Olive Trees
Within the influence of climatic factors, lighting (or radiation) and temperature, vary jointly. Thus, the brighter fruits reach a higher temperature and lower humidity, acquiring better maturity and more oil accumulation. However, an excess of temperature, above 35ºC can slow down the photosynthetic activity of the tree, causing a loss of fruit size.
Spring is the season when processes of great relevance take place in cultivation. The formation of inflorescences concur, with the subsequent flowering and fruit set until the bone hardens. Under normal conditions, and with relatively deep soils and high water storage capacity, winter rain is enough to avoid spring water stress.
According to this, the factors that we will study will be:
Rains.
Frost.
The number of days where the average temperature has exceeded 35ºC.
Production Parameters
In this case, we can see differences in production, there are years like 2012 where production fell a lot and the following year in 2013 the production was the highest recorded in these 14 years. The last 5 years have been more stable, around the average of 1950 kg / ha.
Regarding the results of the correlation, we can see that the linear relationship between the variables is not very good, because in no case does it exceed the value of 0.75. However, we will conduct the study.
Production and Climate Factors
The regression line is
and the correlation coefficient is r=0.311.
Although we cannot really affirm that the relation is good, what we do observe is that the greater the amount of rainfall, the greater the amount of production, but the abrupt decreases that have occurred are not always related to years with little rainfall.
Prediction for 2019
Production:1.80·339.2 + 1180.41=1790.97 kg/ha (below the average)
The regression line is
and the correlation coefficient is r=-0.35.
In this case the relation is decreasing: the greater the number of frosts, the lower the production is, but we cannot affirm that there is a good correlation between both variables, since the correlation coefficient is very low.
Prediction for 2019
Production -22.79x19+2547.47=2114.46 kg/ha (over the average).
In this case, the relation between both variables is decreasing again, as we have said before, high temperatures are detrimental to production, but like the rest of the cases, it is not significant, because it is below 0.75.
The regression line is
and the correlation coefficient is r=-0.216.
Prediction for 2019
Production -21’02·12+2358’38=2106’14 kg/ha (over the average).
Summarizing,
