2.1. Experimental Season Thermal Conditions
In
Table 1 the monthly average temperatures recorded in the study area during seasons 2009, 2010 and 2011, and the variation from the long term average, are reported. The first season was characterized by high UV intensities during the period from June to September [
32,
41] and by a much greater prevalence of high air temperatures (>30 °C), as compared both to the long term 30 year average and seasons 2010 and 2011 [
32,
41,
42,
43]. In 2009, the maximum temperature (T
max) during berry growth and development reached a monthly average value of 27.5 °C in June which was about 3 °C higher than the 30 year average and the seasons 2010 and 2011. Again, in July T
max averaged 31.1 °C, nearly +3 °C than 2011 and long term average but about +1.5 °C higher compared to 2010.
The months of August and September 2009 continued recording temperatures higher than the 30 year average for the same period, while the seasons 2010 and 2011 were much less hot and the maximum temperature values remained close to those of long term data, or even lower than the average values (−0.7 and −0.3 °C during ripening 2010). Also mean (Tmed) and minimum (Tmin) temperatures registered much higher values than the average in 2009 (about +2.4 and +1.2 °C for T med and +1.5 and 0.4 °C for Tmin during ripening months). Conversely in 2010, a lower Tmin was registered in August and September (−0.4 °C and −0.6 °C, respectively) and in 2011, Tmin in August remained 0.6 °C below the average value, while in September it was only slightly higher than the average (about +0.3 °C).
Table 1.
Monthly temperature conditions during the 2009‒11 growth seasons (from June to September) and long-term monthly 30-year average (1971 to 2000) in Capo Frasca, Italy [
42,
43]. Average values (x) and variation (Δ) between the study periods and the 30 year average.
Table 1.
Monthly temperature conditions during the 2009‒11 growth seasons (from June to September) and long-term monthly 30-year average (1971 to 2000) in Capo Frasca, Italy [42,43]. Average values (x) and variation (Δ) between the study periods and the 30 year average.
Variable | Period | June | July | August | September |
---|
x | Δ | x | Δ | x | Δ | x | Δ |
---|
Tmax (°C) | 2009 | 27.5 | 3.0 | 31.1 | 3.3 | 30.3 | 1.5 | 26.9 | 0.9 |
| 2010 | 24.6 | 0.1 | 29.3 | 1.5 | 28.1 | −0.7 | 25.7 | −0.3 |
| 2011 | 24.9 | 0.4 | 27.6 | −0.2 | 29.7 | 0.9 | 26.8 | 0.8 |
| 30 year | 24.5 | | 27.8 | | 28.8 | | 26.0 | |
Tmed (°C) | 2009 | 24.5 | 3.6 | 27.5 | 3.5 | 27.3 | 2.4 | 23.5 | 1.2 |
| 2010 | 22.1 | 1.2 | 26.4 | 2.4 | 25.3 | 0.4 | 22.6 | 0.3 |
| 2011 | 22.2 | 1.3 | 24.4 | 0.4 | 25.7 | 0.8 | 23.7 | 1.4 |
| 30 year | 20.9 | | 24.0 | | 24.9 | | 22.3 | |
Tmin (°C) | 2009 | 19.9 | 2.6 | 22.5 | 2.4 | 22.6 | 1.5 | 19.1 | 0.4 |
| 2010 | 17.9 | 0.6 | 22.3 | 2.2 | 20.7 | −0.4 | 18.1 | −0.6 |
| 2011 | 18.2 | 0.9 | 20.5 | 0.4 | 20.5 | −0.6 | 19.0 | 0.3 |
| 30 year | 17.3 | | 20.1 | | 21.1 | | 18.7 | |
2.3. Berry Skin Temperature
Figure 1 reports the permanence of defined ranges of berry skin temperature (T
b) during ripening. For each season, we calculated the 10th and 90th percentile of T
b in order to determine specific low and high temperatures (<15 °C, <17 °C and >35 °C) that, due to their frequency, could have affected berry skin metabolism.
Figure 1.
Berry skin exposure to defined ranges of temperature (<15 °C, <17 °C and >35 °C) in east and west canopy sides, during ripening in (A) Bovale Grande and (B) Cannonau.
Figure 1.
Berry skin exposure to defined ranges of temperature (<15 °C, <17 °C and >35 °C) in east and west canopy sides, during ripening in (A) Bovale Grande and (B) Cannonau.
Berries in the west side of the canopy were much more exposed to high temperatures than those in the east side. Furthermore, during ripening 2009, the prevalence of elevated temperatures (>35 °C) was significantly higher in all treatments and in both canopy sides as compared to the two following seasons. No variety effect was observed, and in Bovale Grande the permanence of such temperatures ranged from nearly 8% of the duration of ripening in East Vis and Vis + UV-A berries to 14% and 16% in Control and in West Vis and Vis + UV-A berries. In Cannonau, the results were similar, although the differences between east and west sides were higher in Control berries. In 2010, East Vis and Vis + UV-A berries were exposed to more than 35 °C for less than 1% of the entire ripening period in both varieties, while Control and West Vis + UV-A berry skin had more than 35 °C for about 6% of the time. In 2011, all treatments were subjected to more than 35 °C for a similar amount of time, the greatest difference being recorded in Cannonau between Vis and Control berries (from 5% to 10% of the time, respectively). The smallest prevalence of low temperatures (<15 °C) was observed in 2009, specially in Cannonau Vis berry skin (for about less than 2% of the duration of ripening). In that year, Control and Vis + UV-A berry skin reached less than 15 °C with higher frequency, lasting 5% and 7% of the time below this threshold in both varieties. In 2010, the percentage of time for which Control and Vis + UV-A berry skin remained with less than 15 °C was about 7% in Cannonau and 9% in Bovale Grande, and in 2011 it decreased to 4% and to 5% respectively.
Overall, the season 2011 showed the lowest permanence of Tb inferior to 17 °C and also the higher permanence of milder temperatures (ranging from 17 °C to 35 °C). This result is in accordance to the previously described air temperature conditions, since among the three seasons, the third was in fact the one in which air temperatures remained closer to the 30 year average.
2.4. Berry Skin Anthocyanins
The effect of light regime in berry skin anthocyanin content (TSA) at harvest was inconsistent and only statistically significant in Bovale Grande during the season 2010 and in Cannonau during 2009, when control berries were able to accumulate a significantly higher content of TSA as compared to the two UV-screening treatments (
Table 3). No significant differences were observed between the two UV screening treatments but in the last two years of trial slightly higher mean values were observed in Cannonau Vis + UV-A. Also, Spayd
et al. [
12] obtained inconsistent results while Martínez-Lüscher
et al. [
36] have reported that, in Tempranillo berries, although higher concentrations of extractable anthocyanins had been observed, UV-B light did not alter total anthocyanin concentration. Azuma
et al. [
31] studies have demonstrated that high temperature (>35 °C) severely decrease TSA in berry skin and that low temperature (15 °C) and light induce anthocyanin accumulation in a synergetic manner. In our study both varieties were exposed to high temperatures for long time during 2009, with a small permanence of low temperatures (<17 °C). As compared to the previous year, in 2010, direct light exposure promoted higher anthocyanin accumulation in Control berries of Bovale Grande but not in Cannonau. In this variety, Vis + UV-A and Vis berries TSA concentration was probably enhanced due to the effect of lower permanence of high temperatures and higher permanence of low temperatures (
Figure 1).
Cannonau showed significantly lower TSA contents as compared to Bovale Grande in all three seasons. Yet, for Cannonau Vis + UVA treatment, we observed an increase of about 80% in TSA both in 2010 and 2011 as compared to the hot 2009. The same pattern was observed for the Vis treatment: an increase in TSA of 230% in 2010 and 95% in 2011 for Vis. In Bovale Grande, the variation in TSA content between 2009 and the other two years of trial was more relevant in absolute value, but not in percent variations, since for both Vis + UVA and Vis treatments the variation ranged from +50% to +92%.
Table 3.
Effects of light regime on total skin anthocyanin content (mg malvidin kg−1 berry) in Bovale Grande and Cannonau berries at harvest. Mean values (n = 9) and one-way ANOVA. Small letters indicate significant difference of mean values between treatments and ns refers to non-significant differences between treatment.
Table 3.
Effects of light regime on total skin anthocyanin content (mg malvidin kg−1 berry) in Bovale Grande and Cannonau berries at harvest. Mean values (n = 9) and one-way ANOVA. Small letters indicate significant difference of mean values between treatments and ns refers to non-significant differences between treatment.
| | Bovale Grande | Cannonau |
---|
| | 2009 | 2010 | 2011 | 2009 | 2010 | 2011 |
Treatment | Control | 306.9 | 585.8 a | 654.1 | 119.5 a | 127.0 | 102.1 |
| Vis + UV-A | 298.8 | 450.3 b | 638.4 | 80.9 a,b | 182.1 | 143.2 |
| Vis | 258.3 | 496.5 b | 650.2 | 55.5 b | 146.4 | 108.6 |
| Sig. | ns | < 0.05 | ns | <0.05 | ns | ns |
Though having important agronomic and oenological aptitudes [
40,
44], many accessions of Cannonau have shown low phenolic potential, namely regarding TSA. However, in sunny and warm climate conditions, using deficit irrigation strategies, this behavior can be partially compensated by an accumulation of higher proportion of more color stable forms of anthocyanins [
45,
46].
In our work, light regimes have influenced berry skin anthocyanin composition differently in the varieties and among seasons. In
Figure 2 the proportion anthocyanin derivatives berry skin in Bovale Grande at harvest 2009, 2010 and 2011 are presented. In the hot season 2009, a higher proportion of cyanidin and peonidin glucosides was observed in Control and Vis + UV-A berries during ripening and at harvest, which is in accordance with previous studies suggesting a positive effect of light on dihydroxylated anthocyanins [
33]. However, in the following years the treatments did not differ significantly in Bovale Grande and in Cannonau, the proportion of these derivatives was only significantly different between light treatments in 2010. Besides, the exposure to natural UV light intensities did not induce differences in trisubtituted anthocyanins in Bovale Grande and a decrease in these forms was observed on Cannonau Control berries during 2009. In 2009, Bovale Grande Control and Vis + UV-A berries presented higher proportion of acetylglucoside forms (
Figure 3), probably due to both the combined effect of UV light and higher permanence of elevated temperatures [
12,
13,
17,
34,
36]. In 2010 and 2011, the differences between treatments were not so evident. Yet, Cannonau Control berries presented higher acylation degree with coumaric acid, and higher contents of all anthocyanin derivatives at harvest, except for malvidin glucosides (
Figure 3), which can be ascribed to a combined effect of the light treatment and a higher permanence of low temperatures in those years [
31].
Figure 2.
Proportion of TSA in delphinidin, cyanidin, petunidin, peonidin and malvidin based anthocyanins in Bovale Grande (A) and Cannonau (B) berries at harvest 2009, 2010 and 2011. Mean values (n = 9) and one-way ANOVA. Lower case letters (a and b) above the bars indicate significant difference and ns refers to non-significant difference of mean values between treatment (p < 0.05).
Figure 2.
Proportion of TSA in delphinidin, cyanidin, petunidin, peonidin and malvidin based anthocyanins in Bovale Grande (A) and Cannonau (B) berries at harvest 2009, 2010 and 2011. Mean values (n = 9) and one-way ANOVA. Lower case letters (a and b) above the bars indicate significant difference and ns refers to non-significant difference of mean values between treatment (p < 0.05).
Figure 3.
Proportion of TSA in 3-monoglucoside (3G), 3-acetyl-glucoside (3G-Ac) and 3-p-coumaroyl-glucoside (pC-3G) forms in Bovale Grande (A) and Cannonau (B) berries at harvest 2009, 2010 and 2011. Mean values (n = 9) and one-way ANOVA. Lower case letters (a and b) above the bars indicate significant difference and ns refers to non-significant difference of mean values between treatment (p < 0.05).
Figure 3.
Proportion of TSA in 3-monoglucoside (3G), 3-acetyl-glucoside (3G-Ac) and 3-p-coumaroyl-glucoside (pC-3G) forms in Bovale Grande (A) and Cannonau (B) berries at harvest 2009, 2010 and 2011. Mean values (n = 9) and one-way ANOVA. Lower case letters (a and b) above the bars indicate significant difference and ns refers to non-significant difference of mean values between treatment (p < 0.05).
Major differences were observed among seasons (
Table 4). In the two cultivar, the elevated temperatures of 2009 lead to higher accumulation of delphinidin and petunidin, and less peonidin and malvidin derivatives (
Figure 2) in accordance to the results obtained by other authors [
12,
13,
17]. In addition, in 2009 a very significant increase in the proportion of acylated forms was evident right from the beginning of ripening, with much lower monoglucoside contents in both varieties and in every light treatment (
Figure 3,
Table 4). At harvest 2011, the variation in the proportion of anthocyanin derivatives showed a trend similar to that observed in 2009, with significantly higher proportion of delphinidin and petunidin derivatives than in 2010 in Bovale Grande, especially in Control berries, and a much lower proportion of peonidin and malvidin in all treatments as compared to 2010.
These results are in accordance to those reported by Azuma
et al. [
31] who observed an increasing peonidin and malvidin derivatives under light and low temperatures. As far as the acylation degree is concerned, again, in 2011 berry skin anthocyanin profile showed an intermediate content as compared to the other two seasons, with significantly higher anthocyanin acylation than in 2010, probably due two higher permanence of elevated temperatures (
Table 4). Light regimes affected anthocyanin partitioning in the two varieties, but the influence of natural UV light intensities on anthocyanin metabolism can be largely surpassed by that of high temperatures, both via anthocyanin degradation and increased acetylation. A detailed analysis on this issue can be found in [
32].
Table 4.
Effect of light treatment on berry skin percent composition of monoglucoside and acylated anthocyanins in Bovale Grande and Cannonau at harvest 2009, 2010 and 2011. Mean values (n = 9) and one-way ANOVA.
Table 4.
Effect of light treatment on berry skin percent composition of monoglucoside and acylated anthocyanins in Bovale Grande and Cannonau at harvest 2009, 2010 and 2011. Mean values (n = 9) and one-way ANOVA.
| | Bovale Grande | Cannonau |
---|
Control | Vis + UV-A | Vis | Control | Vis + UV-A | Vis |
---|
Monoglucosides | 2009 | 56.0 b | 58.2 b | 52.5 b | 77.0 | 76.4 | 63.1 b |
2010 | 78.0 a | 77.8 a | 75.5 a | 76.0 | 76.0 | 87.3 a |
2011 | 63.4 b | 65.2 b | 60.2 ab | 73.3 | 78.4 | 80.2 a |
Sig. | <0.05 | <0.05 | <0.05 | ns | ns | <0.05 |
Acetylglucosides | 2009 | 12.1 a | 10.2 a | 7.5 b | 10.1 a | 9.4 | 14.0 a |
2010 | 6.8 b | 6.1 b | 6.5 b | 4.2 b | 4.2 | 3.4 b |
2011 | 10.2 a | 9.4 a | 9.3 a | 6.1 c | 5.9 | 5.1 b |
Sig. | <0.05 | <0.05 | <0.05 | <0.05 | <0.05 | <0.05 |
Coumaroylglucosides | 2009 | 32.0 | 31.6 a | 40.0 a | 12.9 b | 14.2 | 22.9 a |
2010 | 15.3 | 16.0 b | 18.1 b | 19.8 a | 19.8 | 9.3 c |
2011 | 25.6 | 24.5 ab | 29.4 ab | 20.6 a | 15.7 | 14.8 b |
Sig. | <0.05 | <0.05 | <0.05 | <0.05 | ns | 0.05 |
2.5. Thermal Efficiency for Berry Skin Anthocyanin Accumulation
Our results suggest that high and low temperatures were more effective than light treatment on influencing anthocyanin accumulation in Cannonau berry skin (
Table 3,
Figure 2 and
Figure 3). Greater sensitivity to anthocyanin decrease driven by high temperature was observed in Cannonau [
32]. Contrary to Bovale Grande and many other varieties [
30], it is extremely difficult to observe the typical two-phase relationship between dynamic of anthocyanin accumulation and that of sugars (°Brix) in Cannonau. In our study, we plotted TSA with total soluble solid (TSS) data from the three years of experiment, and we obtained two completely different scatterplots for the two varieties (
Figure 4). Bovale Grande showed a classic linear relationship between data [
30], with a first lag phase where TSS increases and very small changes occur in TSA, followed by a nearly linear phase where both compounds increase in parallel. Conversely, Cannonau data does not fit any geometrical curve, but present a quite random dispersion of points, much evident under high temperature conditions. Besides for its genetically feeble phenolic potential, such behavior could partially be explained by a high sensitivity to the permanence of critical ranges of temperature [
30,
31]. In fact, as compared to warm and low altitude sites, in Mediterranean mountain terroirs, where weather conditions are characterized by higher daily temperature ranges, the pattern of berry skin anthocyanin accumulation is linearly correlated with TSS increments and considerably greater TSA contents have long been reported [
46].
In order to better understand the effects of temperature on berry skin anthocyanin accumulation, we calculated the accumulated thermal time for anthocyanin synthesis, using the normal heat hours (NHH) model [
47,
48] and we determined the permanence (in hours) of low (<15 °C and <17 °C) and high (>35 °C) temperatures, based on berry skin temperature recorded during ripening. We then tested the relationships between TSA and the four predictor variables (NHH, H
T > 35 °C, H
T < 15 °C and H
T < 17 °C) for each variety.
Figure 4.
Relationships between total soluble solids (TSS) and total berry skin anthocyanin (TSA) content in (A) Bovale Grande and (B) Cannonau datasets.
Figure 4.
Relationships between total soluble solids (TSS) and total berry skin anthocyanin (TSA) content in (A) Bovale Grande and (B) Cannonau datasets.
Table 5 and
Table 6 show the main regression analysis estimates and the model performances of three models tested for Bovale Grande and Cannonau, respectively. The first model estimates TSA contents based on a single variable, the NHH, which was statistically highly significant and showed a very good fitting for Bovale Grande, with correlation (R) and determination (R
2) coefficients of 0.861 and 0.741, respectively. Conversely, despite being a highly significant variable in the simple linear regression for Cannonau model 1 (variable
p-value = 0.004), the NHH was poorly correlated with TSA, with an R of 0.511 and a R
2 of only 0.235. In both varieties, the introduction of the second variable H
T > 35 °C resulted in an improvement of the regression model, especially for Cannonau, with no collinearity problems between predictor and dependent variables, as indicated by the values of tolerance and variance inflation factor. Nevertheless, as far as Bovale Grande is concerned, the second model only resulted in a very slight increase of R and R
2 as compared to model 1, and H
T > 35 °C p-value was indicative of non-statistical significant contribution of this variable for the overall regression. For Cannonau, the inclusion of NHH and H
T > 35 °C as predictor variables (model 2) improved considerably the modeling performances as compared to the simple linear model. Both variables were highly significant correlated to TSA and increased regression significance, R, R
2 and Adjusted R
2 (Adj.R
2), respectively to: 0.0001, 0.649, 0.421 and 0.378. The third model is divided into two alternatives, using: (a) H
T < 17 °C and (b) H
T < 15 °C. The model including the three independent variables, NHH, H
T > 35 °C and H
T < 17 °C (model 3), was the one that explained the most of the variations in Bovale Grande TSA, about 75.9%, without showing collinearity problems. Also in Cannonau, this model accounted for a much higher proportion of total anthocyanin variation than the previous two, although total berry skin anthocyanin contents still remained quite weakly associated with the temperature driving variables (Adj.R
2 = 0.419).
In the last model, after adding NHH, the β coefficient of the variable representing prevalence of low temperatures assumed negative sign in the correlation with TSA in Bovale Grande. On the contrary, in Cannonau the permanence of low temperatures (HT < 17 °C or HT < 15 °C) have demonstrated a positive role in TSA accumulation model 3 while HT > 35 °C assumed negative influence, meaning that holding constant the other predictors, a variation of +1 in HT > 35 °C results in a reduction of −0.209 in TSA.
Table 5.
General model estimates of Bovale Grande berry TSA (mg malvidin kg−1), linear regression analysis and model performance.
Table 5.
General model estimates of Bovale Grande berry TSA (mg malvidin kg−1), linear regression analysis and model performance.
Model | Predictors | Descriptive Statistics | Model Performance |
---|
N | df1 | df2 | Regression Sig. | R | R2 | Adj. R2 | Unstandardized Coefficients | Variables Significance | Collinearity Statistics |
---|
β | Std. Error | T | Sig. | Tolerance | VIF |
---|
1 | Intercept | 30 | 1 | 28 | 0.0001 | 0.861 | 0.741 | 0.732 | 50.348 | 29.272 | 1.72 | 0.096 | | |
NHH | 0.594 | 0.066 | 8.845 | 0.000 | 1 | 1 |
2 | Intercept | 30 | 1 | 27 | 0.0001 | 0.865 | 0.748 | 0.730 | 44.92 | 29.988 | 1.498 | 0.146 | | |
NHH | 0.552 | 0.081 | 6.79 | 0.000 | 0.671 | 1.489 |
HT > 35 °C | 0.41 | 0.456 | 0.899 | 0.377 | 0.671 | 1.489 |
3 | Intercept | 30 | 1 | 26 | 0.0001 | | | | 43.206 | 29.741 | 1.524 | 0.140 | | |
NHH | | | | 0.808 | 0.153 | 5.538 | 0.000 | 0.187 | 5.359 |
HT > 35 °C | | | | 0.108 | 0.478 | 0.238 | 0.814 | 0.602 | 1.661 |
HT < 17 °C (a) | 0.887 | 0.784 | 0.759 | −1.084 | 0.527 | −2.059 | 0.050 | 0.244 | 4.106 |
HT < 15 °C (b) | 0.873 | 0.762 | 0.735 | −1.661 | 1.334 | −1.245 | 0.224 | 0.288 | 3.473 |
Table 6.
General model estimates of Cannonau berry TSA (mg malvidin kg−1), linear regression analysis and model performance.
Table 6.
General model estimates of Cannonau berry TSA (mg malvidin kg−1), linear regression analysis and model performance.
Model | Predictors | Descriptive Statistics | Model Performance |
---|
N | df1 | df2 | Regression Sig. | R | R2 | Adj. R2 | Unstandardized Coefficients | Variables Significance | Collinearity Statistics |
---|
β | Std. Error | T | Sig. | Tolerance | VIF |
---|
1 | Intercept | 30 | 1 | 28 | 0.004 | 0.511 | 0.261 | 0.235 | 71.013 | 7.776 | 9.133 | 0.000 | | |
NHH | 0.055 | 0.017 | 3.145 | 0.004 | 1 | 1 |
2 | Intercept | 30 | 1 | 27 | 0.001 | 0.649 | 0.421 | 0.378 | 75.066 | 7.168 | 10.473 | 0.000 | | |
NHH | 0.083 | 0.019 | 4.412 | 0.000 | 0.698 | 1.432 |
HT > 35 °C | −0.271 | 0.099 | −2.727 | 0.011 | 0.698 | 1.432 |
3 | Intercept | 30 | 1 | 26 | 0.001 | | | | 76.575 | 6.983 | 10.966 | 0.000 | | |
NHH | | | | 0.035 | 0.033 | 1.052 | 0.302 | 0.207 | 4.840 |
HT > 35 °C | | | | −0.209 | 0.103 | −2.036 | 0.052 | 0.611 | 1.637 |
HT < 17 °C (a) | 0.692 | 0.479 | 0.419 | 0.235 | 0.138 | 1.706 | 0.100 | 0.271 | 3.695 |
| HT < 15 °C (b) | 0.681 | 0.463 | 0.401 | 0.42 | 0.292 | 1.44 | 0.162 | 0.434 | 2.306 |
For both varieties, the introduction of H
T < 15 °C instead of H
T < 17 °C produced a smaller improvement on the regression models 1 and 2, reducing correlation and determination coefficients as compared to model 3(a) and adding no statistical significance to the prediction. In
Figure 5, the relationships between the total berry skin anthocyanin and the NHH and the linear regression model 3(a), for Bovale Grande (A) and Cannonau (B) datasets, are represented. In both varieties, the addition of prevalence of high (T > 35 °C) and low (T < 17 °C) temperatures during ripening as predictors of TSA increased the model efficiency goodness in the linear regression, almost doubling the R
2 for the Cannonau dataset.
Figure 5.
Relationships between total berry skin anthocyanin (TSA) content and the Normal Heat Hours (NHH) and between TSA and the regression model 3 in (A) Bovale Grande and (B) Cannonau datasets.
Figure 5.
Relationships between total berry skin anthocyanin (TSA) content and the Normal Heat Hours (NHH) and between TSA and the regression model 3 in (A) Bovale Grande and (B) Cannonau datasets.
A regression considering only NHH and H
T < 17 °C, excluding H
T > 35 °C, would not improve much the model performance in Bovale Grande (R = 0.885; R
2 = 0.783, Adj.R
2 = 0.767) and in Cannonau (R = 0.629; R
2 = 0.396, Adj.R
2 = 0.351) as compared to the NHH model. Despite the influence of other factors on anthocyanin accumulation in berry skin, the permanence of high and low temperatures can help explain the TSA accumulation pattern in Cannonau berries under warm climate conditions. In fact, when modeling TSA based on NHH and the permanence of temperatures higher than 35 °C and lower than 17 °C (
Table 6) we observed much better fitting and model performance for Cannonau data than using only the NHH. Additionally, our results showed that the NHH model alone already represents a good estimator of TSA for Bovale Grande, also under warm climate conditions (
Table 5).