Abstract
In 2020, mango (Mangifera indica) exports contributed over 40 million tons, worth around US$20 billion, to the global economy. Only 10% of this contribution was made from African countries including Ghana, largely due to lower investment in the sector and general paucity of research into the mango value chain, especially production, quality and volume. Considering the global economic importance of mango coupled with the gap in the use of the remote sensing technology in the sector, this study tested the hypothesis that phenological stages of mango can be retrieved from Sentinel-2 (S2) derived time series vegetation indices (VIs) data. The study was conducted on four mango farms in the Yilo Krobo Municipal Area of Ghana. Seasonal (temporal) growth curves using four VIs (NDVI, GNDVI, EVI and SAVI) for the period from 2017 to 2020 were derived for each of the selected orchards and then aligned with five known phenology stages: Flowering/Fruitset (F/FS), Fruit Development (FRD), Maturity/Harvesting (M/H), Flushing (FLU) and Dormancy (D). The significance of the variation “within” and “between” farms obtained from the VI metrics of the S2 data were tested using single-factor and two-factor analysis of variance (ANOVA). Furthermore, to identify which specific variable pairs (phenology stages) were significantly different, a Tukey honest significant difference (HSD) post-hoc test was conducted, following the results of the ANOVA. Whilst it was possible to differentiate the phenological stages using all the four VIs, EVI was found to be the best related with p < 0.05 for most of the studied farms. A distinct annual trend was identified with a peak in June/July and troughs in December/January. The derivation of remote sensing based ‘time series’ growth profiles for commercial mango orchards supports the ‘benchmarking’ of annual and seasonal orchard performance and therefore offers a near ‘real time’ technology for identifying significant variations resulting from pest and disease incursions and the potential impacts of seasonal weather variations.
Highlights
Introduction iationsMango (Mangifera indica) has been venerated as the ‘King of Fruits’ with a global production of 40 million tons at an average productivity of approximately 8 tons per ha from 5.4 million hectares [1,2]
Less variation was observed in the Pentacom Farm (PF) and Akuni Papa Farms (APF) compared to those in the Abora (AF) and Akorle Farm 1 (AF1)
This study aimed to investigate the potential of S2 derived vegetation indices (VIs) to obtain information on five main crop phenology stages of mango, namely F/FS, Fruit Development (FRD), M/H, FLU and D
Summary
Introduction iationsMango (Mangifera indica) has been venerated as the ‘King of Fruits’ with a global production of 40 million tons at an average productivity of approximately 8 tons per ha from 5.4 million hectares [1,2]. The global annual economic value of mango exports in 2020 exceeded US$20 billion, with African countries contributing over 10%. 11% of global fresh and processed mango exports respectively [3,4]. The predominant commercial varieties grown globally include Tommy Atkins, Keitt and Kent. These varieties are preferred for their superior agronomic characteristics including low susceptibility to disease and pest infestation, ability to withstand damage during transportation, as well as sensory and visual appeal [5,6]. In Ghana, Keitt and Kent are predominantly grown due to their resistance to disease and availability during periods of high demand from importing nations [7,8]. The mango sector in Ghana is Licensee MDPI, Basel, Switzerland
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
