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Monitoring a zinc biofortification workflow in an experimental field of Triticum aestivum L. applying smart farming technology
* 1, 2 , 3, 4 , 3, 4 , 3, 4 , 3, 4 , 3, 4 , 3, 4 , 4, 5 , 5 , 3, 4 , 4, 6 , 3, 4 , 4, 7 , 3, 4 , 3, 4 , 4, 8 , 4, 8 , 4, 9 , 3, 4 , 3, 4
1  Earth Sciences Department, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Campus Caparica, 2829-516 Caparica, Portugal
2  GeoBioTec Research Center, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Campus Caparica, 2829-516 Caparica, Portugal
3  Earth Sciences Department, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
4  GeoBioTec Research Center, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal
5  Escola Superior Agrária, Instituto Politécnico de Beja, Beja, Portugal
6  INIAV, Instituto Nacional de Investigação Agrária e Veterinária, Elvas, Portugal
7  ESEAG-COFAC, Lisboa, Portugal
8  INIAV, Instituto Nacional de Investigação Agrária e Veterinária, Oeiras, Portugal
9  PlantStress & Biodiversity Lab, Centro de Estudos Florestais (CEF), Instituto Superior Agronomia (ISA), Universidade de Lisboa, Oeiras, Portugal

Abstract:

The strong increase of the human population worldwide is demanding a food production, meeting quality standards. In this context, the agronomic biofortification with Zn is being widely used in staple food crops as a strategy to surpass micronutrient deficiencies. Conversely, as bread wheat is one of the most produced and consumed cereal, this staple food biofortification can be an opportunity to create an added value product. In this context, a workflow for Zn biofortification of Triticum aestivum L. (cvs Paiva and Roxo) crops, was implemented in an experimental field located in Beja, Portugal and smart farming techniques were used. Accordingly, images were collected by an Unmanned Aerial Vehicle before Zn foliar applications. Grain yield, test weight and thousand kernel weight were analyzed (post-harvest), after two foliar applications of ZnSO4, in three concentrations (control – 0, 8.1 and 18.2 kg.ha-1), at booting and heading stages. In general, when applying higher concentrations of foliar Zn, grain yield, test weight and thousand kernel weight decreased, slightly, in which Paiva presented higher values compared to Roxo. Nevertheless, the Normalized Difference Vegetation Index (NDVI) did not reveal a direct correlation between its higher values and the increase of grain yield. Yet, it was concluded that using drones is of utmost importance to decide whether an experimental field is qualified to implement a biofortification workflow.

Keywords: Agronomic biofortification; Bread wheat; Grain yield; NDVI; Test weight; Thousand kernel weight.
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