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Explora: Environment
and Resource Climate change and apple yield

5.12.4 system. 12,13 The data of NO were adapted from 3. Results
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Himachal Pradesh State Pollution Control Board. The
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apple crop yield data from 1991 to 2018 was obtained from 3.1. Temperature trend analysis
the Department of Horticulture regional office in Shimla Monthly minimum, maximum, and average temperature
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to aid with the assessment of how the variations in climatic trend analysis from January 1901 to December 2020 is
parameters affect apple crop. presented in Table 1. A significant increase in minimum
The Mann–Kendall test was applied for statistical trend temperature could be seen during the months of
analysis. R studio (version 3.5.1) software was used in February, March, April, and November by 1.55°C, 1.08°C,
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data analysis. A P-value ≤ 0.05 was considered statistically 0.87°C, 0.87°C, and 1.10°C, respectively. Furthermore,
significant. the maximum temperature during February, March,
April, November, and December showed a significant
2.3. Calculation of chill units increase by 0.85°C, 0.42°C, 0.67°C, 0.44°C, and 0.42°C,
The hourly chill unit was calculated using the UTAH respectively. Moreover, the average temperature in
model by inputting the temperature data. It is known January, February, March, November, and December
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that a definite period of cool hours in the winter season increased by 0.34°C, 0.81°C, 1.10°C, 0.74°C, and 0.80°C,
is required for the apple trees to break dormancy to respectively, and decreased in the months of June,
induce flowering during the spring season. A lack of July, and September by 0.85°C, 0.54°C, and 0.23°C,
chill hours leads to uneven and delayed leaf development respectively. The temperature trend analysis during the
and flowering, which results in a drop in crop yield and study period indicated a rise in winter temperature and a
poor-quality fruits (small and uneven size). The effective reduction in the temperature of pre-monsoon, monsoon,
chill units during the study period were calculated using and post-monsoon months.
the historic temperature data adopting the UTAH model The temperature changes have different impacts; in
because it introduces the concept of relative chilling case of very high temperatures, the crop development or
effectiveness and negative chilling accumulation (or reproductive phase will disturb pollen and fruit generation
chilling negation), as shown below. and development. 19,20 High temperature reduces anther
• 1 h below 32°F = 0.0 chill unit dehiscence and vivo pollen germination. High temperature
• 1 h 35 – 36°F = 0.5 chill units is also characterized by poor shedding and decreased
• 1 h 37 – 48°F = 1.0 chill units elongation of pollen tube. Several studies have unveiled
• 1 h 49 – 54°F = 0.5 chill units the impact of temperature on flowering, plant growth, and
• 1 h 55 – 60°F = 0.0 chill units crop yield of the different types of crops. 21-23 The minimum
• 1 h 61 – 65°F = -0.5 chill units temperature significantly affects the growth of plants and
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• 1 h > 68°F = -1.0 chill units. the maximum temperature affects the water content in soil
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2.4. Yield reduction risk and plant. A previous study has reported that the rising
temperature caused a decrease in the crop yield, which
Yield reduction risk (X ) was used to measure the risk varied from 2.5 – 10%. 26
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that crop yield will fall from the expected yield trend. The
expected yield trend was calculated using 5-year weighted 3.2. Rainfall trend analysis
average. Equations I to IV were used to calculate the yield Rainfall data from 1901 to 2020 was used for the trend
reduction risk. 18 analysis. Table 2 shows the statistical parameters indicating

YY t Y (I) the significance in rainfall trend variation. The rainfall
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trend analysis showed a significant rise in February, March,
Y − Y April, and May, with increase of 23.2 mm, 19.6 mm,
S = i Y it × 100% i, t = 1, 2, 3.n (II) 10.4 mm, and 13.9 mm, respectively. The increased spring
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season rainfall (February to April) destroyed pollen and
it
led to a reduction in the apple yield.
X = ǀ S ǀ, S < 0 (III)
i i i
3.3. Snowfall trend analysis
X = 0, S >0 (IV)
i i Figure 2 shows the trend of total snowfall during the winter
where Y represents the actual production, Y the trend months, from November to March, of the past 35 years in
t
output, Y the weather output, Ɛ the random error, S the Shimla district. The relevant statistical parameters of the
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relative weather output, and X the yield reduction rate. analysis are shown in Table 3.
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Volume 1 Issue 1 (2024) 3 doi: 10.36922/eer.3608