CLIMATE CHANGE AND AGRICULTURE PAPER
Sensitivity of barley varieties to weather in Finland
K. HAKALA*, L. JAUHIAINEN, S. J. HIMANEN, R. RÖTTER, T. SALO AND H. KAHILUOTO
MTT Agrifood Research Finland, Plant Production Research, FI-31600 Jokioinen and Lönnrotinkatu 5, FI-50100 Mikkeli,
Finland
(Received 1 April 2011; revised 7 June 2011; accepted 13 July 2011; first published online 11 August 2011)
SUMMARY
Global climate change is predicted to shift seasonal temperature and precipitation patterns. An increasing
frequency of extreme weather events such as heat waves and prolonged droughts is predicted, but there are high
levels of uncertainty about the nature of local changes. Crop adaptation will be important in reducing potential
damage to agriculture. Crop diversity may enhance resilience to climate variability and changes that are difficult to
predict. Therefore, there has to be sufficient diversity within the set of available cultivars in response to weather
parameters critical for yield formation. To determine the scale of such ‘weather response diversity’ within barley
(Hordeum vulgare L.), an important crop in northern conditions, the yield responses of awide range of modern and
historical varieties were analysed according to a well-defined set of critical agro-meteorological variables. The
Finnish long-term dataset of MTT Official Variety Trials was used together with historical weather records of the
Finnish Meteorological Institute. The foci of the analysis were firstly to describe the general response of barley to
different weather conditions and secondly to reveal the diversity among varieties in the sensitivity to each weather
variable. It was established that barley yields were frequently reduced by drought or excessive rain early in the
season, by high temperatures at around heading, and by accelerated temperature sum accumulation rates during
periods 2 weeks before heading and between heading and yellow ripeness. Low temperatures early in the season
increased yields, but frost during the first 4 weeks after sowing had no effect. After canopy establishment, higher
precipitation on average resulted in higher yields. In a cultivar-specific analysis, it was found that there were
differences in responses to all but three of the studied climatic variables: waterlogging and drought early in the
season and temperature sum accumulation rate before heading. The results suggest that low temperatures early in
the season, delayed sowing, rain 3–7 weeks after sowing, a temperature change 3–4 weeks after sowing, a high
temperature sum accumulation rate from heading to yellow ripeness and high temperatures (525 °C) at around
heading could mostly be addressed by exploiting the traits found in the range of varieties included in the present
study. However, new technology and novel genetic material are needed to enable crops to withstand periods of
excessive rain or drought early in the season and to enhance performance under increased temperature sum
accumulation rates prior to heading.
INTRODUCTION
Reducing vulnerability to climate change is a key to
sustaining future agriculture. Vulnerability is defined
as a function of exposure, sensitivity and adaptive
capacity of a system (IPCC 2007a). It has been sug-
gested that increasing diversity of cropping systems
and livelihoods may enhance resilience and provide
adaptation options to climate change (Howden et al.
2007). Crop cultivar diversity could also reduce
sensitivity to climate variability and thus be important
for adaptation, supposing a wide diversity exists in
response to critical agro-meteorological variables
within the available cultivar set.
Temperature sum, length of growing season
and critical temperatures during important phenologi-
cal stages, as well as timing and amount of precipi-
tation, are key variables that influence potential
and attainable agricultural crop yields (Kontturi
1979; Wheeler et al. 1996a,b; Porter & Semenov
* To whom all correspondence should be addressed. Email: kaija.
hakala@mtt.fi
Journal of Agricultural Science (2012), 150, 145–160. doi:10.1017/S0021859611000694
© Cambridge University Press 2011. The online version of this article is published within an Open Access environment subject to the
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2005; Peltonen-Sainio et al. 2009c; Rajala et al. 2009,
2011; Trnka et al. 2011). Short and intensive growing
season, early and late season frosts and low accumu-
lated temperature sum are the main reasons for low
yield levels in Finland. Also, precipitation early in the
season is generally too low to fully satisfy the water
requirements of cereals to reach full yield potential
(Peltonen-Sainio et al. 2009c; Trnka et al. 2011).
If conditions become more favourable later in the
growing season, increase in grain weight may com-
pensate for some of the potential yield losses, such as
reduction in grain number/m2, but the yield level may
still be lower than the higher initial yield potential
(Mitchell et al.1993;Wheeleret al.1996a,b; Peltonen-
Sainio et al. 2011; Rajala et al. 2011). In addition to
responses to drought, cereals, especially spring barley
(Hordeum vulgare L.), are sensitive to waterlogging
early in the season (Zhou et al. 2007; Peltonen-Sainio
et al. 2010). Despite the trend of generally dry early
season conditions, Finland, like many other European
countries, has periodically suffered from heavy rains
and flooding early in the season, with consequent
losses in yields (Olesen et al. 2011). Late in the season,
if harvest is delayed because of excessive rain, sensitive
cereals such aswheat (Triticumaestivum L.), barleyand
rye (Secale cereale L.) may suffer loss of quality through
pre-harvest sprouting.
Climate change is generally predicted to improve
growing conditions in the North (Carter et al. 1996;
Rötter & van de Geijn 1999; IPCC 2007a; Peltonen-
Sainio et al. 2009a; Olesen et al. 2011). For example,
the growing season is expected to become longer
and the accumulated temperature sum higher (IPCC
2007b; Kaukoranta & Hakala 2008; Peltonen-Sainio
et al. 2009a). However, rainfall is expected to increase
only little in the spring, offering no solution to early
season drought problems, but may increase in the
autumn and winter, rendering the harvesting con-
ditions worse than today (IPCC 2007b; Peltonen-
Sainio et al. 2009c). However, the uncertainty of
climate projections is high, and changes in variability
of weather, including more frequent extreme events, is
not usually taken into account in impact studies (Harris
et al. 2010; Soussana et al. 2010; Rötter et al., in press).
Increased temperatures during the growing season
(Trnka et al. 2011) and increased occurrence of ex-
tremeweather events such as heat waves (IPCC 2007b)
may lower the yields due to accelerated development
and also due to flower abortion (Mitchell et al. 1993;
Wheeler et al. 1996a,b; Porter & Semenov 2005).
The warm and dry growing season of 2010 provides
an example of future extreme conditions that may
become more frequent in Finland; it resulted in 18%
lower yield/ha for spring wheat and 39% lower yield/
ha for spring barley compared with the yield levels in
2009 (Matilda Agricultural Statistics 2011). In addition
to the climate-induced physical stresses, new stresses
may be caused by increased occurrence of pests and
pathogens (Hakala et al. 2011; Olesen et al. 2011),
emphasizing the need for stress tolerance more than
high productivity.
For a farmer, selection of crop cultivar is often a
gamble between yield stability and potentially high
attainable yields. Risk-taking farmers tend to prefer
cultivars that give them a bumper harvest in good years
but may lead to considerable losses in poor years,
while risk-averse farmers go for cultivars that show
reduced yield variations (Olesen et al. 2011). What
then would ensure farms were well-prepared for in-
creasing weather uncertainty and climate change, e.g.
extreme weather events, changed temperatures and
precipitation patterns in the future? Crop and cultivar
selection are obvious factors. Historically, crop var-
ieties have been bred to be stable under certain
‘average’ conditions, with the variety tests lasting
usually for 10–15 years before a variety can be
considered stable enough for commercial release for
a particular climatic zone (Kangas et al. 2009). While
plant breeding has succeeded in continuously produ-
cing new, more adaptive and higher yielding crop
cultivars (Peltonen-Sainio et al. 2009b), varieties
producing extremely high yields in exceptionally
good conditions may be lost in the process, as the
variety tests aim to find varieties that perform well on
average, not just in certain years favouring an in-
dividual variety (Öfversten et al. 2002). Expectations
for climate change derived improvement of crop
production potential in Finland (Carter et al. 1996;
Peltonen-Sainio et al. 2009a) emphasize the need for
higher-yielding varieties with a longer growing time,
especially as the climatic conditions in the future may
change in favour of them. In the crossfire of alternative,
both positive and negative, factors that affect crop
production, it would be very important to have a
diverse set of crop varieties to select from. This would
offer the farmer greater flexibility and enable selection
of either a more or less risky adaptation strategy in
terms of increasing weather instability.
Many previous studies have attempted to predict
crop responses to weather based on temperature sum
and seasonal precipitation (e.g. Carter et al. 1996;
Peltonen-Sainio et al. 2009a). However, the timing
146 K. Hakala et al.
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of the weather variables in relation to sensitive crop
phenological stages might be much more meaningful
in predicting actual yields (Peltonen-Sainio et al. 2010;
Trnka et al. 2011). Detailed observations of phenolo-
gical and weather variables are needed to explain
yield levels and to identify the most vulnerable
development stages for a specific crop species (Porter
& Semenov 2005). Long-term field trials, including a
large set of differentially responsive varieties, offer one
approach to identifying the most meaningful weather
events regarding yield level and the constraints of their
timing with crop phenology.
The aim of the present study was to establish
the degree of response diversity to Northern climatic
variables that exists among the present selection of
barley varieties cultivated in Finland. Barley was
chosen as the example crop as it is the most widely
grown cereal in Finland and has high variety diversity.
Those weather variables most critical for yield per-
formances were first selected according to published
literature and knowledge of farmers and researchers.
Preliminary tests of the sensitivity of barley in general
to these variables were then conducted with a large
collection of varieties extending back 40 years. The
weather variables found to markedly affect yields
were further tested with a selection of modern barley
cultivars. Diversity in the responses of this set of
cultivars to the selected weather parameters was then
sought in order to assess the current capacity of barley
to adapt to different present and future climatic con-
ditions in the North. The aim was to contribute to
assessments of resilience of Northern crop production
towards climatic variability and change.
MATERIALS AND METHODS
Variety trials
Variety trial data from MTT research stations were
used whenever weather records were available from
a nearby weather observatory or station (Table 1).
During the first phase, all varieties from the last 40
years were included in the tests to establish general
responses of barley as a species to selected weather
variables under Finnish climatic conditions. After a
univariate analysis, combinations of weather variables
were further tested in a multivariate analysis with
variables selected on the basis of the results of the
univariate analysis. This first phase test data included
13242 yield records. In the second phase, a set of
modern cultivars of both Finnish and foreign origin,
from the late 1980s to the present, and older cultivars
that are still cultivated during the 2000s were tested,
amounting to 2384 records. These cultivars are listed
in Table 2. The northernmost test site was Ruukki
(64°40′N, 25°06′E).
Most of the variety trial experiments were part of
the MTT Official Variety Trials and all followed
procedures specified for that purpose (Kangas et al.
2009; Peltonen-Sainio et al. 2011). In addition to MTT
Agrifood Research Finland, which has numerous
regional research units in Finland, some of the ex-
periments were organized by plant breeding compa-
nies and private agricultural research stations.
All experiments were arranged as randomized com-
plete block designs or incomplete block designs.
Numbers of replicates varied between 3 and 4. Each
year the test set of varieties changed, but long-term
control varietieswere used. Plotswere 7−10× 1·25m,
depending on location and year. Fertilizer use de-
pended on cropping history, soil type and fertility and
was comparable with standard practices in Finland.
Yield was combine-harvested and weighed (t/ha)
after removing straw, weed seeds and other particles.
Grain moisture content was determined by weighing
grain samples before and after oven drying or more
recently by using a Dickey John apparatus. Yield was
adjusted to 150 g moisture/kg.
Selection of climatic variables and their thresholds
Based on the literature (e.g. Trnka et al. 2011) and local
observations regarding barley performance under
Table 1. Selected experimental sites, their latitudes,
longitudes, average sowing dates and number
of trials
Location
Latitude
North
Longitude
East
Sowing
date Trials
Piikkiö 60°23′ 22°33′ 13 May 12
Pernaja 60°26′ 26°02′ 7 May 5
Mietoinen 60°38′ 21°55′ 15 May 67
Anjalankoski 60°41′ 26°48′ 18 May 37
Jokioinen 60°49′ 23°30′ 15 May 28
Kokemäki 61°17′ 22°15′ 16 May 20
Pälkäne 61°20′ 24°13′ 14 May 44
Mikkeli 61°40′ 27°10′ 15 May 30
Tohmajärvi 62°14′ 30°21′ 20 May 38
Laukaa 62°19′ 26°19′ 21 May 53
Ylistaro 62°57′ 22°30′ 13 May 118
Maaninka 63°09′ 27°19′ 21 May 35
Sotkamo 64°01′ 28°22′ 22 May 18
Ruukki 64°40′ 25°06′ 22 May 59
Barley variety sensitivity to weather in Finland 147
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Table 2. Modern barley cultivars tested and selected agronomic information
Cultivar Owner
Year of
release First test Last test n
Tests
in
2000s
Heading
(DAS)
Yellow
maturation
(DAS)
Average
yield
(kg/ha)
Diff.
average
heading
Diff.
average
maturity
Kustaa SW 1979 1976 2001 417 25 52·7 94·3 4171 −1 1
Pohto Bor 1987 1984 2001 345 28 51·1 89·9 4758 −2 −3
Arve Gr 1989 1987 2003 301 56 48·7 85·8 4733 −5 −7
Artturi Bor 1992 1989 2008 141 14 49·3 84·4 4641 −4 −9
Botnia Bor 1996 1989 2003 132 1 51·0 90·7 4959 −2 −2
Saana Bor 1996 1992 2008 141 75 54·3 92·7 4612 1 0
Rolfi Bor 1997 1990 2009 189 86 48·7 85·1 4805 −5 −8
Erkki Bor 1998 1992 2008 107 25 50·8 89·7 5027 −3 −3
Scarlett SJB 1998 1995 2009 136 106 53·9 94·0 4851 1 1
Jyvä Bor 2000 1997 2008 76 32 48·1 89·8 4871 −5 −3
Kunnari Bor 2001 1997 2009 155 111 51·0 91·8 5240 −2 −1
Gaute Gr 2003 2001 2005 42 42 51·8 88·6 5182 −2 −4
Annabell NS 2003 2001 2009 80 80 55·6 97·2 5208 2 4
Maaren SW 2004 2002 2008 40 40 55·1 96·2 5073 2 3
Edel Gr 2004 2001 2009 43 43 52·8 93·0 5319 −1 0
Voitto Bor 2005 2002 2009 48 48 49·1 86·3 5052 −4 −7
Vilde Gr 2005 2003 2009 38 38 51·3 90·0 5539 −2 −3
Pilvi SW 2005 2003 2009 40 40 49·1 86·1 5000 −4 −7
Braemar SS 2005 2002 2007 37 37 53·9 95·8 4807 1 3
Tocada KWS 2006 2004 2009 37 37 54·8 97·7 5479 1 5
Olavi Bor 2006 2003 2009 45 45 51·2 90·3 5165 −2 −3
Tiril Gr 2006 2004 2009 37 37 49·1 87·1 5340 −4 −6
SW, Svalöf Weibull AB, Sweden; Bor, Boreal Plant Breeding Ltd, Finland; Gr, Graminor AS, Norway; SJB, Saatzucht Josef Breun GdbR, Germany; NS, Nordsaat
Saatzuchtgesellschaft GmbH, Germany; SS, Syngenta Seeds Ltd, England; KWS, KWS Lochow GmbH, Germany.
DAS, days after sowing. Diff. average heading andDiff. averagematurity, difference of heading or yellowmaturation (DAS) compared to average of all cultivars (negative number
means earlier than average). Average yields for the cultivars are national averages up to 64°40′N.
148
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s of use, available at
different temperature and precipitation patterns, agro-
meteorological variables that were expected to have a
marked influence on growth and yield formation of
barley were pre-selected (see Table 3). The Zadoks
scale (Zadoks et al. 1974) was applied for characteriz-
ing crop phenology.
Imputation of missing values
The set of varieties varied from trial to trial. Sowing day
was the same for all varieties in a trial, but the dates of
heading (growth stage (GS) 55) and yellow ripeness
(GS92) depended on variety. To calculate mutually
comparable heading and yellow ripeness days for all
trials, the following analysis of variance model was
fitted:
datekl = μ+ trialk + varietyl + εkl (1)
where datekl is observed heading or yellow ripeness
date, μ is intercept, varietyl is the effect of l
th variety,
trialk is the effect of k
th trial and εkl is the residual.
Dates of sowing, heading and yellow ripeness were
not available for all trials. The number of missing dates
was 8 for sowing, 267 for heading and 29 for yellow
ripeness for the 514 trials. Latitude plays a key role in
timing in Finland. Missing dates were estimated using
known days and latitudes. In addition, trials for oats
(Avena sativa L.) and spring wheat were used to make
Table 3. Pre-selection of agro-meteorological variables expected to have a marked influence on growth and
yield formation, and the expected yield response in barley. In parentheses, the name of the tested variable in
Tables 4 and 5 and in Figs 1 and 2
Variable Expected yield response
1. Rain for 1 month before sowing. May lead to delayed sowing if soil is too wet to carry tractors,
and consequently to lower yields if conditions become too hot
and dry for optimal yield formation (Peltonen-Sainio et al.
2009c).
2. Delayed sowing (sowing date). See variable 1.
3. Early season drought and waterlogging (rain 0–3 weeks
after sowing).
Early season drought may delay germination and early
development, water logging may significantly reduce yields
(Zhou et al. 2007; Peltonen-Sainio et al. 2010).
4. Drought at yield potential determination (rain
3–7 weeks after sowing).
Drought at yield potential formation may reduce grain number
and yield (Rajala et al. 2009, 2011).
5. Frost damage during early growth (lowest temperature
during 0–4 weeks after sowing).
Early season frost may cause significantly reduced yield of e.g.
turnip rape, but has not been tested previously with barley,
although general opinion is that Finnish cereals are not
susceptible to mild early season frosts (Peltonen-Sainio et al.
2009a,c).
6. Temperatures at tillering phase (temperatures during
3rd and 4th weeks after sowing).
Traditionally it is held that a slow start to growth (low
temperatures during vegetative phases of cereals) may
increase yields, but this has not been tested previously.
7. High temperature stress (number of days with
maximum temperature of 25 °C or higher 1 week
before to 2 weeks after heading).
Very high temperatures during early generative phases have
been shown to reduce grain number and yield (Wardlaw et al.
1989a; Mitchell et al. 1993; Wheeler et al. 1996a).
8. Very high temperature stress (number of days with
maximum temperature of 28 °C or higher 1 week
before to 2 weeks after heading).
See variable 7.
9. Rate of temperature sum (Tsum) accumulation before
heading (Tsum accumulation rate from 14 days before
heading to heading).
Increased rate of development at yield potential formation has
been shown to reduce grain number and yield (Mitchell et al.
1993; Wheeler et al. 1996a; Hakala 1998).
10. Rate of Tsum accumulation at grain filling (Tsum
accumulation rate from heading to yellow ripeness).
Increased temperature has been shown to shorten the duration
of grain filling (Evans & Wardlaw 1976; Kontturi 1979;
Wardlaw et al. 1989a; Wheeler et al. 1996b; Hakala 1998)
and may thus reduce grain yield.
11. Mean daily temperature sum accumulation rate at
grain filling (Tsum accumulation rate (per day)
from heading to yellow ripeness).
See variable 10.
Barley variety sensitivity to weather in Finland 149
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latitude-based estimates more accurate. The following
model was used to estimate missing dates:
dateijk = μ+ speciesi + yearj + β1 latitude
+ yearj × β1 latitude+ εijk (2)
where dateijk is the known date for kth trials (in analysis
of heading and yellow ripeness date is estimates of
trialk from the Eqn 1), μ is the intercept, speciesi is the
effect of ith species (i=barley, oats, spring wheat), yearj
is the effect of jth year ( j=1976, . . ., 2009), β1 is the
regression slope from latitudes presented in Table 1.
Yearj×β1latitude allows for regression slope to vary
from year to year (i.e. in some years sowing occurs
simultaneously in the whole study area, in some
years differences can be more than 3 weeks). Finally,
εijk is the residual. Residuals showed that the difference
between true and estimated date was typically less
than 3 days.
General responses of barley to weather conditions
A univariate approach was used to find general
responses to weather conditions, i.e. regression
analysis was used to model response for each
weather parameter separately. If the response was
not linear (e.g. early season drought and water-
logging), the weather parameter was classified into
2–3 groups.
A multivariate approach was taken after univariate
analyses using a multiple regression model. The initial
model included all the climatic variables from the
univariate analysis. However, moderately and highly
correlated variables (r>0·50) were not accepted be-
cause of the potential multi-collinearity problem. A
correlation matrix of climatic variables is presented
in Table 4. After this, backward selection was used
to reduce the model, i.e. the least significant variable
was dropped, one at a time, until only statistically
significant or almost significant effects (P<0·10) were
left.
Table 4. Correlation among the tested climatic variables*. The upper value is the Pearson correlation
coefficient, the lower value is significance for the coefficient
var1 var2 var3 var4 var5 var6 var7 var8 var9 var10 var11
var1 0·33 0·01 −0·10 0·23 0·25 0·09 0·09 0·15 0·02 0·04
<0·001 0·832 0·022 <0·001 <0·001 0·040 0·037 <0·001 0·673 0·356
var2 0·19 0·06 0·36 0·32 −0·08 −0·08 −0·04 −0·02 −0·38
<0·001 0·144 <0·001 <0·001 0·067 0·048 0·353 0·589 <0·001
var3 −0·05 0·09 −0·13 0·21 0·15 0·19 −0·02 0·02
0·287 0·043 <0·01 <0·001 <0·001 <0·001 0·623 0·684
var4 −0·02 −0·05 −0·14 −0·19 −0·24 −0·02 −0·05
0·662 0·213 <0·001 <0·001 <0·001 0·704 0·218
var5 0·23 −0·08 −0·03 −0·05 0·16 −0·02
<0·001 0·065 0·490 0·275 <0·001 0·672
var6 −0·11 −0·05 −0·03 0·17 0·04
0·010 0·200 0·478 <0·001 0·331
var7 0·83 0·58 −0·07 0·59
<0·001 <0·001 0·120 <0·001
var8 0·54 −0·06 0·57
<0·001 0·184 <0·001
var9 −0·10 0·44
0·017 <0·001
var10 0·15
<0·001
var11
* var1, rain for 1month before sowing; var2, sowing date; var3, rain 0–3weeks after sowing; var4, rain 3–7weeks after sowing;
var5, lowest temperature during 0–4 weeks after sowing (whole period); var6, temperatures during 3rd and 4th weeks after
sowing; var7, number of days with maximum temperature of 25 °C or higher 1 week before to 2 weeks after heading; var8,
number of days with maximum temperature of 28 °C or higher 1 week before to 2 weeks after heading; var9, Tsum
accumulation rate from 14 days before heading to heading; var10, Tsum accumulation rate from heading to yellow ripeness;
var11, Tsum accumulation rate (per day) from heading to yellow ripeness.
150 K. Hakala et al.
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Responses of selected modern barley varieties to
weather conditions
Modern and also older, but currently cultivated,
varieties were selected when interactions between
varieties andweather parameters were tested (Table 2).
Weather parameters were classified into three cat-
egories of equal numbers of trials, e.g. rain during 1
month before sowing was classified according to
monthly rainfall at: up to 23, 23–41 and 41–113mm
of rain/month. Interaction was analysed using the
following mixed model:
yijk = μ+ varietyi + categoryj + variety× categoryij
+ trial category( )kj+εijk
where yijk is the observed yield, μ is the intercept,
varietyi is the average yield level of ith variety,
categoryj is the average yield level at jth level of
categorized environment ( j=1, 2, 3) and variety×
categoryij is the variety-by-environment interaction.
All the above effects are fixed in the model. Trial
(category)kj is the random effect of kth trial within jth
category and εijk is normally distributed residual error.
When comparing modern cultivars, the effects of
various weather variables on crop yields are presented
as percentage of the average national yield calculated
for the variety. This approach was taken as the
differences in the average yields of the studied cultivars
were large, ranging from 4000 to 5500 kg/ha (Table 2),
and thus losses or gains in kilograms would not be a
meaningful measure of cultivar sensitivity. As the
statistical testing was performed only for variety trials
where there was also a weather observatory close by,
and the results were compared with the total cultivar
average, the columns in the figures do not always
reach 100%, even when all possible conditions are
included in the results.
All statistical analyses were performed using
the MIXED and REG procedures in SAS software
(version 9.1).
RESULTS
General yield responses of barley to rainfall
and temperature
In general, yield levels of barley varieties differed
significantly (P<0·001) from each other in all tested
weather conditions. High rainfall before sowing and
delayed sowing reduced barley yields (Table 5).
During the first 3 weeks after sowing, the general
effect of rainfall was negative. However, when
the rainfall was divided into three classes: low
(0–18·2 mm), moderate (18·3–33·6 mm) and high
(33·7–122·4 mm), moderate rainfall resulted in high
yields, while both high rainfall and low rainfall
reduced yields considerably. At later stages, when
the crop had already established (3–7 weeks after
sowing), increase in rainfall increased yield (Table 5).
Early season frost had no effect on yield. However,
cool start of season increased yields: the yield was
significantly reduced by increases in temperatures
during the 3rd and 4th weeks after sowing (Table 5a).
Very high temperatures (525 °C) during a period of
1 week before and 2 weeks after heading reduced
yields significantly. The effect was increased with in-
creasing temperature. High temperature sum accumu-
lation rate during a period of 2 weeks before heading
decreased the yield slightly, while at a later phase,
during the period from heading to yellow ripeness,
increase in temperatures (higher temperature sum
for the period) increased the yields, especially when
calculated as a rate of temperature sum accumulation
(°C d/day) (Table 5a).
A multivariate analysis was performed to establish
how the different weather variables tested individually
would affect yields when they coincide during a grow-
ing season. The results are shown in Table 5b. Of the
variables affecting the yields significantly when tested
alone, sowing date, rain during the first 3 weeks after
sowing (when grouped into three categories), rain 3–7
weeks after sowing, temperatures during 3rd and 4th
weeks after sowing, number of days with maximum
temperature of 25 °C or higher and temperature
accumulation rate from heading to yellow ripeness (°
C d/day) affected the yields statistically significantly
(Table 5b). It was found that when tested together,
drought during the early phases of development caused
a bigger effect than when tested alone, while heavy
rain during the early phases of development caused a
lower effect than when tested alone. High (525 °C)
and very high (528 °C) temperatures around heading
caused more yield reduction and with higher statistical
significance when tested together with other variables
than when tested alone. Increased temperature sum
accumulation rate, again, had a bigger effect on yield
when tested together with other weather variables.
Effects of delayed sowing, as well as rain and
temperatures at early tillering, affected the yields only
slightly differently when tested together with other
variables than when tested alone. When experimental
site was included in the multivariate model (Table 5c),
Barley variety sensitivity to weather in Finland 151
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most of the tested variables remained significant and
the effects on yield were only slightly altered.
Diversity of modern barley varieties in response to
rainfall at different growth stages
In accordance with the general variety trial results
described above, high rainfall before sowing resulted
in yield reduction also when tested separately with the
selectedmodern cultivars (Table 2, Fig. 1a). The lowest
rainfall category resulted in consistently higher yields
than the highest category. In general, the cultivars
tended to react differently to rain before sowing
(P=0·103). For example, cultivars Saana, Kustaa and
Maaren had equal yields with low or moderate rain
before sowing, and yield decreased only when
Table 5. Effects of the tested climatic variables on yield of all barley varieties tested during the last 40 years, at
sites where weather information was also available (total of 13242 yield records). (a) Univariate analysis,
(b) multivariate analysis and (c) multivariate analysis where experimental site is included in the model.
beta_hat=estimated yield effect (kg/ha) per parameter unit; S.E., standard error; P, statistical significance of the
response of barley to the climatic variable
beta_hat S.E. P Climatic variable
(a) Univariate analysis
−6·29 3·04 0·039 Rain for 1 month before sowing
−35·12 7·66 <0·001 Sowing date
−8·38 2·60 <0·01 Rain 0–3 weeks after sowing
−257/−551* <0·001 Rain 0–3 weeks after sowing: 3 groups
5·19 1·99 <0·01 Rain 3–7 weeks after sowing
−7·22 23·91 0·763 Lowest temperature during 0–4 weeks after sowing
(whole period)
−53·74 21·16 0·011 Temperatures during 3rd and 4th weeks after sowing
−41·20 13·80 <0·01 Number of days with maximum temperature of 25 °C or
higher 1 week before to 2 weeks after heading
−76·85 32·20 0·017 Number of days with maximum temperature of 28 °C or
higher 1 week before to 2 weeks after heading
−4·51 2·10 0·033 Tsum accumulation rate from 14 days before heading to
heading
2·50 0·96 <0·01 Tsum accumulation rate from heading to yellow ripeness
59·63 29·92 0·047 Tsum accumulation rate (per day) from heading to yellow
ripeness
(b) Multivariate analysis
−20·84 9·51 0·029 Sowing date
−357/−492* <0·001 Rain 0–3 weeks after sowing: 3 groups
3·93 1·94 0·043 Rain 3–7 weeks after sowing
−48·52 23·74 0·041 Temperatures during 3rd and 4th weeks after sowing
−82·27 17·78 <0·001 Number of days with maximum temperature of 25 °C or
higher 1 week before to 2 weeks after heading
138·97 41·60 <0·001 Tsum accumulation rate (per day) from heading to yellow
ripeness
(c) Multivariate analysis with experimental site included
−24·48 10·17 0·022 Sowing date
−263/−403* <0·01 Rain 0–3 weeks after sowing: 3 groups
3·45 1·94 0·077 Rain 3–7 weeks after sowing
−53·84 23·51 0·022 Temperatures during 3rd and 4th weeks after sowing
−79·28 17·89 <0·001 Number of days with maximum temperature of 25 °C or
higher 1 week before to 2 weeks after heading
114·52 44·15 <0·01 Tsum accumulation rate (per day) from heading to yellow
ripeness
* The weather parameter was classified into three classes: low (0–18·2 mm), moderate (18·3–33·6 mm) and high
(33·7–122·4 mm), as with the selected modern cultivars. The figures denote difference of low/high compared to moderate.
152 K. Hakala et al.
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precipitation before sowing was very high. In contrast,
the cultivar Braemar had the highest yield at moderate
and high rainfall levels before sowing and cultivar
Tocada had the highest yield at the highest rainfall
before sowing.
The effect of high pre-sowing rainfall on yield might
be explained by the weather-forced delay of sowing
in the spring due to soil water saturation (Trnka et al.
2011). Therefore, delayed sowing should also de-
crease yields. This seemed to hold true in most cases
(Fig. 1b). However, the cultivars significantly differed
in their responses (P=0·042). Cultivars Jyvä, Olavi,
Maaren and Braemar showed little response to sowing
date at the tested sowing windows (end of April–12
May; 13–19 May and end of May–beginning of June).
Cultivar Tocada, again, produced its highest yield at
the latest sowing.
All the tested modern barley cultivars responded
similarly (P=0·539) to rainfall during the first 3 weeks
after sowing (results not shown). When rain increased
from the lowest class 0–18mm to 18–34mm, the yield
increased. The only exception here was cultivar
(a)
(b)
(c)
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Fig. 1. Responses of the chosen modern barley cultivars to (a) rain for 1 month before sowing (mm/month), (b) delay of
sowing (sowing date) and (c) rain during 3–7 weeks after sowing (rain sum mm/period). P, statistical significance for the
interaction between the cultivar and the climatic parameter. White, grey and black columns denote, respectively, categories
low, moderate and high (extreme), or in: (a) rain sum: 1·1–23·1, 23·2–40·7 and 40·8–112·9mm; (b) dates: 25 April–12
May; 13–19 May and 20 May–6 June; (c) rain sum: 2·3–39·4, 39·5–63·3 and 63·4–176·7mm. P values for the interaction
between the cultivar and the categories and the average standard error of difference (S.E.D.) of the categories within cultivars
are 0·103 and 4·8%, 0·042 and 4·5% and <0·01 and 4·6% in (a), (b) and (c), respectively.
Barley variety sensitivity to weather in Finland 153
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Maaren, the yield of which seemed to decrease
consistently with increasing precipitation. When rain-
fall increased from 34 up to 122mm during the
3 weeks from sowing, the yield decreased for all
cultivars tested. At a later phase, during 3–7 weeks
after sowing, yield increased when precipitation
increased from low (2·3–39·4 mm) to moderate
(39·5–63·3 mm) in all but one (Maaren) cultivar tested
(Fig. 1c). When rainfall increased further, to a rain
sum of 63·4–176·7 mm, the yield response was rather
small, but more variability within the tested cultivars
appeared. The yields either increased further, de-
creased or there was no change. Even though cultivars
differed in their responses to rainfall at this stage
(P<0·01), all produced the lowest yield at the lowest
rainfall level.
Diversity of modern barley cultivars in response to
temperatures at different growth stages
All tested modern barley cultivars yielded best
when the average temperatures during early growth
(3–4 weeks after sowing) were low (Fig. 2a). Even
though the lowest temperature category resulted in
higher yields in all cultivars, the cultivars differed in
their reactions to early season temperatures (P<0·001).
Cultivars Tocada, Braemar, Scarlett and Maaren
were characterized by a pattern of reduced yield at
moderately increased early season temperatures, but
yield increased when the temperatures rose to an even
higher level (Fig. 2a). Yields of other cultivars were
either stable or decreased under higher temperatures
compared with moderate temperatures. During the
period of 2 weeks before heading, increased average
temperatures decreased yield (Fig. 2b). However,
the decrease was significant only between the first
two threshold temperature sums, 63–135 °C d and
139–159 °C d. When the temperatures increased
further during this phase, the yields seemed to increase
consistently, but the increase was not statistically
significant. All barley cultivars tested behaved simi-
larly (P=0·725).
When maximum day temperatures increased to
very high (525 °C or even 528 °C) levels during
the period of 1 week before and 2 weeks after heading
(the period in which anthesis takes place), the effect
depended on the duration of exposure to the high
temperatures (Fig. 2c). No change in yield was
detected when the exposure to temperatures reaching
or exceeding 25 °C was short, but when the exposure
lasted for more than 6 days, there were yield penalties
in most of the barley cultivars studied. The cultivars
differed statistically significantly from each other in
their responses to high temperatures (P=0·052 for
525 °C and P=0·023 for528 °C) and in the extent of
the yield penalty. Under conditions with maximum
daily temperatures of 25 °C for more than 6 days, there
was no yield penalty for two cultivars: the old cultivar
Kustaa and the Finnish cultivar Botnia (results not
shown). Under even higher temperatures (daily maxi-
mum temperatures of 28 °C or higher for more than
6 days), the yield penalties were in some cases very
serious, with yields decreasing to only 70–80% of
the average yield level (Fig. 2c). The German bred
cultivars Annabell and Scarlett and the Scandinavian
Maaren and Vilde suffered the biggest losses, while
there were small yield losses in cultivar Kustaa.
Temperature sum accumulation rate from heading
to yellow ripeness affected the yields of the tested
barley cultivars significantly. The lowest accumulation
rates resulted in most cases in lower yields than the
highest accumulation rates, but the highest yield levels
were reached at moderate temperature sum accumu-
lation rates (Fig. 2d ). Although the general responses
were relatively consistent, the cultivars differed in their
responses (P<0·001). In cultivars Jyvä, Annabell and
Braemar, the yields were the same at both moderate
and high accumulation rates. The highest yield
penalties following low accumulation rates were in
cultivars Olavi and Annabell (Fig. 2d ). The cultivar
Jyvä seemed to yield equally well at all temperature
conditions compared in the present work.
DISCUSSION
The spectrum of response among diverse barley
varieties to northern weather conditions was estab-
lished. The main findings are that under Finnish
conditions there is a relatively high diversity of
response among varieties that should be fully exploited
for developing local adaptation strategies. There was,
however, no response diversity to drought and excess
rain early in the season or to high temperature sum
accumulation rate before heading which severely
reduced yields of all cultivars.
Yield responses to rainfall
The effect of delayed sowing seemed to be more
significant than the effect of high rainfall per se, yet
with high response diversity among cultivars. Some of
the cultivars, irrespective of their origin, responded
154 K. Hakala et al.
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(a) 
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Fig. 2. Responses of the chosen modern barley cultivars to (a) temperatures during 3rd and 4th weeks after sowing (average
temperature, °C for the period), (b) temperature sum accumulation rates during the period of 2 weeks before heading
(Tsum, °C d for the period), (c) very high temperatures (maximum day temperatures 28 °C or higher) during the period of 7
days before and 14 days after heading and (d ) temperature sum accumulation rate during the period of grain filling (heading
to yellow ripeness) (°C d/day during the period). P, statistical significance for the interaction between the cultivar and the
climatic parameter. White, grey and black columns denote, respectively, categories low, moderate and high (extreme),
or in: (a) average temperatures: 6·3–11·6, 11·6–13·7 and 13·8–19·1 °C; (b) temperature sum: 63–135, 136–159 and
160–237 °C d; (c) duration: 0–2, 3–5 and more than 6 days; (d ) temperature sum accumulation rate: 5·2–10·2, 10·3–11·5
and 11·6–16·6 °C d/day. P values for the interaction between the cultivar and the categories and the average S.E.D. of the
categories within cultivars are <0·001 and 4·5%, 0·725 and 4·8%, 0·023 and 3·8% and <0·001 and 4·7% in (a), (b), (c) and
(d ), respectively.
Barley variety sensitivity to weather in Finland 155
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little if at all to a delay in sowing. Tocada differed
clearly from the other cultivars, giving the highest yield
at the highest rainfall before sowing and also at the
latest sowing. Tocada was the latest maturing and the
longest-growing cultivar in the present study. It is
possible that it can benefit not only from a long
growing season but also from a warm early season,
requiring a high temperature sum for optimal yield, as
would be expected for a cultivar originating from
Germany. In the expected warmer future conditions,
with an earlier start to the growing season, the
problems that occur today with soil moisture and
delayed sowings in the spring may still prevail
(Kaukoranta & Hakala 2008). Cultivars such as
Tocada might be the best types to cultivate under
such conditions, at least in southern Finland.
The effect of rainfall on barley yield during the 3-
week period after sowing was negative (Table 5). This
contradicts the hypothesis that drought, rather than
heavy rain, early in the season leads to decreased yield
potential and lower yield. When the total rain sum for
this period was divided into three categories, it was
found that both low and high rain sum during the first 3
weeks after sowing resulted in lowered yield compared
with moderate rain, with no difference in response
between the cultivars. Heavy rains after sowing can
have at least two kinds of effect: mechanical disturb-
ance and water logging. If heavy rain occurs just after
sowing and is followed by a dry and warm period, the
soil surface can be sealed and crusted, hampering
seedling emergence and resulting in sub-optimal stand
density and lower yields. Heavy and long lasting rains
after emergence, again, can result in water logging and
anoxia. Mechanical damage such as crust formation
on the soil surface is difficult to combat. Breeding new
barley varieties with water logging resistance, how-
ever, is in progress (Zhou et al. 2007), but until
substantial breakthroughs in performance of commer-
cial cultivars have taken place, more conventional
drainage measures have to be used to remove the
excess water from the fields. An expected increase in
heavy rains as climate changes calls for new methods
and innovations to control water in the fields,
especially as extensive periods of drought may occur
between the heavy rains.
The present results showed a general and significant
increase in yield with increased rain during 3–7 weeks
after sowing (Table 5). It seems that no barley cultivar
currently grown can produce maximum yields if
drought limits formation of yield potential (number of
tillers, ears and grains/m2). Drought is a very common
problem in Finland during early growth stages of
spring cereals (Peltonen-Sainio et al. 2009c), and it
has been previously reported that every 10mm in-
crease in precipitation during this phase increases
yields by 45–75 kg/ha (Peltonen-Sainio et al. 2011).
Later in the season, even if precipitation increases, the
reduced sink size cannot recover, although the grains
may grow bigger to compensate (Rajala et al. 2009,
2011). In barley, an increase in grain size has not been
found to compensate for the yield losses caused by
reduced grain number (Peltonen-Sainio et al. 2011;
Rajala et al. 2011), whereas in spring wheat, even full
compensation has been reported, caused partly by
more grains developing from the smaller number of
florets (Rajala et al. 2009). The current results show,
however, that the yield increase from higher precipi-
tation has a limit, at least in some barley cultivars: after
a certain precipitation level, more rain fails to increase
yields further (Fig. 1c). A comparable result was found
with winter wheat, where rain first increased yields
but, after an optimum, started to decrease yields
(Kristensen et al. 2011). It would be tempting to
suggest that the varieties with the highest yield
potential would benefit from higher precipitation
levels, but among the tested cultivars this seems not
to hold true; the differences in yield responses to the
highest precipitation levels do not coincide with the
yield levels (Table 2, Fig. 1c).
Unless breeding succeeds in enhancing drought
resistance of barley, future conditions may cause even
worse cultivation problems than is currently the case
(Rötter et al., in press). According to the most recent
scenarios (Harris et al. 2010; Trnka et al. 2011) for
future climatic conditions in high latitudes, precipi-
tation in the spring and summer will increase slightly.
However, major uncertainties exist in climate projec-
tions, especially regarding precipitation (Harris et al.
2010). Even though areas in the North are likely to
become wetter in the future, the increases in precipi-
tation are predicted to take place mainly in the autumn
and winter. This offers no solution for the early season
drought problems, especially as the temperatures, and
thus evaporation rates, will increase simultaneously
(Harris et al. 2010; Trnka et al. 2011). The situation
may be even more difficult in the future if the already
insufficient precipitation falls increasingly as heavy
rains, as suggested by the IPCC (2007b). Heavy rains
may result in both waterlogging and run-off water
escaping from the field; neither phenomena benefiting
the plants as would moderate rain falling over a longer
time period.
156 K. Hakala et al.
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Yield responses to temperature
The last frosts in Finlandmay occur as late as June even
in the southernmost parts of the country. This means
that crops such as spring barley, which are currently
sown around mid-May (13–22 May, Table 1), may
have emerged and already be growing when freezing
occurs. However, barley seems to be rather resistant to
frosts during its early growth phases (Table 5a). The
result was the same whether the lowest temperatures
during early growth were−7 to−2,−2 to−0 or−0 to
9 °C (results not shown), and there were no differences
in the responses among varieties. The frosts occurring
during the early season are mostly night frosts and
typically last only for a few hours. In addition, during
the initial stages of barley development the canopy is
low enough to be partly protected by the relatively
warm soil, even when frost is measured at 2 m above
the soil surface. Also, during early stages of growth
grass meristems remain buried in the ground, and even
if the leaves were to suffer frost damage, the meristems
usually remain undamaged. If leaves are destroyed by
frost, there is a delay in growth, but typically other
conditions later on affect the growth of the plant more
than this early delay.
According to an old Finnish saying ‘shivering sets the
seed’, which means that cold weather at the beginning
of the season promises good yield. This old wisdom
seems to hold true, as in the present test all barley
varieties yielded best when the average temperatures
during early growth (3–4 weeks after sowing) were low
(Table 5, Fig. 2a). One of the reasons for the beneficial
effects of low temperatures early in the season may be
slower development. When the shift from the vegeta-
tive to the generative growth phase is delayed, roots
may penetrate deeper into the soil and grow larger,
which helps the plant to acquire nutrients and water
later on in the season from the larger soil mass. In
addition, tillering may be enhanced, leading to a
denser canopy with more reproductive organs, higher
grain number per unit area and ultimately increased
yield (Evans & Wardlaw 1976). Also in a recent study
withwinter wheat, highwinter temperatures resulted in
lowered yields, possibly due to hastened development
leading to sub-optimal canopy density and reduced
tiller and ear number (Kristensen et al. 2011). A cool
start to a season also usually means higher moisture
levels in the soil and lower evapotranspiration, thus
less limiting moisture conditions early in the season.
Although a cool early season increased yield in
general, the cultivars differed in their reactions to
early season temperatures. Cultivars originating from
lower latitudes than Finland, such as Tocada, Braemar,
Scarlett andMaaren, showed a pattern of lowered yield
atmoderately increased early season temperatures, but
regained some of the yield when the temperatures rose
(Fig. 2a). Yields of other cultivars, either of Finnish or
foreign origin, were either stable or decreased at higher
temperatures, compared with at moderate tempera-
tures. The differing reactions of the cultivars tested to
high early season temperatures emphasize the impor-
tance of looking at the timing of climatic events when
assessing effects on yield: the effect seems to depend
particularly on the development stage of a variety. The
fact that the responses of the cultivars in the present
work differed gives hope for finding suitable varieties
adapted to future warmer conditions, with markedly
earlier sowing dates (Peltonen-Sainio et al. 2009a) and
somewhat lowered frost risk (Trnka et al. 2011).
High temperature sum accumulation rates during a
period 2 weeks before heading decreased yield levels,
with all barley varieties behaving similarly (Table 5,
Fig. 2b). In earlier investigations, yield responses of
barley to increases in temperatures were found to be
most marked exactly during the developmental phase
just prior to heading (Peltonen-Sainio et al. 2011). The
cause for this may be accelerated development that
may result in smaller numbers of grains/m2 and thus
reduced yield, especially if the grain-filling period is
also shortened (Evans & Wardlaw 1976; Kontturi
1979; Wheeler 1996a,b; Hakala 1998; Kristensen
et al. 2011; Peltonen-Sainio et al. 2011). Higher
temperatures also lead to a higher evapotranspiration
and resulting drought problems, which can lower yield
potential and lead to a lower yield (Peltonen-Sainio
et al. 2009c, 2011; Rajala et al. 2011).
In general, barley suffered significantly from periods
with very high temperatures (525 °C) that occurred
just before and after anthesis, when the exposure lasted
longer than 6 days (Fig. 2c). Very high temperatures
during early phases of heading and anthesis may
damage the florets of the developing ears in addition
to accelerating development, leading to reduced grain
number (Wardlaw et al. 1989a; Mitchell et al. 1993;
Wheeler et al. 1996a). During grain filling, high
temperatures may still cause damage to grains and
yield, but this results not so much from reductions in
grain number as from a decrease in grain weight
(Wardlaw et al. 1989a). In an Australian experiment
with wheat, the varieties under study differed in their
sensitivity to high temperatures so that those sensitive
at booting were less sensitive at later phases of grain
Barley variety sensitivity to weather in Finland 157
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development (Wardlaw et al. 1989a). As the number of
florets was not counted in the variety trials reported
here, it is not clear whether the high temperatures
simply accelerated growth rate and shortened the
period during which florets were turning into grains or
physically damaged the florets.
In a study of wheat, Wardlaw et al. (1989b) found
that the varieties originating from warmer conditions
were not necessarily the least sensitive to hot weather.
In the present study, the biggest losses attributable to
very high temperatures were associated with a number
of cultivars originating from lower latitudes than those
typical for Finland. While some Finnish cultivars also
suffered in hot weather, the old cultivar Kustaa, which
has been cultivated widely in Finland for many years,
coped better with hot conditions than any other
cultivar tested. This surprising result may at least partly
be explained by the low average yield of Kustaa
(Table 2): it seems to be one of those varieties that have
been selected due to yield stability rather than high
yielding performance. Despite the fact that the last
10 years have been among the warmest ever (IPCC
2007b), some of the newest cultivars tested here were
among the most sensitive. The same phenomenon has
been recorded for turnip rape (Brassica rapa L.) in
Finland: surprisingly, the newest cultivars have been
found to be quite sensitive to high temperatures at late
seed set and seed filling stages (Peltonen-Sainio et al.
2007). In the future, when heat waves and extreme
temperatures become more common (IPCC 2007b), it
will be increasingly important to find varieties that
suffer minimal yield penalties under increasing temp-
eratures. Luckily, based on the present results, there
seem to be suitable genetic resources present among
current varieties to breed such varieties that can better
tolerate high temperature stress.
When the grain filling period is shortened at
elevated temperatures, the yield tends to be lower,
despite the acceleration of grain growth at higher
temperatures (Evans & Wardlaw 1976; Kontturi 1979;
Wardlaw et al. 1989a; Wheeler et al. 1996b; Peltonen-
Sainio et al. 2011). The present results showed a clear
effect of increased temperature sum accumulation rate
from heading to yellow maturation on yields of the
tested barley cultivars. The lowest accumulation rates
resulted in most cases in lower yields than the highest
accumulation rates, but the best yield levels were
attained at moderate temperature sum accumulation
rates (Fig. 2d ).
Cultivars bred and selected in Finland are mostly
adapted to perform best at current Finnish conditions
with short and intensive growing seasons and low
temperature sums (Peltonen-Sainio et al. 2009c). Thus,
they most often thrive best under the historically
typical climatic conditions and suffer if conditions
deviate. The same acclimation phenomenon was
found also in a European study, where any deviation
of weather conditions from ‘seasonal normal’ after
the vegetative phase of a crop led to decreases in
yield (Peltonen-Sainio et al. 2010). The present study
suggests, however, that considerable diversity exists
in responsiveness of the modern barley cultivars
to early season temperatures, delay of sowing, rain
3–7 weeks after sowing, very high maximum day
temperatures and temperature sum accumulation rate
from heading to yellow ripeness.
CONCLUSIONS
Selection of suitable crop genotypes for future climatic
conditions could be more easily done where diversity
in the important responses already exists than for
where all the varieties respond negatively to various
extents. The present results suggest that diversity exists
in responsiveness of barley cultivars to all temperature-
related variables studied, except for temperature sum
accumulation immediately prior to heading. However,
regarding precipitation-related variables, there ap-
peared to be significant response diversity only to the
rain sum during the phase of linear growth (3–7 weeks
after sowing). Thus, temperatures 2 weeks prior to
heading and precipitation after sowing seemed to be
the weather factors where there was least diversity in
response to exploit. To combat drought and excess rain
early in the season, and to deliver a high yield despite
high temperature sum accumulation before heading,
either new technologies or new genetic material has to
be introduced to enhance adaptive capacity of barley
to climate change and variability in the North.
This study is part of the ADACAPA project (Enhancing
adaptive capacity of the Finnish agricultural sector)
financed by the Finnish Ministry of Agriculture and
Forestry (as part of the National Climate Change
Adaptation Program, ISTO) and MTT Agrifood
Research Finland.
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