Canonical correlation analysis applied to regulated deficit irrigation in `Tommy Atkins´ mango trees

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DOI:

https://doi.org/10.4025/actascitechnol.v45i1.62882

Keywords:

grouping; multivariate analysis; water deficit; semi-arid region.

Abstract

The objective was to identify the effect of regulated deficit irrigation on physiological, yield and root descriptors of `Tommy Atkins´ mango tree grown in a semi-arid region of Brazil. The work was carried out during two production cycles on an 11-year-old mango orchard. The design was randomized blocks with five treatments and six replications. Irrigation treatments were based on the trees´ development stage: T1, irrigation supplying 100% of the crop evapotranspiration (ETc) in three production stages: fruit set stage (SI), fruit expansion stage (SII), and physiological maturation stage of the fruits (SIII); T2, 50% ETc in SI and 100% ETc in SII and SIII; T3, 100% ETc in SI and SIII and 50% ETc in SII; T4, 100% ETc in SI and SII, and 50% ETc in SIII; and T5, without irrigation in all three stages. Physiological data were measured once per stage. After harvesting the second cycle, roots were collected, following a completely randomized design, with five treatments and three replications, to determine the total root length density. Total or partial water deficit in `Tommy Atkins´ mango trees was identified by decreasing transpiration (E) and photosynthesis (A) and increasing leaf temperature (Tleaf). The total root length density is similar in all irrigation strategies up to 1 m horizontal distance and 0.10 m depth. Water deficit applied in the physiological maturation stage improves yield and water use efficiency.

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Published

2023-04-28

How to Cite

Dias, C. B. G. ., Santos, M. R. dos, Donato, S. L. R. ., & Azevedo, A. . M. . (2023). Canonical correlation analysis applied to regulated deficit irrigation in `Tommy Atkins´ mango trees . Acta Scientiarum. Technology, 45(1), e62882. https://doi.org/10.4025/actascitechnol.v45i1.62882

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Technological Information

 

0.8
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0.8
2019CiteScore
 
 
36th percentile
Powered by  Scopus

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