Obtaining and Validating High-Density Coffee Yield Data
Abstract
:1. Introduction
2. Material and Methods
3. Results and Discussion
3.1. Quality of Yield Data
3.2. Temporal and Spatial Yield Variability
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Companhia Nacional de Abastecimento—(CONAB). Acompanhamento da Safra Brasileira: Café. 2021. Available online: https://www.conab.gov.br/component/k2/item/download/40314_5ca4f5eaec7d5fb8e90ec9645427e205 (accessed on 23 March 2022).
- Companhia Nacional de Abastecimento—(CONAB). Acompanhamento da Safra Brasileira: Café. 2022. Available online: https://www.conab.gov.br/component/k2/item/download/40911_0eac1d762da9a95acc3d8d4bd36d7359 (accessed on 23 March 2022).
- Santinato, F. Inovações Tecnológicas Para Cafeicultura de Precisão. Doctoral Thesis, Faculdade de Ciências Agrárias e Veterinárias—UNESP, Jaboticabal, São Paulo, Brazil, 2016; 125p. [Google Scholar]
- De Camargo, A.P.; de Camargo, M.B.P. Definition and outline for the phenological phases of arabic coffee under Brazilian tropical conditions. Bragantia 2001, 60, 65–68. [Google Scholar] [CrossRef] [Green Version]
- Rena, A.B.; Maestri, M. Fisiologia do cafeeiro. Inf. Agropecuário 1985, 11, 26–40. [Google Scholar]
- Molin, J.P.; Motomiya, A.V.D.A.; Frasson, F.R.; Faulin, G.D.C.; Tosta, W. Test procedure for variable rate fertilizer on coffee. Acta Scientiarum. Agronomy 2010, 32, 569–575. [Google Scholar] [CrossRef] [Green Version]
- Lowenberg-DeBoer, J.; Erickson, B. Setting the record straight on precision agriculture adoption. Agron. J. 2019, 111, 1552–1569. [Google Scholar] [CrossRef] [Green Version]
- Murugan, D.; Garg, A.; Singh, D. Development of an Adaptive Approach for Precision Agriculture Monitoring with Drone and Satellite Data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2017, 10, 5322–5328. [Google Scholar] [CrossRef]
- Molin, J.P.; Faulin, G.D.C. Spatial and temporal variability of soil electrical conductivity related to soil moisture. Sci. Agric. 2013, 70, 1–5. [Google Scholar] [CrossRef]
- Colaço, A.F.; Pagliuca, L.G.; Romanelli, T.L.; Molin, J.P. Economic viability, energy and nutrient balances of site-specific fertilization for citrus. Biosyst. Eng. 2020, 200, 138–156. [Google Scholar] [CrossRef]
- Molin, J.P.; do Amaral, L.R.; Colaço, A. Agricultura de Precisão, 1st ed.; Oficina de Textos: São Paulo, Brazil, 2015; p. 224. [Google Scholar]
- Rosa, V.G.C.; Moreira, M.A.; Rudorff, B.F.T.; Adami, M. Coffee crop yield estimate using an agrometeorological-spectral model. Pesqui. Agropecuária Bras. 2010, 45, 1478–1488. [Google Scholar] [CrossRef] [Green Version]
- Silva, F.M.; Souza, Z.M.; Figueiredo, C.A.P.; Vieira, L.H.S.; Oliveira, E. Spatial variability of chemical attributes and coffee productivity in two harvests. Ciência E Agrotecnologia 2008, 32, 231–241. [Google Scholar] [CrossRef] [Green Version]
- Ferraz, G.A.E.S.; da Silva, F.M.; Carvalho, L.C.C.; Alves, M.D.C.; Franco, B.C. Spatial and temporal variability of phosphorus, potassium and of the yield of a coffee field. Eng. Agric. 2012, 32, 140–150. [Google Scholar] [CrossRef] [Green Version]
- Carvalho, L.C.; Silva, F.M.; Ferraz, G.A.; Stracieri, J.; Ferraz, P.F.; Ambrosano, L. Geostatistical analysis of Arabic coffee yield in two crop seasons. Rev. Bras. Eng. Agrícola E Ambient. 2017, 21, 410–414. [Google Scholar] [CrossRef]
- Ferraz, G.A.E.S.; da Silva, F.M.; de Oliveira, M.S.; Custódio, A.A.P.; Ferraz, P. Spatial variability of plant attributes in a coffee plantation. Rev. Ciênc. Agron. 2017, 48, 81–91. [Google Scholar] [CrossRef] [Green Version]
- Balastreire, L.A.; Schueller, J.K.; Amaral, J.R.; Leal, J.C.G.; Baio, F.H.R. Coffee Yield Mapping. ASAE Annu. Meet. 2002. [Google Scholar] [CrossRef]
- Sartori, S.; Fava, J.F.M.; Domingues, E.L.; Ribeiro Filho, A.C.; Shiraisi, L.E. Mapping the spatial variability of coffee yield with mechanical harvester. In Proceedings of the World Congress on Computers in Agriculture and Natural Resources, Foz do Iguaçu, Paraná, Brazil, 13–15 March 2002; pp. 196–205. [Google Scholar] [CrossRef]
- Angnes, G.; Martello, M.; Faulin, G.D.C.; Molin, J.P.; Romanelli, T.L. Energy efficiency of variable rate fertilizer application in coffee production in Brazil. AgriEngineering 2021, 3, 815–826. [Google Scholar] [CrossRef]
- Faulin, G.C.; Molin, J.P.; Stanislavski, W.M. Sample density and method for obtaining of the correction factor used in the coffee (Coffea arabica L.) yield map. In Proceedings of the Congresso Brasileiro de Agricultura de Precisão—ConBAP, São Pedro, São Paulo, Brazil, 14–17 September 2014. [Google Scholar]
- Bazame, H.C.; Molin, J.P.; Althoff, D.; Martello, M. Detection, classification, and mapping of coffee fruits during harvest with computer vision. Comput. Electron. Agric. 2021, 183, 106066. [Google Scholar] [CrossRef]
- Santana, L.S.; Ferraz, G.A.e.S.; Teodoro, A.J.d.S.; Santana, M.S.; Rossi, G.; Palchetti, E. Advances in Precision Coffee Growing Research: A Bibliometric Review. Agronomy 2021, 11, 1557. [Google Scholar] [CrossRef]
- Alvares, A.C.; Stape, J.L.; Sentelhas, P.C.; Gonçalves, J.L.M.; Sparovek, G. Koppen’s climate classification map for Brazil. Meteorol. Z. 2013, 22, 711–728. [Google Scholar] [CrossRef]
- INMET. Brazil Climate Normals 1991–2020. 2022. Available online: https://portal.inmet.gov.br/normais (accessed on 30 April 2022).
- Maldaner, L.F.; Canata, T.F.; Dias, C.T.S.; Molin, J.P. A statistical approach to static and dynamic tests for Global Navigation Satellite Systems receivers used in agricultural operations. Sci. Agric. 2021, 78. [Google Scholar] [CrossRef]
- Maldaner, L.F.; Molin, J.P. Data processing within rows for sugarcane yield mapping. Sci. Agric. 2020, 77. [Google Scholar] [CrossRef]
- Colaço, A.F.; Molin, J.P.; Rosell-Polo, J.R.; Escolà, A. Spatial variability in commercial orange groves. Part 1: Canopy volume and height. Precis. Agric. 2019, 20, 788–804. [Google Scholar] [CrossRef] [Green Version]
- Warrick, A.W.; Nielsen, D.R. Spatial variability of soil physical properties in the field. In Applications of Soil Physics; Hillel, D., Ed.; Academic Press: New York, NY, USA, 1980; pp. 319–344. [Google Scholar]
- Cambardella, C.A.; Moorman, T.B.; Nowak, J.M.; Parkin, T.B.; Karlen, D.L.; Turco, R.F.; Konopka, A.E. Field-scale variability of soil properties in central Iowa soils. Soil Sci. Soc. Am. J. 1994, 58, 1501–1511. [Google Scholar] [CrossRef]
- Minasny, B.; Mcbratney, A.B.; Whelan, B.M. VESPER Version 1.62; Australian Centre for Precision Agriculture, McMillan Building A05; The University of Sydney: Sydney, Australia, 2005. [Google Scholar]
- Blackmore, S.; Godwin, R.J.; Fountas, S. The analysis of spatial and temporal trends in yield map data over six years. Biosyst. Eng. 2003, 84, 455–466. [Google Scholar] [CrossRef]
- Maldaner, L.F.; Canata, T.F.; Molin, J.P. An approach to sugarcane yield estimation using sensors in the harvester and zigbee technology. Sugar Tech 2021. [Google Scholar] [CrossRef]
- Gaspari-Pezzopane, C.D.; Medina Filho, H.P.; Bordignon, R.; Siqueira, W.J.; Ambrósio, L.A.; Mazzafera, P. Environmental influences on the intrinsic outturn of coffee. Bragantia 2005, 64, 39–50. [Google Scholar] [CrossRef]
- Silva, J.S.; Moreli, A.P.; Donzeles, S.M.L.; Soares, S.F.; Vitor, D.G. Harvesting, Drying and Storage of Coffee. In Food Engineering Series; Springer: Berlin/Heidelberg, Germany, 2021; pp. 1–64. [Google Scholar] [CrossRef]
- Pereira, S.O.; Bartholo, G.F.; Baliza, D.P.; Sogreira, F.M.; Guimarães, R.J. Growth, productivity and bienniality of coffee plants according to cultivation spacing. Pesqui. Agropecuária Bras. 2011, 46, 152–160. [Google Scholar] [CrossRef]
- Valadares, S.V.; Neves, J.C.L.; Rosa, G.N.G.P.; Martinez, H.E.P.; Venegas, V.H.A.; Lima, P.C. Productivity and biennial production of dense coffee plantations under diferente levels of N and K. Pesqui. Agropecuária Bras. 2013, 98, 296–303. [Google Scholar] [CrossRef] [Green Version]
- Fialho, C.M.T.; Silva, G.R.; Freitas, M.A.M.; França, A.C.; Mello, C.A.D.; Silva, A.A. Competition of weeds with coffee plants, in two times of infestation. Planta Daninha 2011, 28, 969–978. [Google Scholar] [CrossRef]
- Carvalho, A.M.; Mendes, A.N.; Botelho, C.E.; Oliveira, A.C.; Rezende, J.C.; Rezende, R.M. Agronomic performance of coffee cultivars resistant to coffee rust in Minas Gerais state, Brazil. Bragantia 2012, 71, 481–487. [Google Scholar] [CrossRef] [Green Version]
- Lopes, P.R.; Araújo, K.C.S.; Ferraz, J.M.G.; Lopes, I.M.; Fernandes, L.G. Producing agroecological coffee in Southern Minas Gerais: Alternative systems forintensive production of agrochemicals. Rev. Bras. Agroecol. 2012, 7, 25–38. [Google Scholar]
- Wadt, P.G.S.; Dias, J.R.M. Regional and inter-regional DRIS norms for nutritional evaluation of Conilon coffee. Pesqui. Agropecuária Bras. 2012, 47, 822–830. [Google Scholar] [CrossRef] [Green Version]
- Scalco, M.S.; Alvarenga, L.A.; Guimarães, R.J.; Dominghetti, A.W.; Colombo, A.; Assis, G.A.; Abreu, G.F. Leaf contents of phosphorus and zinc, productivity, and growth of irrigated coffee. Pesquisa Agropecuária Brasileira 2014, 49, 95–101. [Google Scholar] [CrossRef] [Green Version]
- Matiello, J.B.; Garcia, A.W.R.; Almeida, S.R. Adubação Racional na Lavoura Cafeeira, 1st ed.; Bom Pastor: Varginha, Brazil, 2008; p. 114. [Google Scholar]
Coffee Sample Weight (g) | Dry Coffee Humidity (%) | Processed Coffee Weight—CF (g L−1) | Unripe Coffee Fruits (%) | Ripe Coffee Fruits (%) | Overripe Coffee Fruits (%) | |
---|---|---|---|---|---|---|
2019 (n = 23) | 470.0 | 11.9 | 159.5 | 6.1 | 7.5 | 86.4 |
SD | 39.2 | 0.26 | 14.8 | 4.4 | 3.9 | 8.3 |
CV (%) | 8.3 | 2.2 | 9.3 | 72.2 | 51.7 | 9.4 |
2020 (n = 44) | 677.5 | 12.0 | 127.7 | 22.2 | 49.1 | 28.7 |
SD | 22.9 | 0.1 | 9.4 | 8.6 | 11.2 | 7.6 |
CV (%) | 3.4 | 1.2 | 7.4 | 39.0 | 22.9 | 26.5 |
2021 (n = 31) | 492.5 | 12.0 | 143.5 | 7.4 | 8.5 | 84.1 |
SD | 33.3 | 0.2 | 12.5 | 3.8 | 4.2 | 8.4 |
CV (%) | 6.8 | 1.5 | 8.7 | 51.8 | 48.7 | 10.1 |
Year | Dataset | n | n ha−1 | Mean | Min | Max | SD | CV (%) |
---|---|---|---|---|---|---|---|---|
Mg ha−1 | ||||||||
2019 | Original | 6398 | 624.8 | 1.90 | 0 | 303.88 | 4.96 | 260.88 |
Filtered | 5479 | 535.0 | 1.29 | 0.12 | 2.68 | 0.57 | 44.35 | |
2020 | Original | 8242 | 804.8 | 2.20 | 0.00 | 164.63 | 3.90 | 176.94 |
Filtered | 7789 | 760.6 | 2.03 | 0.09 | 4.06 | 0.88 | 43.43 | |
2021 | Original | 7748 | 756.6 | 1.54 | 0.00 | 7.18 | 0.89 | 57.90 |
Filtered | 6913 | 675.1 | 1.44 | 0.13 | 2.90 | 0.71 | 49.04 |
Year | Model | Range | Sill 1 | Nugget 2 | RSME (Mg ha−1) | SDI |
---|---|---|---|---|---|---|
2019 | Exponential | 59.9 | 0.343 | 0.214 | 0.022 | moderate |
2020 | Gaussian | 316.4 | 1.031 | 0.563 | 0.011 | moderate |
2021 | Gaussian | 202.2 | 0.596 | 0.345 | 0.016 | moderate |
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Martello, M.; Molin, J.P.; Bazame, H.C. Obtaining and Validating High-Density Coffee Yield Data. Horticulturae 2022, 8, 421. https://doi.org/10.3390/horticulturae8050421
Martello M, Molin JP, Bazame HC. Obtaining and Validating High-Density Coffee Yield Data. Horticulturae. 2022; 8(5):421. https://doi.org/10.3390/horticulturae8050421
Chicago/Turabian StyleMartello, Maurício, José Paulo Molin, and Helizani Couto Bazame. 2022. "Obtaining and Validating High-Density Coffee Yield Data" Horticulturae 8, no. 5: 421. https://doi.org/10.3390/horticulturae8050421