Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Statistical Approach to Assess Chill and Heat Requirements of Olive Tree Based on Flowering Date and Temperatures Data: Towards Selection of Adapted Cultivars to Global Warming

Version 1 : Received: 13 October 2022 / Approved: 14 October 2022 / Online: 14 October 2022 (10:44:53 CEST)
Version 2 : Received: 26 November 2022 / Approved: 29 November 2022 / Online: 29 November 2022 (01:05:59 CET)

A peer-reviewed article of this Preprint also exists.

Abou-Saaid, O.; Yaacoubi, A.E.; Moukhli, A.; Bakkali, A.E.; Oulbi, S.; Delalande, M.; Farrera, I.; Kelner, J.-J.; Lochon-Menseau, S.; Modafar, C.E.; Zaher, H.; Khadari, B. Statistical Approach to Assess Chill and Heat Requirements of Olive Tree Based on Flowering Date and Temperatures Data: Towards Selection of Adapted Cultivars to Global Warming. Agronomy 2022, 12, 2975. Abou-Saaid, O.; Yaacoubi, A.E.; Moukhli, A.; Bakkali, A.E.; Oulbi, S.; Delalande, M.; Farrera, I.; Kelner, J.-J.; Lochon-Menseau, S.; Modafar, C.E.; Zaher, H.; Khadari, B. Statistical Approach to Assess Chill and Heat Requirements of Olive Tree Based on Flowering Date and Temperatures Data: Towards Selection of Adapted Cultivars to Global Warming. Agronomy 2022, 12, 2975.

Abstract

Delineating chilling and forcing periods is one of the challenging topics in understanding how temperatures drive the timing of budburst and bloom in fruit tree species. Here, we investigated this question on olive trees, using flowering data collected over six years on 331 cultivars in the worldwide collection of Marrakech, Morocco. Using a Partial Least Squares approach on a long-term phenology (29 years) of ‘Picholine Marocaine’ cultivar, we showed that the relevance of delineating the chilling and forcing periods depends more on the variability of inter-annual temperatures than on the long-term datasets. In fact, chilling and forcing periods are similar between those delineated by using datasets of 29 years and those of only 6 years (2014–2019). We demonstrated that the variability of inter-annual temperatures is the main factor explaining this pattern. We then used the datasets of six years to assess the chill and heat requirements of 285 cultivars. We classified Mediterranean olive cultivars into four groups according to their chill requirements. Our results, using the Kriging interpolation method, indicated that flowering dates of most of these cultivars (92%) were governed by both chilling and forcing temperatures. Our investigations provided first insights to select adapted cultivars to global warming.

Keywords

Olea europaea L.; flowering data; partial least squares regression; Dynamic model; chill requirements; climate change; Mediterranean fruit tree; adapted cultivars.

Subject

Biology and Life Sciences, Agricultural Science and Agronomy

Comments (1)

Comment 1
Received: 29 November 2022
Commenter: BOUCHAIB KHADARI
Commenter's Conflict of Interests: Author
Comment: After reviewing we made the following changes:

- We added the sentence: “Our investigations provided first insights to select adapted cultivars to global warmings” (see page 1)

- We added the information: “the soil is characterized by clay loam texture” (see page 3)

- We described representative cultivars of the four chill groups in the Table 3 as following: “Arbequina (spanish cultivar largely cultivated in the world), Picholine marocaine (single dominant cultivar in Morocco), Rossello (local italian cultivar present in Tuscany), Leccino (main Italian cultivar) (El Bakkali et al., 2019)” (see page 11)

- We added the country of origin for the Pessl Instruments GmbH “Austria” (see page 3)

- Page 1, line 40: replace “It mainly involved” with “It is mainly involved”; It’s done (see page 1)

- Page 2, line 91: please, specify the CRS (coordinate reference system)We added the information: “CRS: WGS84-EPSG:4326” (see page 2)

- Page 3, line 121: please, specify the equation applied by the chillR package to derive the hourly dataWe added the following explanation: “ChillR implements the two following equations (Linvill, 1990) … Differences in daylenth between locations are accounted by computing sunrise and sunset times based on geographic latitude using chillR package [32]” (See page 3)

- Page 4, line 169: it is not clear what period the generated dataset of hourly temperatures covers (1972 to 2019, as reported here or 1972 to 2012, as reported in line 121?; )We revised as follows: “the generated dataset of hourly temperature during the period from 1972 to 2012 and the registered dataset from 2013 to 2019  were analyzed using the chillR package.” (see page 5)

- Page 5, line 190: “therefore” is repeated; We removed “therefore” (see page 5)

- Page 5, line 193- 194: the sentence from “Positive model….day delay bloom” is not clear. In addition, with the aim to improving readability, I suggest better explaining the signs of coefficients, as in the cited paper of Rojo et al. 2020 [9]: …positive coefficients imply that the temperatures (…) were positively correlated with the flowering dates, i.e., lower temperatures during winter lead to earlier flowering dates (equivalent to the chilling accumulation period). In contrast, negative coefficients signify that the temperatures were negatively correlated with the flowering dates, i.e., higher temperatures in spring also contribute to earlier flowering (equivalent to the forcing period); We revised this paragraph as follows: “Positive coefficients imply that the temperatures on these days were positively correlated with the flowering dates, i.e., lower temperatures during winter lead to earlier flowering dates (equivalent to the chilling accumulation period). In contrast, negative coefficients signify that the temperatures were negatively correlated with the flowering dates, i.e., higher temperatures in spring also contribute to earlier flowering (equivalent to the forcing period). This is consistent with the notion of chill requirements, according to which warm temperatures should delay the dormancy breaking and thus lead to later flowering.” (see page 5)

- Page 6, line 243: it is not Fig. S3: maybe it is Fig. S1; We replaced Fig. S3 by Fig. S6 (see page 6)

- Page 12, line 421: please, consider moving figure S10 from Supplementary materials to the paper, it can improve the readability. We moved the Figure S10 from Supplementary materials to the main paper as Figure 7 (see page 12)

- Page 13, line 444: replace “ovoid” with “avoid”; It’s done (see page 13)

- Page 13, line 451: replace Links with “links”; It’s done (see page 13)

- Page 21, line 900: this reference is duplicated (see [9]); We removed the duplicated reference (see page 21)

Note that this article is now published, therefore some changes with regards to English editing and some minor changes have been done. 
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