In Shimla district an increasing trend has been observed in the area from last thirty six years. Change in area of apple crop in Shimla district has been shown in Fig. 3 which shows that area is expanding from last three decades. There was dip in area during the period 2002–2009, which was seen as the decade of uprooting and extensive replanting in this district. But overall the area increased in the district and in many low altitude areas low chilling varieties are planted
According to decade wise data, Fig. 4 during the first representative decade which was considered as baseline year (1984–1993) the area was 23797.3 ha, during the period 1994-2002the area was 32715.89 ha, which was 8918.59 ha more than the baseline period. During the period 2003–2011, the area was 30777.8 ha, which was 6.980.5 ha more than Baseline period similarly during the period 2012–2020 the area of the district under apple crop was 39170ha which was 15372.7 ha more than the baseline period.
It can be observed that there was a considerable increase in the area under apple crop from23797.3ha during the first period to 39170ha during the last decade. The change in area over the years has been increased by 60.7%. [18]have also reported increase in area under apple in Shimla district in the last about thirty years.
An increasing trend has been observed for the last four representative decades in apple production in Shimla district as shown in Fig. 5. Shimla district is known for the origin of the apple or the Golden Belt of Himachal Pradesh crop where different varieties of apple are grown [19]. In 1984-85 the production of apple crop in the district was 129670 MT and in 2019-20 the production has increased by 437024 MT. The area has increased as well as introduction of high yielding varieties have contributed to the higher production (Economic survey Himachal Pradesh 2017-18.[20] .
The decade wise data is presented in Fig. 6 and it showed that during the representative decade (1984–1993) the average production was 179945.89 MT, during 1994–2002 it was 160074 MT, during 2003–2011 it was 308472.8 MT and in the last representative decade 2012–2020 it was 326983 MT which was 147038 MT more than the baseline period. It was also observed that during the second decade (1994–2002), a sharp decline has been seen in between the decade during this particular 1999–2000 year because of severe weather conditions resulting in low fruit set. Such observations of spatial and temporal variability in apple production have also been observed by [21].
An increasing trend has been observed in the productivity of apple crop in Shimla District. Figure 7 illustrates the trends of area-wise apple productivity in Shimla region from 1984 to 2020. In 1984-85 the productivity of apple in Shimla district was 6.16 MT/ha and during 2019-20 the productivity was 10.46 MT/ha. According to Negi et al., [22] factors affecting the productivity of apple crop in Shimla district were Climate variation, application of farm yard manure and chemical fertilizers, human labour availability, variability in expenditure on fixed capital, management factor, literacy and capacity building of orchardists, and deviation of the orchardists from the prescribed spray schedule and density of plantation.
According to decade wise data, it has been observed that there has been an increase in productivity in two representative decades (1st & 3rd ) and decrease in other two representative (2nd & 4th ) decades as shown in Fig. 8. The average productivity in the baseline period / first decade (1984-93) is 7.52 MT/ha, during 1995-02 it was 4.9 MT/ha, during 2003-11 it was 9.96 MT /ha and during 2012-20 it was 8.34 MT/ha. As compared to the baseline there was increase in productivity by 0.82 MT/ha in 2019–2020. According to [23]Apple output has gradually increased, but productivity has decreased, with climate variability, soil and crop improvement, and other factors being blamed. Climate change is also said to be one of the most difficult things to control when it comes to diminishing productivity[24].
The average maximum temperature for last thirty-six years of Shimla district is presented in Fig. 9, and an increasing trend has been observed in Shimla district the average maximum temperature (20.9℃) was recorded for the period 2015–2020 and it was 2.14℃ more than the period 1985–1994(18.76℃).
The average minimum temperature for last thirty-six years Shimla was plotted graphically and an increasing trend in minimum temperature was observed in Shimla district (Fig. 10). the average minimum temperature (11.07 ℃) was recorded for the period 2015–2020 and it was 1.1 ℃ more than (9.97℃) for the period 1985–1994.
In Shimla district the mean decadal rainfall was 1395.48 mm during the baseline Period 1985–1994, 1569. 61 mm in 1995–2004, 1444. 26mm in 2005–2014 and 1409.5 mm in 2015–2020 (Fig. 11) and while comparing it to the baseline period the mean annual rainfall increased in all the three decades by 174.13mm, 48.78 mm and 14.02 mm during the period 1995–2004,2005–2014 and 2015–2020 respectively.
Important information regarding the correlations can be found in the correlation matrix as shown in Table 2. It is evident from the statistical analysis that the maximum temperature and agricultural productivity have a positive correlation (r = 0.268), meaning that greater temperatures are linked to higher productivity. This is expected as improved crop growth and development are frequently facilitated by warmer temperatures.
Table 2
Correlation Matrix between Average Maximum Temperature, Average Minimum Temperature, Average Rainfall and Average Productivity
| Average Max Temp | Average Min Temp | Average Rainfall | Average Productivity |
Max Temp | 0.267876071 | 0.021213863 | -0.877648541 | 1 |
Min Temp | -0.201555743 | 0.272746732 | 1 | |
Avg Rainfall | -0.714480859 | 1 | | |
Avg Productivity | 1 | | | |
On the other hand, there is a relatively strong negative association (r = -0.202) between agricultural productivity and minimum temperature. This implies that productivity tends to decline slightly when minimum temperatures rise. This finding may suggest that apple growth may be negatively impacted by overly high minimum temperatures, or that they may obstruct the ideal growing conditions. Notable relationships exist between average rainfall and agricultural productivity. Average rainfall has a greater connection with productivity than with minimum temperature (r = 0.021), with the former showing only a weak positive correlation that suggests a slight likelihood for heavier rainfall when minimum temperature is higher. The productivity and average rainfall show a relatively strong negative association (r = -0.714), suggesting that higher rainfall levels are linked to poorer productivity. This implies that too much rain could cause waterlogging, nutrient leaching, or an increase in disease susceptibility, all of which could reduce crop production. The overall correlation matrix has been illustrated in Fig. 12.
Several conclusions about the correlations between meteorological factors and agricultural productivity, as seen in Fig. 12, can be made based on the analysis and the correlation matrix that have been provided. The maximum temperature and agricultural productivity have a positive correlation, meaning that better productivity levels are typically associated with warmer temperatures. This implies that warmer temperatures may be advantageous for crops, possibly resulting in higher yields in such circumstances.
Abnormally high minimum temperatures may have a negative impact on agricultural productivity, as indicated by the negative association observed between minimum temperature and productivity. This suggests that crop yields may have a maximum threshold for minimum temperatures, above which they begin to decrease. The more important conclusion is the negative link between rainfall and agricultural productivity, even though there is a slight positive correlation between average rainfall and lowest temperature. This suggests that although increased precipitation may go hand in hand with greater minimum temperatures, it also frequently corresponds with decreased productivity levels. This implies that an excessive amount of rainfall may present problems for crop production, whether as a result of increased disease pressure or waterlogging. The correlations show how intricately meteorological factors and crop productivity correlate. Even though some weather conditions could boost output on their own, their combined effects can have complex implications. For example, while higher temperatures could usually be advantageous, heavy rains could counteract these advantages and reduce output.