Navarro Alejandra, Nicastro Nicola, Costa Corrado, Pentangelo Alfonso, Cardarelli Mariateresa, Ortenzi Luciano, Pallottino Federico, Cardi Teodoro, Pane Catello
Council for Agricultural Research and Economics (CREA), Research Centre for Vegetable and Ornamental Crops, Via Cavalleggeri 25, 84098, Pontecagnano Faiano, Italy.
Consiglio 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, Italy.
Plant Methods. 2022 Apr 2;18(1):45. doi: 10.1186/s13007-022-00880-4.
Wild rocket (Diplotaxis tenuifolia) is prone to soil-borne stresses under intensive cultivation systems devoted to ready-to-eat salad chain, increasing needs for external inputs. Early detection of the abiotic and biotic stresses by using digital reflectance-based probes may allow optimization and enhance performances of the mitigation strategies.
Hyperspectral image analysis was applied to D. tenuifolia potted plants subjected, in a greenhouse experiment, to five treatments for one week: a control treatment watered to 100% water holding capacity, two biotic stresses: Fusarium wilting and Rhizoctonia rotting, and two abiotic stresses: water deficit and salinity. Leaf hyperspectral fingerprints were submitted to an artificial intelligence pipeline for training and validating image-based classification models able to work in the stress range. Spectral investigation was corroborated by pertaining physiological parameters.
Water status was mainly affected by water deficit treatment, followed by fungal diseases, while salinity did not change water relations of wild rocket plants compared to control treatment. Biotic stresses triggered discoloration in plants just in a week after application of the treatments, as evidenced by the colour space coordinates and pigment contents values. Some vegetation indices, calculated on the bases of the reflectance data, targeted on plant vitality and chlorophyll content, healthiness, and carotenoid content, agreed with the patterns of variations observed for the physiological parameters. Artificial neural network helped selection of VIS (492-504, 540-568 and 712-720 nm) and NIR (855, 900-908 and 970 nm) bands, whose read reflectance contributed to discriminate stresses by imaging.
This study provided significative spectral information linked to the assessed stresses, allowing the identification of narrowed spectral regions and single wavelengths due to changes in photosynthetically active pigments and in water status revealing the etiological cause.
在用于即食沙拉链的集约化种植系统中，野生火箭菜（细叶双行芥）容易受到土传胁迫，对外源投入的需求不断增加。使用基于数字反射率的探头早期检测非生物和生物胁迫，可能有助于优化和提高缓解策略的效果。
在温室实验中，对细叶双行芥盆栽植物进行了为期一周的五种处理：一种对照处理，浇水至持水量的100%；两种生物胁迫：枯萎病和丝核菌腐烂病；两种非生物胁迫：水分亏缺和盐度。将叶片高光谱指纹图谱输入人工智能流程，以训练和验证能够在胁迫范围内工作的基于图像的分类模型。通过相关生理参数证实光谱研究结果。
水分状况主要受水分亏缺处理影响，其次是真菌病害，而与对照处理相比，盐度并未改变野生火箭菜植株的水分关系。生物胁迫在处理后仅一周就引发了植物变色，颜色空间坐标和色素含量值证明了这一点。基于反射率数据计算的一些植被指数，针对植物活力、叶绿素含量、健康状况和类胡萝卜素含量，与生理参数观察到的变化模式一致。人工神经网络有助于选择可见光（492 - 504、540 - 568和712 - 720 nm）和近红外（855、900 - 908和970 nm）波段，其读取的反射率有助于通过成像区分胁迫。
本研究提供了与评估胁迫相关的重要光谱信息，由于光合活性色素和水分状况的变化揭示了病因，从而能够识别狭窄的光谱区域和单一波长。
