## 3 Results  
### Grower Samples  
We examined many different air temperature patterns during 4 fruit developmental stages prior to fruit ripening across the regional farms. We found strong correlations between mean air temperatures during the green to pink fruit (\(r\) = -0.39, \(p\) < 0.006) and pink to rip fruit stages (\(r\) = -0.36, \(p\) < 0.03; Figure 1), but the lowest minimum air temperature also was negatively correlated with SSC (\(r\) = -0.42, \(p\) < 0.003; Figure 2) between first flower and green fruit. Therefore, we subtracted the lowest minimum air temperature from the mean air temperature to generate the temperature differential for each stage of fruit development. This differential was even more strongly associated with SSC for both Stage 1 and Stage 2 (\(r\) = 0.43, 0.36; \(p\) < 0.03, 0.01 respectively, Figure 3). A similarly strong relationship was found with TA (\(r\) = 0.75, 0.74; \(p\) < 0.0001, respectively; Figure 4). SSC and TA were strongly correlated with each other in our study (\(r\) = 0.45, \(p\) < 0.01) so their relationship with the temperature differential was similar. Positive correlations also were found between solar radiation and TA at each stage of fruit development, but correlations with the temperature differential were stronger than correlations with any other weather variable. \begin{table}
\begin{tabular}{c c c} \hline
**Compound** & **Normalized Peak Area** & **CV** \\ \hline Furanone & 0.4 & 119\% \\ Isoamyl acetate & 0.2 & 122\% \\ Ethyl hexanoate & 0.6 & 83\% \\ Linalool & 2.0 & 86\% \\ Hexanoic acid & 1.5 & 100\% \\ Ethyl butanoate & 0.6 & 93\% \\ \hline \end{tabular}
\end{table} 
Table 2: Mean value of normalized peak area (cumulative sum of ion intensity/min retention time) and coefficient of variation (CV) of six volatiles measured in \({}^{\prime}\)Jewel” strawberry fruit collected in 2018 from 22 farms across New York State. Figure 1: Regression between soluble solids content of strawberry fruit at harvest and the mean temperature between green and pink fruit (line A) and pink and red fruit (line B) for 16 farms across New York State visited in 2018, 2019, and 2020. A: y = 0.35x + 0.4, \(r\) = 0.39, \(p\) = 0.0062. B: y = 0.21x + 3.0, \(r\) = 0.36, \(p\) = 0.03. Figure 3: Regression between final soluble solids content of strawberry fruit at harvest and the difference between mean air temperature and the lowest single temperature between first flower and green fruit (A) and green to pink fruit (B) for 16 farms across New York State visited in 2018, 2019, and 2020. A: y = 0.27x + 4.0, \(r\) = 0.43, \(p\)\(<\) 0.005. B: y = 0.24x + 4.6, \(r\) = 0.36, \(p\) \(<\) 0.05. Figure 2: Regression between soluble solids content of strawberry fruit at harvest and the lowest single temperature between first flower and green fruit for 16 farms across New York State visited in 2018, 2019, and 2020. y = -0.26x + 8.9, \(r\) = -0.42, \(p\)\(<\) 0.0027. The relative importance of year-to-year variation and farm-to-farm variation was determined by examining the coefficients of variation (CV) of the measured variables. The CV of the population of differences from one year to the next on the same farm (70-360% for SSC; 34-49% for TA) was much larger than the CV of the population of differences among farms in the same year (12-18% for SSC; 11-25% for TA). Furthermore, SSC and TA levels increased or decreased in a consistent direction from one year to the next across all farms (Figures 5 and 6). Accumulated GDD and rainfall from 1 April were either weakly or not consistently correlated with SSC or TA. SSC and TA were significantly different between years when treating farm site as a replicate (\(p<0.05\), \(<\)0.0001, respectively), but the effect of farm site was not significant when treating year as a replicate (\(p>0.3\), \(p>0.9\), respectively).