A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping
The development of high-throughput field phenotyping, which uses modern detection technologies and advanced data processing algorithms, could increase productivity and make in-field phenotypic evaluation more efficient by collecting large amounts of data with no or minimal human assistance. Moreover...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/4/2436 |
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| author | Francesca Antonucci Corrado Costa Simone Figorilli Luciano Ortenzi Rossella Manganiello Enrico Santangelo Łukasz Gierz Federico Pallottino |
| author_facet | Francesca Antonucci Corrado Costa Simone Figorilli Luciano Ortenzi Rossella Manganiello Enrico Santangelo Łukasz Gierz Federico Pallottino |
| author_sort | Francesca Antonucci |
| collection | DOAJ |
| description | The development of high-throughput field phenotyping, which uses modern detection technologies and advanced data processing algorithms, could increase productivity and make in-field phenotypic evaluation more efficient by collecting large amounts of data with no or minimal human assistance. Moreover, high-throughput plant phenotyping systems are also very effective in selecting crops and characterizing germplasm for drought tolerance and disease resistance by using spectral sensor data in combination with machine learning. In this study, an affordable high-throughput phenotyping platform (phenomobile) aims to obtain solutions at reasonable prices for all the components that make up it and the many data collected. The goal of the practical innovation in field phenotyping is to implement high-performance precision phenotyping under real-world conditions at accessible costs, making real-time data analysis techniques more user-friendly. This work aims to test the ability of a phenotyping prototype system constituted by an electric phenomobile integrated with a MAIA multispectral camera for real in-field plant characterization. This was done by acquiring spectral signatures of F1 hybrid Elisir (Olter Sementi) tomato plants and calculating their vegetation indexes. This work allowed to collect, in real time, a great number of field data about, for example, the morphological traits of crops, plant physiological activities, plant diseases, fruit maturity, and plant water stress. |
| first_indexed | 2024-03-11T09:11:54Z |
| format | Article |
| id | doaj.art-4d575731da2b420681b737604855e8bb |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T09:11:54Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4d575731da2b420681b737604855e8bb2023-11-16T18:55:42ZengMDPI AGApplied Sciences2076-34172023-02-01134243610.3390/app13042436A Low-Cost Sensorized Vehicle for In-Field Crop PhenotypingFrancesca Antonucci0Corrado Costa1Simone Figorilli2Luciano Ortenzi3Rossella Manganiello4Enrico Santangelo5Łukasz Gierz6Federico Pallottino7Consiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, ItalyConsiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, ItalyInstitute of Machine Design, Faculty of Mechanical Engineering, Poznan University of Technology, 60-965 Poznan, PolandConsiglio per la Ricerca in Agricoltura e L’analisi Dell’economia Agraria (CREA), Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Via della Pascolare 16, 00015 Monterotondo, ItalyThe development of high-throughput field phenotyping, which uses modern detection technologies and advanced data processing algorithms, could increase productivity and make in-field phenotypic evaluation more efficient by collecting large amounts of data with no or minimal human assistance. Moreover, high-throughput plant phenotyping systems are also very effective in selecting crops and characterizing germplasm for drought tolerance and disease resistance by using spectral sensor data in combination with machine learning. In this study, an affordable high-throughput phenotyping platform (phenomobile) aims to obtain solutions at reasonable prices for all the components that make up it and the many data collected. The goal of the practical innovation in field phenotyping is to implement high-performance precision phenotyping under real-world conditions at accessible costs, making real-time data analysis techniques more user-friendly. This work aims to test the ability of a phenotyping prototype system constituted by an electric phenomobile integrated with a MAIA multispectral camera for real in-field plant characterization. This was done by acquiring spectral signatures of F1 hybrid Elisir (Olter Sementi) tomato plants and calculating their vegetation indexes. This work allowed to collect, in real time, a great number of field data about, for example, the morphological traits of crops, plant physiological activities, plant diseases, fruit maturity, and plant water stress.https://www.mdpi.com/2076-3417/13/4/2436phenomobilemultispectral camerasensorsreal-time analysisproximal sensing |
| spellingShingle | Francesca Antonucci Corrado Costa Simone Figorilli Luciano Ortenzi Rossella Manganiello Enrico Santangelo Łukasz Gierz Federico Pallottino A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping Applied Sciences phenomobile multispectral camera sensors real-time analysis proximal sensing |
| title | A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping |
| title_full | A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping |
| title_fullStr | A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping |
| title_full_unstemmed | A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping |
| title_short | A Low-Cost Sensorized Vehicle for In-Field Crop Phenotyping |
| title_sort | low cost sensorized vehicle for in field crop phenotyping |
| topic | phenomobile multispectral camera sensors real-time analysis proximal sensing |
| url | https://www.mdpi.com/2076-3417/13/4/2436 |
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