Active vs. Passive Thermal Imaging for Helping the Early Detection of Soil-Borne Rot Diseases on Wild Rocket [Diplotaxis tenuifolia (L.) D.C.]
Abstract
:1. Introduction
2. Results
2.1. Infrared Imaging: Active Approach
2.2. Infrared Imaging: Passive Approach
2.3. Monitoring through Visible Inspection
2.4. Comparison of MWIR and LWIR Analyses
3. Discussion
4. Materials and Methods
4.1. Plant Growth and Inoculation Methods
4.2. Infrared Imaging Measurements
4.2.1. Methods: Active and Passive Thermographic Approaches
4.2.2. Set-Up and Instrumentation
4.3. Statistical Analysis and ΔT Parameters
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- Takahama, M.; Kawagishi, K.; Sugawara, A.; Araki, K.; Munekata, S.; Nicola, S.; Araki, H. Classification and screening of baby-leaf vegetables on the basis of their yield, external appearance and internal quality. Hort. J. 2019, 88, 387–400. [Google Scholar] [CrossRef] [Green Version]
- Jasper, J.; Elmore, J.S.; Wagstaff, C. Determining the quality of leafy salads: Past, present and future. Postharvest Biol. Technol. 2021, 180, 111630. [Google Scholar] [CrossRef]
- Pinotti, L.; Manoni, M.; Fumagalli, F.; Rovere, N.; Luciano, A.; Ottoboni, M.; Ferrari, L.; Cheli, F.; Djuragic, O. Reduce, reuse, recycle for food waste: A second life for fresh-cut leafy salad crops in animal diets. Animals 2020, 10, 1082. [Google Scholar] [CrossRef]
- Cricca, L. Rucola, Sul Podio Del Made in Italy. 2019. Available online: https://agronotizie.imagelinenetwork.com/agronomia/2019/05/23/rucola-sul-podio-del-made-in-italy/63080 (accessed on 28 January 2023).
- Caruso, G.; Parrella, G.; Giorgini, M.; Nicoletti, R. Crop systems, quality and protection of Diplotaxis tenuifolia. Agriculture 2018, 8, 55. [Google Scholar] [CrossRef] [Green Version]
- Bonasia, A.; Lazzizera, C.; Elia, A.; Conversa, G. Nutritional, biophysical and physiological characteristics of wild rocket genotypes as affected by soilless cultivation system, salinity level of nutrient solution and growing period. Front. Plant Sci. 2017, 8, 300. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Galieni, A.; Nicastro, N.; Pentangelo, A.; Platani, C.; Cardi, T.; Pane, C. Surveying soil-borne disease development on wild rocket salad crop by proximal sensing based on high-resolution hyperspectral features. Sci. Rep. 2022, 12, 5098. [Google Scholar] [CrossRef] [PubMed]
- Nicoletti, R.; Raimo, F.; Miccio, G. First report of Rhizoctonia solani on Diplotaxis tenuifolia in Italy. Plant Pathol. 2004, 53, 811. [Google Scholar] [CrossRef]
- Garibaldi, A.; Minuto, A.; Gullino, M.L. First report of Sclerotinia stem rot and watery soft rot caused by Sclerotinia sclerotiorum on sand rocket (Diplotaxis tenuifolia) in Italy. Plant Dis. 2005, 89, 11. [Google Scholar] [CrossRef]
- Pane, C.; Francese, G.; Raimo, F.; Mennella, G.; Zaccardelli, M. Activity of foliar extracts of cultivated eggplants against Sclerotinia lettuce drop disease and their phytochemical profiles. Eur. J. Plant Pathol. 2017, 148, 687–697. [Google Scholar] [CrossRef]
- Pane, C.; Caputo, M.; Francese, G.; Manganiello, G.; Lo Scalzo, R.; Mennella, G.; Zaccardelli, M. Managing Rhizoctonia damping-off of rocket (Eruca sativa) seedlings by drench application of bioactive potato leaf phytochemical extracts. Biology 2020, 9, 270. [Google Scholar] [CrossRef]
- Zaccardelli, M.; Sorrentino, R.; Caputo, M.; Scotti, R.; De Falco, E.; Pane, C. Stepwise-selected Bacillus amyloliquefaciens and B. subtilis strains from composted aromatic plant waste able to control soil-borne diseases. Agriculture 2020, 10, 30. [Google Scholar] [CrossRef] [Green Version]
- Ishimwe, R.; Abutaleb, K.; Ahmed, F. Applications of thermal imaging in agriculture—A review. Adv. Remote Sens. 2014, 3, 128–140. [Google Scholar] [CrossRef] [Green Version]
- Capraro, A.C.W.; Steppe, K.; Van Asten, P.J.A.; Laderach, P.; Jassogne, L.T.P.; Grab, S.W. Application of thermography for monitoring stomatal conductance of Coffea Arabica under different shading systems. Sci. Total Environ. 2017, 609, 755–763. [Google Scholar] [CrossRef] [PubMed]
- Vadivambal, R.; Jayas, D.S. Applications of thermal imaging in agriculture and food industry—A review. Food Bioprocess Technol. 2011, 4, 186–199. [Google Scholar] [CrossRef]
- Grant, O.M.; Chaves, M.M.; Jones, H.G. Optimizing thermal imaging as a technique for detecting stomatal closure induced by drought stress under greenhouse conditions. Physiol. Plant. 2006, 127, 507–518. [Google Scholar] [CrossRef]
- Guilioni, L.; Jones, H.G.; Leinonen, I.; Lhomme, J.P. On the relationships between stomatal resistance and leaf temperatures in thermography. Agric. For. Meteorol. 2008, 148, 1908–1912. [Google Scholar] [CrossRef]
- Blonquist, J.M., Jr.; Norman, J.M.; Bugbee, B. Automated measurement of canopy stomatal conductance based on infrared temperature. Agric. For. Meteorol. 2009, 149, 1931–1945. [Google Scholar] [CrossRef]
- Garbea, C.S.; Schurrb, U.; Jähnea, B. Thermographic measurements on plant leaves. Thermosense XXIV 2002, 4710, 1–9. [Google Scholar]
- Bajons, P.; Klinger, G.; Schlosser, V. Determination of stomatal conductance by means of infrared thermography. Infrared Phys. Technol. 2005, 46, 429–439. [Google Scholar] [CrossRef]
- Rippa, M.; Ambrosone, A.; Leone, A.; Mormile, P. Active thermography for real time monitoring of UV-B plant interactions. J. Photochem. Photobiol. B Biol. 2020, 208, 111900. [Google Scholar] [CrossRef]
- Rippa, M.; Battaglia, V.; Cermola, M.; Sicignano, M.; Lahoz, E.; Mormile, P. Monitoring of the copper persistence on plant leaves using pulsed thermography. Environ. Monit. Assess. 2022, 194, 60. [Google Scholar] [CrossRef] [PubMed]
- Bonanomi, G.; Battista Chirico, G.; Palladino, M.; Gaglione, S.A.; Crispo, D.G.; Lazzaro, U.; Sica, B.; Cesarano, G.; Tushar, F.I.; Sarker, C.; et al. Combined application of photo-selective mulching films and beneficial microbes affects crop yield and irrigation water productivity in intensive farming systems. Agric. Water Manag. 2017, 184, 104–113. [Google Scholar] [CrossRef]
- Pineda, M.; Barón, M.; Pérez-Bueno, M.L. Thermal imaging for plant stress detection and phenotyping. Remote Sens. 2021, 13, 68. [Google Scholar] [CrossRef]
- Shakeel, Q.; Bajwa, R.T.; Rashid, I.; Aslam, H.M.U.; Iftikhar, Y.; Mubeen, M.; Li, G.; Wu, M. Concept and application of infrared thermography for plant disease measurement. In Trends in Plant Disease Assessment; Ul Haq, I., Ijaz, S., Eds.; Springer: Singapore, 2022; Volume 7, pp. 109–125. [Google Scholar]
- Gonçalves, B.J.; Giarola, T.M.; Pereira, D.F.; Vilas Boas, E.V.; de Resende, J.V. Using infrared thermography to evaluate the injuries of cold-stored guava. J. Food Sci. Technol. 2016, 53, 1063–1070. [Google Scholar] [CrossRef]
- Yuxuan, W.; Zia-Khan, S.; Owusu-Adu, S.; Miedaner, T.; Müller, J. Early detection of Zymoseptoria tritici in winter wheat by infrared thermography. Agriculture 2019, 9, 139. [Google Scholar]
- Wang, L.; Poque, S.; Valkonen, J.P. Phenotyping viral infection in sweetpotato using a high-throughput chlorophyll fluorescence and thermal imaging platform. Plant Methods 2019, 15, 116. [Google Scholar] [CrossRef] [Green Version]
- Pineda, M.; Pérez-Bueno, M.L.; Barón, M. Detection of bacterial infection in melon plants by classification methods based on imaging data. Front. Plant Sci. 2018, 9, 164. [Google Scholar] [CrossRef] [Green Version]
- Manganiello, G.; Nicastro, N.; Caputo, M.; Zaccardelli, M.; Cardi, T.; Pane, C. Functional hyperspectral imaging by high-related vegetation indices to track the wide-spectrum trichoderma biocontrol activity against soil-borne diseases of baby-leaf vegetables. Front. Plant Sci. 2021, 12, 630059. [Google Scholar] [CrossRef]
- Navarro, A.; Nicastro, N.; Costa, C.; Pentangelo, A.; Cardarelli, M.; Ortenzi, L.; Pallottino, F.; Cardi, T.; Pane, C. Sorting biotic and abiotic stresses on wild rocket by leaf-image hyperspectral data mining with an artificial intelligence model. Plant Methods 2022, 18, 45. [Google Scholar] [CrossRef]
- Pane, C.; Manganiello, G.; Nicastro, N.; Carotenuto, F. Early detection of wild rocket tracheofusariosis using hyperspectral image-based machine learning. Remote Sens. 2022, 14, 84. [Google Scholar] [CrossRef]
- Gilardi, G.; Webb, K.; Ortu, G.; Gullino, M.L.; Garibaldi, A. Real-time PCR for rapid in planta detection of Plectosphaerella cucumerina on wild rocket (Diplotaxis tenuifolia). Phytopathol. Mediterr. 2016, 55, 285–292. [Google Scholar]
- Tziros, G.T.; Karaoglanidis, G.S. Molecular identification and pathogenicity of Rhizoctonia solani and Pythium spp. associated with damping-off disease on baby leafy vegetables in Greece. Plant Pathol. 2022, 71, 1381–1391. [Google Scholar] [CrossRef]
- Budgea, G.E.; Shawb, M.W.; Colyera, A.; Pietravalle, S.; Boonhama, N. Molecular tools to investigate Rhizoctonia solani distribution in soil. Plant Pathol. 2009, 58, 1071–1080. [Google Scholar] [CrossRef]
- Rogers, S.L.; Atkins, S.D.; West, J.S. Detection and quantification of airborne inoculum of Sclerotinia sclerotiorum using quantitative PCR. Plant Pathol. 2009, 58, 324–331. [Google Scholar] [CrossRef]
- Grabicoski, E.M.G.; de Souza Jaccoud-Filho, D.; Lee, D.; Henneberg, L.; Pileggi, M. Real-time quantitative and ion-metal indicator lamp-based assays for rapid detection of Sclerotinia sclerotiorum. Plant Dis. 2020, 104, 1514–1526. [Google Scholar] [CrossRef]
- Choudhary, P.; Rai, P.; Yadav, J.; Verma, S.; Chakdar, H.; Goswami, S.K.; Srivastava, A.K.; Kashyap, P.L.; Saxena, A.K. A rapid colorimetric LAMP assay for detection of Rhizoctonia solani AG-1 IA causing sheath blight of rice. Sci. Rep. 2020, 10, 22022. [Google Scholar] [CrossRef]
- Gullino, M.L.; Gilardi, G.; Garibaldi, A. Ready-to-eat salad crops: A plant pathogen’s heaven. Plant Dis. 2019, 103, 2153–2170. [Google Scholar] [CrossRef] [Green Version]
- Cao, F.; Liu, F.; Guo, H.; Kong, W.; Zhang, C.; He, Y. Fast Detection of Sclerotinia Sclerotiorum on Oilseed Rape Leaves Using Low-Altitude Remote Sensing Technology. Sensors 2018, 18, 4464. [Google Scholar] [CrossRef] [Green Version]
- Swain, S.; Rundquist, D.; Arkebauer, T.J.; Narumalani, S.; Wardlow, B. Non-invasive estimation of relative water content in soybean leaves using infrared thermography. Isr. J. Plant Sci. 2012, 60, 25–36. [Google Scholar] [CrossRef]
- O’Sullivan, C.A.; Belt, K.; Thatcher, L.F. Tackling control of a cosmopolitan phytopathogen: Sclerotinia. Front. Plant Sci. 2021, 12, 707509. [Google Scholar] [CrossRef]
- Orzechowska, A.; Trtílek, M.; Tokarz, K.; Rozpa, P. A study of light-induced stomatal response in Arabidopsis using thermal imaging. Biochem. Biophys. Res. Commun. 2020, 533, 1129–1134. [Google Scholar] [CrossRef] [PubMed]
- Tripodi, P.; Nicastro, N.; Pane, C. Digital applications and artificial intelligence in agriculture toward next-generation plant phenotyping. Crop Pasture Sci. 2022, CP21387. [Google Scholar] [CrossRef]
- Sandmann, M.; Grosch, R.; Graefe, J. The use of features from fluorescence, thermography, and NDVI imaging to detect biotic stress in lettuce. Plant Dis. 2018, 102, 1101–1107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Pignon, C.P.; Fernandes, S.B.; Valluru, R.; Bandillo, N.; Lozano, R.; Buckler, E.; Gore, M.A.; Long, S.P.; Brown, P.J.; Leakey, A.D.B. Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes. Plant Physiol. 2021, 187, 2544–2562. [Google Scholar] [CrossRef]
- Ghosh, S.; Malukani, K.K.; Chandan, R.K.; Sonti, R.V.; Jha, G. How plants respond to pathogen attack: Interaction and communication. In Sensory Biology of Plants; Sopory, S., Ed.; Springer: Singapore, 2019. [Google Scholar] [CrossRef]
- Nishad, R.; Ahmed, T.; Rahman, V.J.; Kareem, A. Modulation of plant defense system in response to microbial interactions. Front. Microbiol. 2020, 11, 1298. [Google Scholar] [CrossRef]
- Yang, L.-N.; Liu, H.; Wang, Y.-P.; Seematti, J.; Grenville-Briggs, L.J.; Wang, Z.; Zhan, J. Pathogen-mediated stomatal opening: A previously overlooked pathogenicity strategy in the oomycete pathogen Phytophthora infestans. Front. Plant Sci. 2021, 12, 668797. [Google Scholar] [CrossRef]
- Bharath, P.; Gahir, S.; Raghavendra, A.S. Abscisic acid-induced stomatal closure: An important component of plant defense against abiotic and biotic stress. Front. Plant Sci. 2021, 12, 615114. [Google Scholar] [CrossRef]
- Pane, C.; Spaccini, R.; Caputo, M.; De Falco, E.; Zaccardelli, M. Multi-parameter characterization of disease-suppressive bio-composts from aromatic plant residues evaluated for garden cress (Lepidium sativum L.) cultivation. Horticulturae 2022, 8, 632. [Google Scholar] [CrossRef]
Treatments | Positive Leaves (%) | Total (%) | ||||
---|---|---|---|---|---|---|
0–24 h.p.i. | 24–48 h.p.i. | 48–72 h.p.i. | 72–96 h.p.i. | Positive | Negative | |
S. sclerotiorum foliar inoculation (T1) | 17.5 | 25 | 22.5 | 7.5 | 72.5 (TP) | 27.5 (FN) |
S. sclerotiorum collar inoculation (T2) | 22.5 | 35.0 | 25.0 | 5.0 | 87.5 (TP) | 12.5 (FN) |
R. solani foliar inoculation (T3) | 27.5 | 27.5 | 17.5 | 5.0 | 77.5 (TP) | 22.5 (FN) |
R. solani collar inoculation (T4) | 30.0 | 37.5 | 20.0 | 2.5 | 90.0 (TP) | 10.0 (FN) |
Not inoculated (T5) | 2.5 | 0 | 2.5 | 2.5 | 7.5 (FP) | 92.5 (TN) |
Score | Overall Appearance of the Symptoms | Description |
---|---|---|
0 | Not detectable | Canopy without macroscopic withering |
1 | Initial | Canopy slightly wilted and/or with curling leaves |
2 | Moderate | Plant showing leaf yellowing |
3 | Severe | Plant showing marked yellowing and/or wilting |
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Rippa, M.; Pasqualini, A.; Curcio, R.; Mormile, P.; Pane, C. Active vs. Passive Thermal Imaging for Helping the Early Detection of Soil-Borne Rot Diseases on Wild Rocket [Diplotaxis tenuifolia (L.) D.C.]. Plants 2023, 12, 1615. https://doi.org/10.3390/plants12081615
Rippa M, Pasqualini A, Curcio R, Mormile P, Pane C. Active vs. Passive Thermal Imaging for Helping the Early Detection of Soil-Borne Rot Diseases on Wild Rocket [Diplotaxis tenuifolia (L.) D.C.]. Plants. 2023; 12(8):1615. https://doi.org/10.3390/plants12081615
Chicago/Turabian StyleRippa, Massimo, Andrea Pasqualini, Rossella Curcio, Pasquale Mormile, and Catello Pane. 2023. "Active vs. Passive Thermal Imaging for Helping the Early Detection of Soil-Borne Rot Diseases on Wild Rocket [Diplotaxis tenuifolia (L.) D.C.]" Plants 12, no. 8: 1615. https://doi.org/10.3390/plants12081615