López-Bernal, A., Villalobos, F. J., García-Tejera, O., Testi, L., and Orgaz, F. (2017). Do olive vegetative buds undergo a real dormant state in Winter? Acta Hortic. 1160, 227–230. doi: 10.17660/ActaHortic.2017.1160.33

Mariscal, M. J., Orgaz, F., and Villalobos, F. J. (2000). Radiation-use efficiency and dry matter partitioning of a young olive ( Olea europaea) orchard. Tree Physiol. 20, 65–72. doi: 10.1093/treephys/20.1.65 Overall, the results of all the aforementioned comparisons suggest that model performance is fairly satisfactory. However, further testing against experimental data taken from different environmental conditions and orchard characteristics seems highly desirable. This would help to provide additional evidence on the predictive power of OliveCan, or else to identify situations for which model accuracy could be improved through either better calibrations or reformulation of some routines. Apart from that, it should be noted that the reliability of OliveCan for estimating certain output parameters (e.g., NEE, RESP H) has not been tested specifically in the present study, which should also be the focus of future research efforts. Model Applicability Our gordal olives have been carefully selected from special harvests and this you will appreciate when tasting their firm and fleshy texture. These gordal olives come in a simple brine with a mild anchovy flavouring, so you can enhance their incredible flavour by creating your own marinade. Try them with fresh red chillies, fresh rosemary and garlic to make these olives become first class. Vialet-Chabrand, S., Dreyer, E., and Brendel, O. (2013). Performance of a new dynamic model for predicting diurnal time courses of stomatal conductance at the leaf level. Plant Cell Environ. 36, 1529–1546. doi: 10.1111/pce.12086 Daily effective precipitation ( P eff) is calculated by discounting rainfall interception by the canopy ( P int) from total daily precipitation ( P). P int is calculated using a simplified version of the model of Gómez et al. (2001) and the resulting P eff is distributed proportionally between the two soil zones as a function of the surface fractions that remain rainfed or are wetted by localized irrigation. With regard to P int, the canopy is treated as a capacitor capable of storing rain water up to a certain limit determined by canopy dimensions and leaf area index ( LAI), according to Gómez et al. (2001). The stored water is subsequently lost by direct evaporation, which is simulated based on the Penman–Monteith equation assuming a null canopy resistance. As in Testi et al. (2006), the aerodynamic resistance is deduced from the model proposed by Raupach (1994), parametrized and validated specifically for olive orchards following Verhoef et al. (1997). The direct evaporation from wet foliage prevents tree transpiration ( E p), until the intercepted water is totally lost.The model presented here targets the simulation of the interactions between olive trees and their environment through a detailed characterization of the water and carbon balances of the orchard as affected by weather variables, soil attributes and management operations. The generally high level of agreement found between measured and simulated data evidence the suitability of OliveCan for estimating olive orchard dynamics. These results encourage the application of the model to simulate the growth, carbon exchange and water relations of olive orchards in a wide range of research contexts, including studies on the performance of olive trees under climate change scenarios. The development of OliveCan has also highlighted significant knowledge gaps in relation to some physiological processes and the cultivar specificity of some of the parameters. Further research on these aspects may contribute to improve the reliability of the model. Author Contributions When available, the values of the different parameters were taken from the literature. Supplementary Table S2 provides a complete list with the parameter values used for the simulations and the source from which they were taken. In short, the parameters of the SPAC model were taken from García-Tejera et al. (2017a, b), who, in turn, gathered most of the parameter values from different sources. Parameters related to phenology were obtained from reports by De Melo-Abreu et al. (2004) and López-Bernal et al. (2014, 2017). The studies by Mariscal et al. (2000) and Pérez-Priego et al. (2014) were used for setting the maintenance respiration and PV coefficients, respectively. Parameters related to the calculation of fruit number and yield were taken from several sources, including experimental data (see section “Number of Fruits and Alternate Bearing” in Supplementary Material). The coefficient of oil yield to dry fruit matter was taken from experimental data collected in a hedgerow cv. ‘Arbequina’ orchard ( López-Bernal et al., 2015). Partitioning coefficients were based on findings by Mariscal et al. (2000); Villalobos et al. (2006) and Scariano et al. (2008). Reports from Barranco et al. (2005) and Koubouris et al. (2009) were used to parametrize the routines modeling the impacts of frost damage and heat stress, respectively. Coefficients modulating fine root growth distribution were directly taken from Jones and Kiniry (1986). Finally, parameters implied in the soil carbon balance were taken from Verstraeten et al. (2006); Huang et al. (2009) and, to a lesser extent, from other studies. Model Testing What’s inside a stuffed olive? When you buy stuffed olives from the store, they’re typically stuffed with pimiento peppers, you probably recognize that red color found in green olives.

Considering all the simulations together, the maximum simulated oil yield was 358 g m -2 (Table 1), which is comparable to the maximum values estimated by the model of Morales et al. (2016) and to available experimental data ( Villalobos et al., 2006; Pastor et al., 2007). Simulated values of radiation use efficiency for oil production (i.e., the amount of oil produced per unit of intercepted PAR) averaged over biennia ranged between 0.17 and 0.10 g MJ -1. These estimates are within the range of variation found by Villalobos et al. (2006) across a wide range of commercial orchards in Southern Spain. Ingredients: Water, pitted green olives, salt, flavour enhancer (E-621, E-627, E-631), sugar, acidulant (E-330, E-270), antioxidant (E-300), preservative (E-202),

Regulated deficit irrigation (RDI), which applied the same seasonal water as CDI, with a midsummer (July 1st to September 10th–15th) deficit period without irrigation. The goal of this study is to present and test a process-oriented model integrating existing knowledge on the growth and development processes of olive orchards and capable to account for the impacts of water stress, management and climate on their productivity, in the absence of nutrient deficiencies, diseases and pests. The model, hereafter named ‘OliveCan’ -which comes from ‘Olive Canopy-,’ was formulated using the models by Testi et al. (2006); Morales et al. (2016) and García-Tejera et al. (2017a) as starting point. Materials and Methods Model Description Bonachela, S., Orgaz, F., Villalobos, F. J., and Fereres, E. (2001). Soil evaporation from drip irrigated olive orchards. Irrig. Sci. 20, 65–71. doi: 10.1007/s002710000030 The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Supplementary Material Further research regarding genetic variability in model parameters is also desirable. With the exception of those related to the simulation of flowering date ( De Melo-Abreu et al., 2004) and frost damage ( Barranco et al., 2005), all parameters have been taken from past experiments carried out either with only one cultivar each (‘Arbequina’ being the most frequent) or averaging the results obtained for a few of them. Although the scarce literature does not allow us to disentangle how many of these crop parameters are cultivar-specific, it is clear that exploring their genetic variability might be important for enhancing model reliability. Moreover, the quantification of such cultivar variability may be used for evaluating its impact on tree physiology and productivity under different management, weather or orchard characteristics using OliveCan, which may be useful for breeding purposes.