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- Disclosing proteins in the leaves of cork oak plants associated with the immune response to Phytophthora cinnamomi inoculation in the roots: a long-term proteomics approachPublication . Coelho, Ana Cristina; Pires, Rosa; Schütz, Gabriela; Santa, Cátia; Manadas, Bruno; Pinto, Patricia ISThe pathological interaction between oak trees and Phytophthora cinnamomi has implications in the cork oak decline observed over the last decades in the Iberian Peninsula. During host colonization, the phytopathogen secretes effector molecules like elicitins to increase disease effectiveness. The objective of this study was to unravel the proteome changes associated with the cork oak immune response triggered by P. cinnamomi inoculation in a long-term assay, through SWATH-MS quantitative proteomics performed in the oak leaves. Using the Arabidopis proteome database as a reference, 424 proteins were confidently quantified in cork oak leaves, of which 80 proteins showed a p-value below 0.05 or a fold-change greater than 2 or less than 0.5 in their levels between inoculated and control samples being considered as altered. The inoculation of cork oak roots with P. cinnamomi increased the levels of proteins associated with protein-DNA complex assembly, lipid oxidation, response to endoplasmic reticulum stress, and pyridine-containing compound metabolic process in the leaves. In opposition, several proteins associated with cellular metabolic compound salvage and monosaccharide catabolic process had significantly decreased abundances. The most significant abundance variations were observed for the Ribulose 1,5-Bisphosphate Carboxylase small subunit (RBCS1A), Heat Shock protein 90-1 (Hsp90-1), Lipoxygenase 2 (LOX2) and Histone superfamily protein H3.3 (A8MRLO/At4G40030) revealing a pertinent role for these proteins in the host-pathogen interaction mechanism. This work represents the first SWATH-MS analysis performed in cork oak plants inoculated with P. cinnamomi and highlights host proteins that have a relevant action in the homeostatic states that emerge from the interaction between the oomycete and the host in the long term and in a distal organ.
- Spectral analysis, biocompounds, and physiological assessment of Cork Oak leaves: unveiling the interaction with Phytophthora cinnamomi and beyondPublication . Guerra, Rui; Pires, Rosa; Brazio, António; Cavaco, Ana Margarida; Schütz, Gabriela; Coelho, Ana CristinaThe cork oak tree (Quercus suber L.) symbolizes the Montado landscape in Portugal and is a central element in the country’s social and economic history. In recent decades, the loss of thousands of cork oaks has been reported, revealing the ongoing decline of these agroforestry ecosystems. This emblematic tree of the Mediterranean Basin is host to the soil-born root pathogen Phytophthora cinnamomi, an active cork oak decline driver. In this framework, the early diagnosis of trees infected by the oomycete by non-invasive methods should contribute to the sustainable management of cork oak ecosystems, which motivated this work. Gas exchange and visible/near-infrared (400–1100 nm) reflectance spectroscopy measurements were conducted on leaves of both control and P. cinnamomi inoculated plants. These measurements were taken at 63, 78, 91, 126, and 248 days after inoculation. Additionally, at the end of the experiment, biochemical assays of pigments, sugars, and starch were performed. The spectroscopic measurements proved effective in distinguishing between control and inoculated plants, while the standard gas exchange and biochemistry data did not exhibit clear differences between the groups. The spectral data were examined both daily and globally, utilizing the PARAFAC method applied to a three-way array of samples × wavelengths × days. The separation of the two plant groups was attributed to variations in water content (4v (O−H)); shifts in the spectra red edge; and structural modifications in the epidermal layer and leaves’ mesophyll. These spectral signatures can assist in the field identification of cork oaks that are interacting with P. cinnamomi.
- Spatiotemporal modelling of the quality and ripening of two cultivars of "Algarve Citrus" orchards at different edaphoclimatic conditionsPublication . Cavaco, Ana M.; Cruz, Sandra P.; Antunes, M. Dulce; Guerra, Rui; Pires, Rosa; Afonso, Andreia M.; Brazio, António; Silva, Leonardo; Lucas, Marcia Rosendo; Daniel, Mariana; Panagopoulos, ThomasAlgarve Citrus are non-climacteric Protected Geographical Indication (PGI) commodities. They are harvested with minimal levels of juice content (>35 %), soluble solids content (SSC) (>10 %) and maturation index (MI) (>8), as required by the respective PGI normative reference. These internal quality attributes (IQA) are usually determined in small samples of fruit collected from the orchards close to harvest. This study aimed to use geostatistics to help predict the optimal harvest date (OHD) of two sweet orange (Citrus sinensis (L.) Osbeck) cultivars, namely, 'Newhall', and 'Valencia Late', at two different edaphoclimatic conditions observed in the locations of Quarteira, at the coast, and Paderne, near a mountainous area. Two orchards of 0.5-0.7 ha per cultivar were chosen and a total of 25 trees were georeferenced within each orchard, comprising 100 sampling points/trees. Firmness, juice content, SSC and MI of fruit were determined through time. In general, the fruit grown in Quarteira showed higher SSC and MI and lower firmness values, ripening two months earlier than those grown in Paderne, although the full effect of the various edaphoclimatic factors on these results are not fully understood. However, geospatial modelling of ripening has shown a large variability within the orchards, with some IQA evolution patterns observed in some orchards and/or cultivars but not in the others. Specifically, 1) a negative correlation between the firmness and MI spatial patterns; 2) a variable decay rate of firmness, much faster in Paderne for 'Valencia Late'; 3) local minima in juice content, below 35 %, observed in restricted spatial areas and in specific time periods, and which were clearer in 'Newhall'. These local variations highlight the need for an optimized management based on geospatial modelling. For example, the variable decay rate of firmness must be taken into account during fruit harvest and postharvest handling. On the other side, the observation of localized plots with juice content below 35 % must be contextualized in the broader picture of the entire orchard which, in the present study, always had consistent temporal average level above 35 %. This study has provided evidence that fruit ripening variability should be considered in the site-specific orchard management of citrus to optimize their harvest date.
- Ripening assessment of ‘Ortanique’ (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) on tree by SW-NIR reflectance spectroscopy-based calibration modelsPublication . Pires, Rosa; Guerra, Rui Manuel Farinha das Neves; Cruz, Sandra; Antunes, MDC; Brazio, António; Afonso, Andreia M.; Daniel, Mariana; Panagopoulos, Thomas; Gonçalves, Isabel; Cavaco, Ana M.The aim of this study was the non-destructive assessment of ‘Ortanique’ (Citrus reticulata Blanco x Citrus sinensis (L) Osbeck) ripening, based on the prediction of internal quality attributes (IQA) by short-wave near-infrared reflectance spectroscopy (SW-NIRS) calibration models. Spectra from fruit of 50 trees located in two different orchards, were acquired on tree using a customized portable visible near-infrared (vis-NIR) system. Partial least squares (PLS) was used to build the various IQA calibration models. The models were tested through internal validation (IV) and external validation (EV). Generally, the IV results were always superior to those of EV: regarding IV, a high regression coefficient (R2) and low root mean square error of prediction (RMSEP) were achieved, revealing a good predictive performance for juice pH (R2 = 0.80; RMSEP = 0.10; SDR = 2.23), soluble solids content (SSC) (R2 = 0.79; RMSEP = 0.75 %; SDR = 2.27), titratable acidity (TA) (R2 = 0.73; RMSEP = 0.24 % citric acid; SDR = 1.94) and the maturation index (MI) (R2 = 0.80; RMSEP = 1.38; SDR = 2.2). The best EV predictions were obtained for TA (R2 = 0.69; RMSEP = 0.38 % citric acid; SDR = 1.24), and MI (R2 = 0.69; RMSEP = 2.07; SDR = 1.49). Calibration models for glucose, fructose and sucrose showed medium-coarse predictions for both validation strategies. A detailed investigation of MI models was performed, to understand the causes of their poor EV results. In the context of EV, model updating strategies were explored by using some validation samples to improve the calibration model. The methods of bias correction and spiking were tested, showing a clear improvement in the predictions.