambridge. Magambo, M.J.S. and Cannell, M.G.R., 1981. Dry matter production and partition in relation to the yield of tea. Expl. Agric. 17: 33-38. Mkwaila, B., 1987. A comparative observation of shoot growth in Mulanje and Thyolo. Tea Res. Found. Cent. Afric. Q. Newsl., 87: 13-15. Mkwaila, B. and Grice, W.J., 1988. Review of results from the Bloomfield irrigation trial on mature tea. Tea Res. Found. Cent. Afric. Q. Newsl., 92: 4-6. Monteith, J.L., 1977. Climate and the efficiency of crop production in Britain. Philosophical Transactions of the Royal Society, London B 281: 277-294. Mwakha, E., 1983. Hail reports from Kericho and Nandi tea areas (1977-1982). Tea, 4(2): 8-10. Mwakha, E., 1988. Agro 8a: Mechanical harvesting of seedling tea at different heights and intervals. In Annual Report 1988. Kericho: Tea Research Foundation of Kenya, pp. 8-9. Obaga, S.O., Squire, G.R. and Langat, J.K., 1988. Altitude, temperature and the growth rate of tea shoots. Tea, 9(1): 28-33. Othieno, C.O., 1983. Effect of weather on the recovery from pruning and yield of tea in Kenya. J. Plant. Crops, 11 (Suppl.): 44-52. Othieno, C.O. and Ahn, P.M., 1980. Effects of soil mulches on soil temperatures and growth of tea plants in Kenya. Expl. Agric. 16: 287-294. Owuor, P.O., Obaga, S.O. and Othieno, C.O., 1990. The effects of altitude on the chemical composition of black tea. J. Sci. Food Agric., 50: 9-17. Sen, A.R., Biswas, A.K. and Sanyal, D.K., 1966. The influence of climatic factors on the yield of tea in the Assam Valley. J. Appl. Meteorol., 5: 789-800. Schnell, R.C. and Tan-Schnell, S.N., 1978. Tea litter: a prolific source of ice (hail?) nuclei. Tea East Afric., 18(2): 20-24. Scott, R.M., 1962. Summary of soil survey observations on Sambret Valley. East Afric. Agric. For. J., 27: 22. Smith, B.G., Stephens, W., Burgess, P.J. and Carr, M.K.V., 1992. Effects of light, temperature, irrigation and fertilizer on photosynthetic rate in tea (Camellia sinensis). Expl. Agric. (in press). Squire, G.R., 1985. Ten years of tea physiology. Tea, 6(2): 43-48. Squire, G.R. and Callander, B.A., 1981. Tea plantations. In: T.T. Kozlowski (Editor), Water Deficits and Plant Growth, New York Academic Press, New York, pp. 471-510. Stephens, W. and Carr, M.K.V., 1989. A water stress index for tea (Camellia sinensis). Expl. Agric. 25: 545-558. Stephens, W. and Carr, M.K.V., 1990. Seasonal and clonal differences in shoot extension rates and numbers in tea (Camellia sinensis). Expl. Agric., 26: 83-98. Stephens, W., Othieno, C.O. and Carr, M.K.V., 1992. Climate and weather variability at the Tea Research Foundation of Kenya. Agric. For. Meteorol., 61: 219-235. Tanton, T.W., 1982a. Environmental factors affecting the yield of tea (Camellia sinensis) I. Effects of air temperature. Expl. Agric., 18: 47-52. Tanton, T.W., 1982b. Environmental factors affecting the yield of tea (Camellia sinensis) II. Effects of soil temperature, day length and dry air. Expl. Agric., 18: 53-63.
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Elsevier Science Publishers B.V., Amsterdam
Yield variability at the Tea Research Foundation of Kenya C.O. Othieno a, William Stephens b and M.K.V. Carr b aTea Research Foundation of Kenya, P.O. Box 820, Kericho, Kenya bDepartment of Agricultural Water Management, Silsoe College, Silsoe, Bedford MK45 4DT, ( UK) (Received 22 June 1991; revision accepted 18 April 1992)
ABSTRACT Othieno, C.O., Stephens, W. and Carr, M.K.V., 1992. Yield variability at the Tea Research Foundation of Kenya. Agric. For. Meteorol., 61: 237-252. The results of an experiment to monitor the effects of weather variability on the yield of tea (Camellia sinensis) under constant management over a 16 year period are reported. The overall yield potential was limited to about 2 t ha ~ by the low air and soil temperatures associated with the high altitude (2180m) which restricted shoot extension rates. The within-year yield distribution was determined by sometimes large potential soil water deficits (up to 400 mm) during the dry season (which restricted yields of made tea by about 1.3 kg ha- ~mm ~) and by the incidence of damaging hail storms throughout the rest of the year (which caused mean losses of 10% of the total annual yield). The implications of this analysis for tea research at Tea Research Foundation of Kenya (TRFK) and elsewhere are discussed.
INTRODUCTION
Tea is grown at latitudes ranging from the equator to 33°S in Natal, South Africa and 49°N in Georgia, Russia (Huang, 1989), and from sea level (for example in Bangladesh) to as high as 2500 m in Kenya (Carr and Stephens, 1992). It is an unusual crop in that the young shoots which form the useful product, are harvested at intervals throughout the growing season with the frequency of harvesting normally determined by the mean air temperature and/or the rainfall distribution (when irrigation is not practised). Various attempts have been made to relate yields to current and antecedent weather conditions using a range of empirical factors (e.g. Sen et al., 1966) but these have rarely been interpreted in terms of the processes controlling growth (Squire and Callander, 1981), and therefore have had only local significance. Correspondence to: C.O. Othieno, Tea Research Foundation of Kenya, P.O. Box 820, Kericho, Kenya.
0168-1923/92/$05.00 © 1992 Elsevier Science Publishers B.V. All rights reserved.
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Statistical analyses of this type have also been complicated by the effects of the stage in the pruning cycle, and the times after the application of fertilizer. In a renewed attempt to quantify the effects of the principal weather variables on the yield of tea, an experiment was initiated at the Tea Research Foundation of Kenya (TRFK) in 1970 in which the effects of time of pruning and/or fertilizer applications on sequential yields were minimised (Carr and Othieno, 1971). The climate at the headquarters of T R F K in Kericho is dominated by the effects of the high altitude and its proximity to Lake Victoria and the equator. This results in uniform, but relatively low prevailing air and soil temperatures throughout the year, and high total rainfall, though there are annual droughts of variable duration and intensity. In addition, the whole of 15000 ha of commercial tea in the district is subject to frequent hailstorms, perhaps the highest incidence in the world (Schnell and Tan-Schnell, 1978), which can cause considerable losses in yield. For example, it has been estimated that over the 5 year period 1977-1982 hail damage resulted in a loss of 14000 tonnes of tea in the Kericho and neighbouring Nandi Hills districts (Mwakha, 1983). This was equivalent to about 140kgha -~ per annum. The majority of the commercial estate and smallholders' tea in the Kericho district is planted at altitudes from about 1700-2100 m and the T R F K is at the extreme end of this altitude range. In a companion paper, the climate and weather variability at T R F K have been quantified using historical weather data (Stephens et al., 1992). In this paper the results of the weather-yield correlation experiment over the 16 year period December 1970 to September 1986 are presented. Attempts are made to derive empirical relationships between yields and measured or derived weather variables, and to interpret the results in terms of physiological processes. METHODS
Climate Climate and weather variability at the Tea Research Foundation of Kenya (0°22'S 35°2 I'E; altitude 2178 m) have been fully described elsewhere, but are summarised here for clarity.
Temperature Mean maximum temperatures range from around 21°C in June and July to about 25°C in March: minimum temperatures are close to 8-9°C throughout the year. Mean daily air temperatures range from about 15.5 to 18°C. The effective thermal time for shoot extension, above a base temperature of 12.5°C (Tanton, 1982a), is therefore only 3-5.5 day °C. Assuming that 475 day °C are
YIELD VARIABILITY AT THE TRFK
239
needed for an axillary bud released from apical dominance to grow to 3 leaves and a bud (Mkwaila, 1987) the length of the shoot replacement cycle should vary from about 95 days in February to 130 days in May. Soil temperatures, at 0.3 m depth beneath short grass, are usually in the range 17-19°C.
Saturation deficit Midday values rarely exceed the critical value of 2.3 kPa (Tanton, 1982b). The total annual saturation deficit time is analogous to thermal time and is defined as the sum of daily saturation deficits above 2.3 kPa (Stephens et al., 1992).
Radiation The mean daily solar radiation total is in the range 1 7 - 2 2 M J m -2, with annual receipts of about 67 TJ h a - t.
Wind Wind runs are generally low, ranging from 120 to 160 km per day.
Rainfall The mean annual rainfall is about 2150mm of which about 90% falls between mid March and mid November.
Evaporation The daily mean rates of potential evapotranspiration range from 3 m m per day in April to 4.5 m m per day in mid March.
Soil water deficit (SWD) The maximum potential soil water deficit during the long dry season varies widely from between 75 m m to more than 400 mm. The actual total soil water stress time, calculated by summing the potential soil water deficit on a daily basis above a limiting deficit of 5 0 m m (SWSTs0), ranges from 0.5 to more than 25 day m.
Hail At the experimental site there are on average 25 hail storms every year. Soi/s The soils are very deep, well drained volcanic clays with a water holding capacity of about 170-220 m m m - i (Scott, 1962). At T R F K roots of mature tea have been observed to extend to depths of 6 m (Cooper, 1979) but the effective rooting depth is normally about 1.5-3 m (Carr, 1977).
Field experiment The experiment was initiated in 1970 in an area of 8-year old unshaded
240
C.O. OTHIENO ET AL.
Assam-type tea, originally propagated from seed which had been obtained from Ambangulu estate in Tanzania and planted at 1.5 m × 0.75 m spacing. The experiment was sited 200 m away from a standard agro-meteorological station. In order to isolate any effects of the time of pruning on yield distribution, one of the 156 bushes in each plot was pruned every week giving a staggered 3-year pruning cycle. Similarly, to avoid an uneven yield response to fertilizer applied infrequently, equal monthly applications were given totalling 222 kgN ha-I year -~ . Fertilizer was applied as NPKS 25:5:5:5 until 1978, and as N P K 20:10:10 c o m p o u n d thereafter. Shoots, mainly two leaves and a bud, were harvested at weekly intervals from each plot, except for the period from February 1972 to April 1973 when the harvest interval was increased to 10 days. The fresh weight of leaf tea was converted to the made tea equivalent using a constant value of 0.22.
Yield analysis Initially annual yields were examined to determine whether there was a year-to-year trend not accounted for by the meteorological variables. The year was then split into three periods, based on mean temperatures (Tmean)and rainfall; these were designed to correspond as closely as possible with the main seasons. First, (a) a warming period from September to November (Tme,n increasing from 15.3 to 16.0°C), which could be either wet or dry depending on whether or not there was a short dry season; then (b) a warm dry period from December to March (Tme~napprox. 16.5°C); and finally (c) a cooling wet period from April to August (Tm~, decreasing from 16.4 to 15.0°C). Year-toyear variations in seasonal yields were analysed by first identifying and removing any annual trend, and then relating the residual variation to measured climate variables, such as air and soil temperature, saturation deficit, solar radiation, wind and rainfall; and then to derived variables, such as evapotranspiration, soil water deficit, thermal time, soil water stress time and saturation deficit time, using stepwise multiple regression. The possible carry over effect of the yield obtained in the previous season was also included as a predictor variable. A preliminary examination of the data available suggested that hail was the most important determinant of within-season yield variation. Specific hailstorms classified as 'moderate' or 'severe' in the experimental record book were therefore examined to determine: (1) what proportion of yield was lost, (2) how long yields took to return to their pre-storm levels. These results were compared with yield losses estimated subjectively by experienced estate management staff, by considering yields in the 3 weeks following the hail storm with the yield in the week preceeding the storm. A frequency distribution of estimated monthly yield losses was calculated to assess whether most hail
241
YIELD VARIABILITY AT THE TRFK
2.5 due to hail coolin wet Apdl -g~gulrt wllrm dry December - March warrnln Sept ~lgber - November
," "" i
2.0
..,
i
¢= ¢,.. .--
ca 1.5
"'-i
"D
iiiiiiiii! i !iiii!i
E 1.0
,~
0
i!il
0.5
: ........ ii!iii ii I
I
I
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I
I
i
I
I
I
i
I
1~1~ 1~1'~ 1~ • 1~,1~ 1~1~' l~,g 11~ 1~1~ 1~
Harvest year Fig. 1. Annual yields at TRFK, Kericho showing the contribution of crop harvested in each of the three seasons (D warming period, [] warm dry period, [] cooling wet period), and ~:! the estimated annual yield loss owing to hail.
damage was caused by a few large storms, or whether each storm caused more or less equal damage. RESULTS
Year-to-year yield variation Annual yields of made tea averaged only 1.35tha -1 and showed wide year-to-year variation from less than 0 . 9 t h a -1 in 1982/1983 to just under 2.0tha -~ in 1972/1973 (Fig. 1). This was much greater than the annual variation in any of the meteorological variables except rainfall, soil water deficit and hail. There was no discernible increase in annual yields over time. Stepwise regression analysis on all variables showed that the maximum potential soil water deficit (SWDmax, mm) was the best predictor of yield explaining about 50% of the annual variation (Y~,n, kg ha -~) Yann
=
(1930
___
243) - - (2.01
___ 0 . S 5 ) S W D m a
x (n
=
15; R 2 =
0.45)
(1)
Figures following the coefficients are standard errors. For the range of SWDma x recorded this implies annual yield losses (estimated from the mean yield with zero SWD) of 0.15 to 0.80tha t with an average of 0.55tha -~. This relationship was not improved by including a
242
C.O. O T H I E N O E T AL.
"7
1000
e-
(o
800
600
E "O
400
tO
200
1O0
200
300
400
maximum potential soil water deficit (mm) F i g . 2 . Relationship between the dry season yields in the field experiment and the maximum potential soil water deficit at TRFK, Kericho. ( - fitted regression line; Y = 8 0 0 - 1 . 3 0 S W D m . x ; 9 5 % confidence limits for - - - m e a n ; • . • individual predicted values).
coded value for year (to represent a technology trend) or any other meteorological or derived variable. The yield loss owing to hail damage over the period 1970-1986 in the field surrounding the experiment, averaged about 0.22 t ha-~ year -l , corresponding to a mean annual yield reduction of about 16%. There was, though, a wide variation in the losses sustained, from less than 0.02 to almost 0.6 t ha ~ year- i (in 1970/1971), representing up to 45 % of the average annual yield. Between season yield variation
Annual yield totals can mask climate related fluctuations between seasons. The analysis was therefore extended to cover the warm dry, cooling wet and warming (wet or dry) periods defined on the basis of temperature and soil water deficits (see above). The relationships between warm dry season yields (Ydry) and all the meteorological and derived variables were analysed using stepwise multiple regression. There was a highly significant negative relationship (P < 0.001) between yield (kgha -I) and the maximum potential soil water deficit (mm) (Fig. 2). Incorporating a time trend in the regression equation did not improve the fit.
Ydry
=
(800 + 111) -- (1.30 ±
0.24)SWDma
x
(n = 16; R 2
=
0.68)
(2)
The total soil water stress time (SWST; day m), summed above a critical deficit (CD) of 50 mm, was also a good predictor explaining about 70% of the warm dry season yield variation. Ydry
----
(767 -I- 108) -- (1051 ___ 178)SWSTs0 (n
=
16; R 2 =
0.71)
(3)
YIELD VARIABILITY AT THE TRFK
243
The intercept and the slope of the relationship depend on the CD selected; when values of 0 and 100ram were substituted a similar proportion of the variation was estimated. The high level of year-to-year variation in yields precluded the accurate identification of a CD using the procedure developed by Stephens and Carr (1989). In the cooling wet period from April to August and the warming period from September to November there were no significant relationships between current yields and yields in the previous season, or with any of the actual or derived weather variables. The lack of any significant relationship is perhaps surprising, although throughout both these periods the irregular occurrence of damaging hail storms appeared to mask any weather related yield variation. Further analysis was therefore undertaken to investigate the within season variations in yield. Within season yield variation
On a week-to-week basis, yields fluctuated widely (Fig. 3) so part of the analysis involved searching for consistent patterns related to meteorological or derived variables. In particular, it is important to identify the critical SWD at which yields begin to decline to determine the sensitivity of the tea to short duration droughts. In eight of the 15 warm dry seasons analysed, weekly yields began to decline after a clearly defined break point in the latter half of December or early January. This change occurred at a critical deficit of about 85 mm (Fig. 4). Once the potential SWD exceeded 200 mm the rate of decline in weekly yields fell from 2 to 1 kg for every 10 mm increase in SWD. In years when the SWD did not exceed 100 mm no decline in yield owing to water stress was observed. When weather conditions such as drought, or cold weather, restrict shoot extension for a long time the removal of the limiting factors may result in a series of discrete yield peaks interspersed with deep troughs. This phenomenon, often known as the 'Fordham' cycle, is the result of rapid synchronised growth by the whole population of shoots (Fordham, 1970). The amplitude of the cycle depends on the duration and severity of the limiting period, and on the subsequent rates of shoot extension, which are largely controlled by the prevailing temperatures. Following the start of the rains in April there was often evidence of the beginning of a 'Fordham' cycle (e.g. in 1974, 1975, 1982, 1983, and 1984)but closer examination of the records suggested that the rapid decline in yields after the subsequent peak was the result of falling temperatures which increased the duration of the shoot replacement system to 130 days (Stephens et al., 1992). Hail damage was another confounding factor which limited the amplitude of the expected yield peak. Overall, only 20% of the recorded hail storms caused assessable yield losses
o
o
o
pote~lal soil water deficit (ram)
o
o
o o
rainfall (ram week 1) ~
° o
weekly yield of made tea (kg hd 1) o
o
o
o
potential soil water deficit (mm) o
~
rainfall (mm week 1) o
weekly yield of made tea (kg ha1 )
YIELD VARIABILITYAT THE TRFK
245
1
100 1 c) 1981-1986
| E~ 3, V
E
1°I ~,..,,. J ,,.
l,.,,,i,..,JL. JilL,i,,
(.1 "o
200 300
i
400
1981 I
1982
L
1983
I
1984
I
Fig. 3. Weekly variation in rainfall, soil water deficit and yield from the field experiment at T R F K , Kericho for the periods (a) 1971-1976; (b) 1976-1981; (c) 1981-1986.
t-40
~30
E .I
0
50
100
150
200
250
300
350
Potential soil water deficit (mm)
Fig. 4. Relationship between mean weekly yields and SWD in consecutive weeks during the dry season at T R F K , Kericho. (Bars represent standard error of the mean, n = 8).
246
C.O. OTH1ENO
ET AL.
100 A
v
80.2 80
E
9. 50 "0 0 e,l
~
40 15.1
20
~
3.2
1.0
0.5
100
150
>200
j
0
50
i
estimated yield loss (kg ha 1 ) Fig. 5. Frequency distribution of yield losses from individual storms on field adjacent to the experiment T R F K , Kericho: 1970-1986; [] non-damaging and II damaging storms.
and in three quarters of these the damage was estimated to be less than 5 0 k g h a -~ per event, which is equivalent to about 2.5% of the potential annual yield of around 2.0 t h a - i (Fig. 5). However, from April to November the damage caused by individual hail storms was considerable. The worst storms, recorded in October 1970 (shortly before the start of the experiment) and July 1982, caused yield losses of more than 0.3 t ha-f per event, equivalent to over 15% of the potential annual yield. Damage of this magnitude can be expected to occur about once in every 200 storms or once in every 8 years. In the field surrounding the experiment, the average yield losses resulting from storms classed in the experimental record book as 'moderate' and 'severe' were assessed as 4 0 k g h a -1 and 8 5 k g h a i, respectively. A more detailed analysis of records for individual storms showed that yields from the meteorological correlation plots were reduced after 'severe' hailstorms by approximately 80% for a period of 4 weeks before recovering rapidly over the next 4 weeks (Fig. 6). By contrast, hail storms classified as 'moderate' caused a 60% reduction in yield in the following week but yields then recovered steadily over the next 6 weeks. The yield lost as a result of each storm was estimated by accumulating the difference between the mean pre-storm yield and the mean yield for each subsequent week. On average 'moderate' storms caused a total estimated yield reduction of 50 kg ha -I , which is only slightly more than the field assessments. By contrast, the losses estimated for 'severe' storms were 130kgha -~ about 50% greater than the field estimates. This suggests that the method of field assessment may need revision when bushes take a long time to recover from the damage. No other short-term relationships between weather and yield were observed, presumably because of the overwhelming effects of erratic hail storms during the period April-November which disrupted any developing pattern.
YIELD VARIABILITY AT THE TRFK
E
247
120
0
.~ 1O0
~3
60
O3
,-
40
0
i
0
~ 20
sevo:
n
•~ "N,
0 w e e k s since hailstorm
Fig. 6. Relative yields p r e c e d i n g a n d f o l l o w i n g hail s t o r m s classified as m o d e r a t e + --t:3-- at T R F K , K e r i c h o .
a n d severe
DISCUSSION
A basis for comparison Squire (1985) suggested that the potential yield of tea (Ypo,; tha-~) is determined by: (1) the incoming photosynthetically active solar radiation (S; TJ ha-~ where 1TJ = 10 ~2J); (2) the proportion of radiation intercepted by the crop canopy (i; nondimensional); (3) the conversion efficiency of intercepted solar radiation to dry matter (e; tTJ-~); (4) the proportion of dry matter partitioned to harvestable shoots (the harvest index, HI; non-dimensional ratio), as follows rpot =
S.i.e.HI
(4)
At T R F K , the mean annual incident solar radiation is about 67 TJ h a - i of which slightly less than half is photosynthetically active. The canopy of well managed tea covers the ground within about three to four months after pruning (Othieno, 1983) and, thereafter, about 95% of the incoming radiation is intercepted by green leaves (Smith et al., 1992). Thus in the experimental area, where one bush was pruned every week over a 3 year pruning cycle, about 90% of the incoming radiation would be intercepted by the canopy throughout the year, so S x i = 30 TJ ha -I . Little work has been reported on conversion efficiencies or harvest indices in tea. However, in an experiment carried out at T R F K in 1977/1978, the total
248
C.O. OTHIENO ET AL,
dry matter production of clone 6/8, including roots, was 16.9tha ~year (Magambo and Cannell, 1981) which corresponds to a conversion efficiency of 0.6tTJ I photosynthetically active radiation (PAR). By contrast, many temperate C3 crops have considerably larger conversion efficiencies of about 1.4tTJ -I (Monteith, 1977) and in tropical perennial plantation crops the largest recorded values are in the range 1.0-1.7tTJ -~ (Corley, 1983). As photosynthesis is one of the most temperature-sensitive aspects of growth (Jones, 1983) the low conversion efficiency recorded at T R F K may be due in part, to the low ambient temperatures prevalent at this altitude (Stephens et al., 1992). The harvest index is also temperature dependent to a great extent since, in the absence of water stress, shoot extension is proportional to temperature above a base which is generally taken to be 12.5°C though there is evidence of clonal variations in base temperature from 7 to 15°C (Tanton, 1982a; Obaga et al., 1988; Stephens and Carr, 1990). During periods when shoot growth is restricted by low temperatures, dry matter production continues but a greater proportion is partitioned to the roots (Fordham, 1972). In the experiment on partitioning reported by Magambo and Cannell (1981), the annual yield of shoots (mainly two leaves and a bud) was 1.4 t ha ~, which is close to the mean yield from seedling tea in the experiment reported here. This corresponds to a harvest index of 0.08, which is only about one quarter of that recorded for other tropical perennial crops (Corley, 1983). The harvesting policy, (i.e. the guide lines on acceptable shoot size and stage of growth) and the method of harvesting are also important determinants of yield through their effect on the harvest index. For instance, increasing the proportion of shoots harvested with three leaves and a bud by extending the interval between harvests, increased yields from an irrigation experiment in Mulanje, Malawi by about 30% (Mkwaila and Grice, 1988). Similarly mechanical harvesting, which unselectively removes all shoots protruding above the plucking table, raised the annual yield of seedling tea at Chepgoiben Estate in Kericho (altitude approximately 2000m) from 2.5 t ha-~ when hand plucked to over 5.8 t ha-~ when machine harvested at 42 day intervals (Mwakha, 1988). The reasons for this remarkable increase with mechanical harvesting are not yet fully understood, but must be attributable in part to a larger harvest index rather than to any change in the proportion of solar radiation intercepted by leaves or converted to dry matter. The constant management imposed on the field experiment reported here allow the results to be considered in the absence of any management dependent changes in harvest index.
Year-to-year yield variation The mean annual yield of tea in the experiment was only 1.4 t ha ~but in
YIELD VARIABILITY AT THE TRFK
249
individual years yields varied around the mean by _+40%. Yield losses owing to drought were the major cause of this variation and averaged approximately 0.4 t ha -I . Hail damage reduced yields by, on average, a further 0.2 t ha I so that in the absence of hail and drought the potential yield for seedling tea at this site is around 2 t h a - ' . This value is consistent with estimates based on long term commercial yields from an estate in Kericho at a similar altitude. (Carr and Stephens, 1992). Intercepted solar radiation sets a limit on the total dry matter production whilst the conversion efficiency (e) and the harvest index (HI), which control the actual dry matter produced and the proportion allocated to the young shoots, are temperature dependent. At T R F K , the annual receipt of solar radiation, 6 years out of 10, is 6 5 - 7 0 T J h a ~, a variation around the mean of only _+4%. By contrast, because air temperatures are close to the base temperature for growth throughout much of the year, there are larger year-toyear fluctuations in the length of the potential shoot replacement cycle (Stephens et al., 1992). The responses however, are modified by dry weather during January to March when the critical soil water deficit may be exceeded in about 6 years in 10. The extent to which temperature dominates the yield potential in the Kericho district is well illustrated by the relationship between annual yield and altitude for 21 estates with similar management policies (Fig. 7). The fitted line represents the theoretical relationship between altitude and the duration of the shoot replacement cycle, assuming an adiabatic lapse rate of 6°C km-~; it suggests a decrease in yield of between 0.2 and 0.3 t for every 100m increase in altitude, with yields declining more rapidly above about 2200 m. Since yields on the high altitude (2200 m) estates have remained virtually constant at 2 t ha ' over the 15-year period since 1970, whilst yields on similar estates only 300-400m lower have doubled from 2.0 to 4.0 t ha -~ over the same time interval (Carr and Stephens, 1991), the rate of loss of yield per unit increase in altitude has been increasing with time, and is therefore now of greater commercial importance. The analysis of course ignores any effect on quality of the manufactured tea (Owuor et al., 1990). In summary, the overall ceiling to the annual yields of tea in high altitude (2000 m + ) areas of Kericho such as T R F K is determined by the ambient air (and soil) temperatures but within these constraints large soil water deficits (> 120mm) may reduce the yields by up to 20% whilst on average a further 10% will be lost because of hail damage. Between and within season yield variations
Yields in Kericho are more evenly distributed through the year than in the major tea growing areas of Tanzania and Malawi (Carr and Stephens, 1992). In these areas south of the equator the distribution between seasons is deter-
250
C.O. OTHIENO
•- 2 ,,C
~
"-~-. ~ -'~-~_._
s
.~-
-
,
\
\ \
E
ET AL.
\
\ \
\
2
\ \
\
m
\ C ¢,,
\ \ \ \\
2000
2500
altitude (m) Fig. 7. Relationship between 1984/1985 a n n u a l yields and altitude for 21 estates in the Kericho district. The fitted lines represents - the predicted relationship between yield and s h o o t replacem e n t cycle duration, and the 95% confidence limits for - - - mean; • •. individual predicted values.
mined primarily by the occurrence of large seasonal differences in temperature and soil water status. By contrast, the fluctuations within seasons are caused by the rapid amelioration of limiting weather conditions such as low soil and air temperatures, and/or large saturation deficits, and/or large SWD leading to the initiation of synchronised shoot growth which results in a cyclical series of yield peaks. In Kericho, these cycles can be expected to develop at the beginning of the rains in April, and as temperatures rise in September and October. In April, however, they rarely occur because temperatures at this time are falling, and because developing yield peaks are disrupted by hail. In September and October hail is even more prevalent but it is doubtful whether the necessary conditions exist for the development of a 'Fordham' cycle since the increase in temperatures is gradual rather than rapid leading to a steady rise in shoot growth rates.
YIELD VARIABILITYAT THE TRFK
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Implications The T R F K is sited close to the upper altitudinal limit for economic tea production. Effects of altitude on tea quality (Owuor et al., 1990) at present price differentials do not compensate for the relatively small yields. Low soil and air temperatures throughout most of the year restrict shoot growth rates, and can dominate the effects of other treatment variables (such as fertilizers) on yields recorded in experiments conducted on this site. Inconclusive results for a long term (30 year) shade experiment may perhaps be explained by the overriding influence of low temperatures on yield. By contrast increasing soil temperatures using plastic mulch in newly planted tea can increase shoot growth rates (Othieno and Ahn, 1980). It is essential that everyone is aware of these factors, otherwise scientists and the industry they serve can be misled. More experiments must be carried out in representative tea growing areas if results of general value are to be obtained. However, the immediate commercial implications of the results suggest that it would appear to be unwise to establish new tea areas at altitudes greatly in excess of 2200 m in Kenya if they are to be financially viable. Nevertheless, the main station does, in theory, allow clones to be selected which will grow at lower base temperatures, or which have a faster response in terms of shoot extension rates per °C. Indeed at least one clone with a low (7°C) base temperature may have already been identified (Obaga et al., 1988). Research organisations and growers should always exercise caution when attempting to extrapolate experimental results from one location to another. We await similar descriptions of the climate, weather and yield variability at the other major tea research stations so that the transfer of knowledge can be achieved with greater precision in the future. ACKNOWLEDGEMENTS
The design of the field experiment was based on an idea of the late J.C. Templer who initiated a similar experiment in Uganda at the same time. This analysis was undertaken as part of a research project sponsored by the UK Overseas Development Administration. REFERENCES Carr, M.K.V., 1977. Changes in the water status of tea clones during dry weather in Kenya. J. Agric. Sci., 89: 297-307. Carr, M.K.V. and Othieno, C.O., 1971. Weather and yields. In: Tea Research Institute of East Africa Annual Report 1971, Tea Research Institute of East Africa, Kericho, pp. 36-37. Carr, M.K.V. and Stephens, W., 1991. Climate, weather and the yield of tea. In: K.C. Willson and M.N. Clifford (Editors), Tea: Cultivation to consumption. Chapman and Hall, London, pp. 87135.
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