Abstract
As the human population is growing worldwide, the food demand is sharply increasing. Following this assumption, strategies to enhance the food production are being explored, namely, smart farming, for monitoring crops during the production cycle. In this study, a vineyard of Vitis vinifera cv. Moscatel located in Palmela (N 38°35′47.113′′ O 8°40′46.651) was submitted to a Zn biofortification workflow, through foliar application of zinc oxide (ZnO) or zinc sulfate (ZnSO4) (at a concentration of 60% and 90%—900 g·ha−1 and 1350 g·ha−1, respectively). The field morphology and vigor of the vineyard was performed through Unmanned Aerial Vehicles (UAVs) images (assessed with altimetric measurement sensors), synchronized by GPS. Drainage capacity and slopes showed one-third of the field with reduced surface drainage and a maximum variation of 0.80 m between the extremes (almost flat), respectively. The NDVI (Normalized Difference Vegetation Index) values reflected a greater vigor in treated grapes with treatment SZn90 showing a higher value. These data were interpolated with mineral content, monitored with atomic absorption analysis (showing a 1.3-fold increase for the biofortification index). It was concluded that the used technologies furnishes specific target information in real time about the crops production.
1. Introduction
By 2050, due to the increase in the world population, to avoid hunger, food production must significantly increase [1]. In addition, to ensure safety, food also must have high quality, specifically at a prophylactic level, providing the necessary nutrients, since it is expected that their deficiency might affect the health of more than two billion people worldwide [2,3]. In this context, some alternatives are being suggested, namely, agronomic biofortification to increase target nutrients in edible plant tissues. This alternative can be accomplished through soil and foliar application, and this latter application seems to allow plants to assimilate micronutrients with high efficiency, as it does not depend upon root-to-shoot translocation [4,5]. Beyond the main aims of agronomic biofortification, some evidence showed that yield and nutritional quality increases with this practice [6].
Zinc deficiency continues to affect around three billion people worldwide, leading to the appearance of neurological disorders, autoimmune, degenerative diseases related to age, Wilson’s disease, cardiovascular problems, and diabetes mellitus, among other conditions [7].
To address this increase in food demand, other factors also may be considered, such as climate change, the limited availability of arable lands, as well as the growing necessity for freshwater, making it indispensable to resort to new technologies such as Unmanned Aerial Vehicle (UAVs). This technology can carry different types of cameras, including multispectral cameras that allow users to obtain vegetation indices translated by Normalized Difference Vegetation Index (NDVI), providing us with information about biomass levels and stress conditions such as crop diseases, water stress, pest infestations, nutrient deficiencies and other factors that affect crop productivity [8]. Regarding other advantages of UAVs, acquirement of field data its carried out more easily, and in a fast and cost-effective way [9]. Following this assumption, the present study used multispectral images from UAVs to monitor Zn biofortified vineyards, once this fruit plays a predominant role in the development of the world and, according to the Food and Agriculture Organization (FAO), covers 75.866 square kilometers worldwide, additionally helping in some health problems [10].
2. Materials and Methods
2.1. Experimental Field
Biofortification with Zn was performed in a Vitis vinifera L. variety Moscatel field located in Lau Novo, Palmela, Portugal (38°35′47.113′′ O 8°40′46.651′′ W), under irrigation conditions. Foliar application with zinc sulfate (ZnSO4) and zinc oxide (ZnO), at concentrations of 0%, 60% and 90% (0, 900 and 1350 g ha−1) was performed between 29 June and 19 July, with harvest being carried out on 10 September 2019.
2.2. Field Morphology and Vigor of the Vine
Flight planning and execution was performed to obtain images with a high resolution RGB (20 Mp) and Parrot Sequoia Plus installed multispectral cameras in an unmanned aerial vehicle (UAV), model DJI Phantom 4 Pro +. The multispectral camera had four band sensors: Green (550 BP 40), Red (660 BP 40), Red Edge (735 BP 10) and Near Infrared (790 BP 40). After acquisition of images, an orthophotomap was processed and, using the altimetry data, the digital model of the terrain (MDT) was obtained, as well as the surface drainage model (using the ARCGIS and Agisoft Photoscan software), creating the vegetation index maps that reflect the vigor of the plants (NDVI) [11].
2.3. Quantification of Zn in Grapes
At harvest, grapes were cut, dried (until constant weight, at 60 °C) and subjected to an acid digestion procedure with a mixture of HNO3-HCL (4:1), according to [12]. Then, the samples were filtrated, and Zn contents were measured using an atomic absorption spectrophotometer model Perkin Elmer AAnalyst 200, fitted with a deuterium background corrector, and the AA WinLab software program.
2.4. Statistical Analyses
Data were statistically analyzed using a One-Way ANOVA (p ≤ 0.05) to access differences, followed by a Tukey’s test for mean comparison (95% confidence level).
3. Results
The slopes of the experimental field were determined, being found a moderate surface drainage prevailing, with 63.86% of infiltration capacity (Table 1).
Table 1.
Slope characterization before foliar application of Lau Novo field.
Zn contents in treated grapes showed, relatively to the control, 1.2–1.3-fold increases in the higher concentrations of treatments, OZn90 and SZn90, respectively (Table 2).
Table 2.
Average content ± S.E. (n = 3) of Zn in fruits at harvest of Vitis vinifera L. variety Moscatel. Letter a indicate the absence of significant differences among treatments (p ≤ 0.05). Treatments OZn60, OZn90, SZn60 e SZn90 indicate the following concentrations for zinc oxide (ZnO) or zinc sulfate (ZnSO4): 0%, 60%, 90%. (i.e., 0, 900 e 1350 g ha−1).
After the fourth treatment, Moscatel-treated grapes revealed a positive response, showing higher NDVI values than the control, with treatments by SZn displaying the highest foliage densities (Table 3; Figure 1).
Table 3.
Average vigor ± S.E. (n = 3) in fruits of Vitis vinifera L. variety Moscatel after the 4th application. Letter indicates the absence of significant differences among treatments (p ≤ 0.05). Treatments OZn60, OZn90, SZn60 e SZn90 indicate the following concentrations for zinc oxide (ZnO) or zinc sulfate (ZnSO4): 0%, 60%, 90%. (i.e., 0, 900 e 1350 g ha−1).
Figure 1.
NDVI index of Lau Novo field after the 4th application (1—Control; 2—Treatment ZnSO4 60%; 3—Treatment ZnSO4 90%; 4—Treatment ZnO 60%; 5—Treatment ZnO 90%).
4. Discussion
Climate changes are a concern among winemakers, as grapes are one of the fruit crops most sensitive to severe drought conditions and water shortage [13]. Water shortage is considered one of the most common causes of stress conditions in grapes, leading to yield and quality losses. Under these conditions, decreases in relative water content (RWC), leaf dry matter, chlorophyll (Chl) content, net photosynthetic rate (PN), ribulose-1,5-bisphosphate carboxylase (RuBPC) and nitrate reductase (NR) activities of Riesling grapevines can develop [14].
The Portuguese climate is becoming dryer, and it is indispensable to develop adaptation strategies to face water scarcity. In this framework, a smart irrigation, optimizing grape composition and providing a balanced solution between environment and plant requirements can become a relevant option. Indeed, with higher dryness, and without irrigation, yield reductions were already found in Portugal (i.e., Alentejo, Lisboa, Minho and Terras-da-Beira) [15]. Moreover, an efficient irrigation showed a diminishing volume of water applied to crops fields by 30–70% and an increase in crop yields by 20–90% [16]. According to our data, the experimental field with Moscatel grapes showed a moderate capacity of surface drainage in 63.86% of the area (Table 1), which determines a moderate infiltration capacity, contributing to the groundwater recharge (i.e., water available for plant growth) [17]. Additionally, as this field is being irrigated, the potential hydric stress derived by rain scarcity, observed in recent decades, is being mitigated.
In Turkey, fertilization with Zn was carried out by leaves spraying, which determined increases in productivity of about 25% in cereals, with the concurrent augmentation of Zn contents in the edible parts of the plants [18]. Our study also showed an increase in Zn content in grapes sprayed with ZnO and ZnSO4 (Table 2). In addition, following [19,20], Zn biofortification through foliar application, also affected yield parameters. Indeed, through vegetation indices, namely NDVI, is possible to access health conditions, providing information of photosynthetic capacity, which can be correlated with plant vigor and vegetation abundance, health and growth [21,22]. This index has values normalized between +1 and −1, with higher values indicating a denser vegetation [22]. In fact, our data showed higher values for NDVI in the vines fertilized with ZnSO4 and ZnO, relative to the control, but treatments with ZnSO4 triggered a higher vigor (Table 3).
5. Conclusions
Through images obtained with cameras attached to UAVs, it is possible to obtain information about morphology of the field and potential limiting conditions for vines development. Using the Moscatel field as a test system, important characteristics—namely, moderate infiltration capacity and the use of irrigation, enabling vines to have more resistance to hydric stress—were optimized. The obtained images further provided information regarding the crops’ state, detecting a positive response to Zn fertilization with an increase in the Zn content and vigor of vines subjected to ZnO and ZnSO4.
Supplementary Materials
The following are available online at https://www.mdpi.com/article/10.3390/IECAG2021-09663/s1.
Author Contributions
Conceptualization, P.S.C., J.C.R. and F.C.L.; methodology, M.G.B., J.C.K. and F.C.L.; software, M.G.B.; formal analysis, D.D., C.C.P., A.R.F.C., A.C.M., I.C.L., J.C. and J.C.K.; resources, M.M.S., M.S., F.H.R., M.F.P., P.L., M.G.B., J.C.K., J.A.A. and F.C.L.; writing—original draft preparation, D.D.; writing—review and editing, D.D. and F.C.L.; supervision, F.C.L.; project administration, F.C.L.; funding acquisition, F.C.L. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by PDR2020, grant number 101-030727.
Acknowledgments
The authors thanks to Engenier Luís Silva (Adega Cooperativa de Palmela- Casa Agrícola Nunes Oliveira da Silva Lda) for technical assistance. We also thanks to the Research centres (GeoBioTec) UIDB/04035/2020 and (CEF) UIDB/00239/2020 for support facilities.
Conflicts of Interest
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
References
- Berners-Lee, M.; Kennelly, C.; Watson, R.; Hewitt, C.N. Current global food production is sufficient to meet human nutritional needs in 2050 provided there is radical societal adaptation. Elem. Sci. Anth. 2018, 6–52. [Google Scholar] [CrossRef]
- Lowe, N.M.; Zaman, M.; Moran, V.H.; Ohly, H.; Sinclair, J.; Fatima, S.; Broadley, M.R.; Joy, E.J.M.; Mahboob, U.; Lark, M.; et al. Biofortification of wheat with zinc for eliminating deficiency in Pakistan: Study protocol for a cluster-randomised, double-blind, controlled effectiveness study (BIZIFED2). BMJ 2020, 10. [Google Scholar] [CrossRef] [PubMed]
- Wang, M.X.; Koh, J.; Pang, J. Association between micronutrient deficiency and acute respiratory infections in healthy adults: A systematic review of observational studies. Nutr. J. 2018, 18, 80. [Google Scholar] [CrossRef] [Green Version]
- Di Gioia, F.; Petropoulos, S.A.; Ozores-Hampton, M.; Morgan, K.; Rosskopf, E.N. Zinc and iron agronomic biofortification of Brassicaceae microgreens. J. Agron. 2019, 9, 677. [Google Scholar] [CrossRef] [Green Version]
- Zhao, H.; Xie, X.; Read, P.; Loseke, B.; Gamet, S.; Li, W.; Xu, C. Biofortification with selenium and lithium improves nutraceutical properties of major winery grapes in the Midwestern United States. J. Food Sci. Technol. 2020, 56, 825–837. [Google Scholar] [CrossRef]
- De Valença, A.W.; Bake, A.; Brouwer, I.D.; Giller, K.E. Agronomic biofortification of crops to fight hidden hunger in sub-Saharan Africa. Glob. Food Sec. 2017, 12, 8–14. [Google Scholar] [CrossRef]
- Chasapis, C.T.; Loutsidou, A.C.; Spiliopoulou, C.A.; Srefanidou, M.E. Zinc and human health: An update. Arch. Toxicol. 2011, 86, 521–534. [Google Scholar] [CrossRef] [PubMed]
- Radoglou-Grammatikis, P.; Sarigiannidis, P.; Lagkas, T.; Moscholios, I. A Compilation of UAV applications for precision agriculture. Comput. Netw. 2020, 172, 107148. [Google Scholar] [CrossRef]
- Tsouros, D.C.; Bibi, S.; Sarigiannidis, P.G. A Review on UAV-based applications for precision agriculture. Information 2019, 10, 349. [Google Scholar] [CrossRef] [Green Version]
- Khan, N.; Fahad, S.; Naushad, M.; Faisal, S. Grape production critical review in the world. SSRN 2020. [Google Scholar] [CrossRef]
- Coelho, A.R.F.; Lidon, F.C.; Pessoa, C.C.; Marques, A.C.; Luís, I.C.; Caleiro, J.C.; Simões, M.; Kullberg, J.; Legoinha, P.; Brito, G.; et al. Can foliar pulverization with CaCl2 and Ca(NO3)2 trigger Ca enrichment in Solanum Tuberosum L. tubers? Plants 2021, 10, 245. [Google Scholar] [CrossRef]
- Pelica, J.; Barbosa, S.; Lidon, F.; Pessoa, M.F.; Reboredo, F.; Calvão, T. The paradigm of high concentration 252 of metals of natural or anthropogenic origin in soils—The case of Neves-Corvo mine area (Southern 253 Portugal). J. Geochem. Explor. 2018, 186, 12–23. [Google Scholar] [CrossRef]
- Zombardo, A.; Mica, E.; Puccioni, S.; Perria, R.; Valentini, P.; Mattii, G.B.; Cattivelli, L.; Storchi, P. Berry Quality of grapevine under water stress as affected by rootstock–scion interactions through gene expression regulation. J. Agron. 2020, 10, 680. [Google Scholar] [CrossRef]
- Ju, Y.; Yue, X.; Zhao, X.; Zhao, H.; Fang, Y. Physiological, micro-morphological and metabolomic analysis of grapevine (Vitis vinifera L.) leaf of plants under water stress. Plant Physiol. Biochem. 2018, 130, 501–510. [Google Scholar] [CrossRef] [PubMed]
- Fraga, H.; García de Cortázar Atauri, I.; Santos, J. Viticultural irrigation demands under climate change scenarios in Portugal. Agric. Water Manag. 2018, 196, 66–74. [Google Scholar] [CrossRef]
- Saccon, P. Water for agriculture, irrigation management. Agric. Ecosyst. Environ. Appl. Soil Ecol. 2018, 123, 793–796. [Google Scholar] [CrossRef]
- Harden, C.P. Infiltration. In International Encyclopedia of Geography: People, the Earth, Environment and Technology; Wiley: Hoboken, NJ, USA, 2017; pp. 1–4. [Google Scholar] [CrossRef]
- Maqbool, A.; Abrar, M.; Bakhsh, A.; Çalışkan, S.; Khan, H.Z.; Aslam, M.; Aksoy, E. Biofortification under climate change: The fight between quality and quantity. In Environment, Climate, Plant and Vegetation Growth; Springer: Berlin, Germany, 2020; pp. 173–227. [Google Scholar] [CrossRef]
- Bhatt, R.; Hossain, A.; Sharma, P. Zinc biofortification as an innovative technology to alleviate the zinc deficiency in human health: A review. Open Agric. 2020, 5, 176–187. [Google Scholar] [CrossRef]
- Shivay, Y.S.; Prasad, R.; Rahal, A. Relative efficiency of zinc oxide and zinc sulphate-enriched urea for 229 spring wheat. Nutr. Cycl. Agroecosyst. 2008, 82, 259–264. [Google Scholar] [CrossRef]
- Easterday, K.; Kislik, C.; Dawson, T.; Hogan, S.; Kelly, M. Remotely sensed water limitation in vegetation: Insights from an experiment with unmanned aerial vehicles (UAVs). Remote Sens. 2019, 11, 1853. [Google Scholar] [CrossRef] [Green Version]
- Reddy, D.S.; Prasad, P.R.C. Prediction of vegetation dynamics using NDVI time series data and LSTM. MESE 2018, 4, 409–419. [Google Scholar] [CrossRef]
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