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- A possibility for non-invasive diagnosis of superficial scald in 'Rocha' pear based on chlorophyll a fluorescence, colorimetry, and the relation between alpha-farnesene and conjugated trienolsPublication . Guerra, Rui Manuel Farinha das Neves; Garde, I. V.; Antunes, Maria Dulce; da Silva, J. M.; Antunes, Rosário; Cavaco, A. M.This study aimed to identify physiological markers in superficially scalded 'Rocha' pear (Pyrus communis L 'Rocha') that would relate to chlorophyll a fluorescence (CF), allowing a non-invasive diagnosis of the disorder. Conditions chosen before shelf life provided two fruit groups with different developing patterns and severity of superficial scald: T fruit fully developed the disorder in storage, while C fruit developed it progressively throughout shelf life. Principal component analysis (PCA) of all the measured variables, and simple linear correlations among several major parameters and scald index (SI)/shelf life showed that scald and ripening/aging were concurring processes, and that it was not possible to isolate a particular variable that could deliver a direct non-invasive diagnosis of the disorder. For both fruit groups the SI resulted from the balance between the reducing power (OD200) and the content of conjugated trienols (CTos) and alpha-farnesene (alpha-Farn) in the fruit peel. At OD200 > 150 there was a linear relationship between CTos and OD200, suggesting that the level of antioxidants was self-adjusted in order to compensate the CTos level. However, at OD200 < 150 this relationship disappeared. A consistent linear relationship between dos and alpha-Farn existed throughout shelf life in both fruit groups, contrarily to the early storage stage, when those compounds do not relate linearly. The CF variables F-0, F-v/F-m, and the colorimetric variables, L* and h degrees were used in multi-linear regressions with other physiological variables. The regressions were made on one of the fruit groups and validated through the other. Reliable regressions to alpha-Farn and CTos were obtained (R approximate to 0.6; rmsec approximate to rmsep). Our results suggest that a model based on CF and colorimetric parameters could be used to diagnose non-invasively both the contents and the relationship between alpha-Farn and CTos and hence the stage of scald development. (C) 2011 Elsevier By. All rights reserved.
- Chlorophyll a Fluorescence: a Fast and Low-Cost Tool to Detect Superficial Scald in 'Rocha' Pear (Pyrus communis L. 'Rocha')?Publication . Garde, I.; Antunes, Maria Dulce; da Silva, J. M.; Guerra, Rui Manuel Farinha das Neves; Cavaco, A. M.This study aimed to test whether the chlorophyll a (Chla) fluorescence determined by a low-cost non-modulated fluorometer could provide fast, reliable and non-invasive estimators of superficial scald in 'Rocha' pear (Pyrus communis L. 'Rocha'). Fruit were harvested before the optimal maturation stage and cold stored under normal atmosphere for 7 months (NA: 0 degrees C, 90-95% RH) and 2 in controlled atmosphere (CA: 0 degrees C, 90-95% RH, 1.5 kPaO(2) + 0.5 kPa CO2) (T), or harvested at the optimal maturation stage and cold stored for 9 months under CA (C). Then, they were transferred to shelf-life conditions (22+/-2 degrees C, 70% RH) and followed for 7 d. Chla fluorescence, scald index (SI), ripening attributes, alpha-farnesene, conjugated trienols, and photosynthetic pigments were determined for each pear in both groups. Conditions chosen before shelf-life did not prevent the subsequent ripening of any fruit, but changed dramatically the superficial scald development pattern: in C fruit, the disorder developed progressively during shelf-life, whereas in T fruit, it peaked during storage. C fruit exhibited a significant negative correlation (R=-0.65; p<0.05) between Fv/Fm and scald development, but not with ripening (R=-0.15; p<0.05). As expected, the opposite was observed in T fruit, in which only a low, positive, yet significant correlation was found between Fv/Fm and ripening (R=0.44; p<0.05). The multiple regression approach using Fv/Fm and other Chla fluorescence parameters produced an equation from which we calculated the 'predicted' scald index in C fruit. This correlated clearly (R=0.73; p<0.05) with the real values visually assessed. If color values a*, b* and Hue were included in this multiple regression, the correlation was significantly enhanced (0.91; p<0.05). Although preliminary, this study has shown that basic Chla fluorescence parameters are valuable estimators of superficial scald in 'Rocha' pear and might be used in the early detection of the disorder.
- Estimation of soluble solids content and fruit temperature in 'rocha' pear using Vis-NIR spectroscopy and the spectraNet–32 deep learning architecturePublication . Martins, J. A; Rodrigues, Daniela; Cavaco, A. M.; Antunes, Maria Dulce; Guerra, Rui Manuel Farinha das NevesSpectra-based methods are becoming increasingly important in Precision Agriculture as they offer non-destructive, quick tools for measuring the quality of produce. This study introduces a novel approach for esti-mating the soluble solids content (SSC) of 'Rocha' pears using the SpectraNet-32 deep learning architecture, which operates on 1D fruit spectra in the visible to near-infrared region (Vis-NIRS). This method was also able to estimate fruit temperatures, which improved the SSC prediction performance. The dataset consisted of 3300 spectra from 1650 'Rocha' pears collected from local markets over several weeks during the 2010 and 2011 seasons, which had varying edaphoclimatic conditions. Two types of partial least squares (PLS) feature selection methods, under various configurations, were applied to the input spectra to identify the most significant wavelengths for training SpectraNet-32. The model's robustness was also compared to a similar state-of-the-art deep learning architecture, DeepSpectra, as well as four other classical machine learning algorithms: PLS, multiple linear regression (MLR), support vector machine (SVM), and multi-layer perceptron (MLP). In total, 23 different experimental method configurations were assessed, with 150 neural networks each. SpectraNet-32 consistently outperformed other methods in several metrics. On average, it was 6.1% better than PLS in terms of the root mean square error of prediction (RMSEP, 1.08 vs. 1.15%), 7.7% better in prediction gain (PG, 1.67 vs. 1.55), 3.6% better in the coefficient of determination (R2, 0.58 vs. 0.56) and 5.8% better in the coefficient of variation (CV%, 8.35 vs. 8.86).
- Temporal metabolic profiling of theQuercus suber-Phytophthora cinnamomisystem by middle-infrared spectroscopyPublication . Hardoim, P.R.; Guerra, Rui Manuel Farinha das Neves; Costa, Ana M. Rosa da; Serrano, M. S.; Sánchez, M. E.; Coelho, A. C.The oomycete Phytophthora cinnamomi is an aggressive plant pathogen, detrimental to many ecosystems including cork oak (Quercus suber) stands, and can inflict great losses in one of the greatest ‘hotspots’ for biodiversity in the world. Here, we applied Fourier transform-infrared (FT-IR) spectroscopy combined with chemometrics to disclose the metabolic patterns of cork oak roots and P. cinnamomi mycelium during the early hours of the interaction. As early as 2 h post-inoculation (hpi), cork oak roots showed altered metabolic patterns with significant variations for regions associated with carbohydrate, glycoconjugate and lipid groups when compared to mockinoculated plants. These variations were further extended at 8 hpi. Surprisingly, at 16 hpi, the metabolic changes in inoculated and mock-inoculated plants were similar, and at 24 hpi, the metabolic patterns of the regions mentioned above were inverted when compared to samples collected at 8 hpi. Principal component analysis of the FT-IR spectra confirmed that the metabolic patterns of inoculated cork oak roots could be readily distinguished from those of mock-inoculated plants at 2, 8 and 24 hpi, but not at 16 hpi. FT-IR spectral analysis from mycelium of P. cinnamomi exposed to cork oak root exudates revealed contrasting variations for regions associated with protein groups at 16 and 24 h post-exposure (hpe), whereas carbohydrate and glycoconjugate groups varied mainly at 24 hpe. Our results revealed early alterations in the metabolic patterns of the host plant when interacting with the biotrophic pathogen. In addition, the FTIR technique can be successfully applied to discriminate infected cork oak plants from mock-inoculated plants, although these differences were dynamic with time. To a lesser extent, the metabolic patterns of P. cinnamomi were also altered when exposed to cork oak root exudates.
- Gene transcripts responsive to drought stress identified in Citrus macrophylla bark tissue transcriptome have a modified response in plants infected by Citrus tristeza virusPublication . da Silva, Melina; Pinto, Patricia IS; Guerra, Rui Manuel Farinha das Neves; Duarte, Amilcar; Power, Deborah; Marques, N T.Citrus macrophylla Wester (CM) has valuable agronomic characteristics such as the ability to grow in saline soils, although with low tolerance to prolonged drought stress (DS). To understand the mechanisms that characterize CM response to water scarcity, this study compared transcriptome profile changes in CM stem tissue when exposed to DS and identified a total of 2745 differentially expressed transcripts (DETs, fold change > 2), of which 631 were up-regulated and 2114 were down-regulated. DETs up-regulated by DS were enriched in pathways such as the redox and osmotic system or soluble carbohydrates and in transcripts for low molecular weight proteins such as late embryogenesis abundant protein (LEA). Down-regulated transcripts were mainly assigned to photosynthesis, transport, phenylpropanoids, calcium dependent kinases, brassinosteroids and other hormones including salicylic acid and abscisic acid. To assess the interplay between DS and Citrus tristeza virus (CTV) infection, twelve genes were profiled by quantitative Real-Time PCR (qPCR) analysis in control and CTV-infected CM plants, with or without DS. The twelve analyzed transcripts were significantly correlated (r = 0.82, p < 0.001) with the RNA-Seq results and gave insight into the responses of CM to drought and/or to infection with CTV. Transcriptome results unveiled highly responsive genes to DS in stem tissue, which may be candidates for genetic selection of high drought tolerant plants of CM.
- 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.
- A TSS classification study of 'Rocha' pear (Pyrus communis L.) based on non-invasive visible/near infra-red reflectance spectraPublication . Bexiga, Florentino; Rodrigues, Daniela; Guerra, Rui Manuel Farinha das Neves; Brazio, António; Balegas, Tiago; Cavaco, A. M.; Antunes, Maria Dulce; Valente de Oliveira, JOSÉThe study focuses on the application of machine learning techniques for classifying the internal quality of 'Rocha' Pear (Pyrus communis L.), i.e., the total soluble solids (TSS), using the non-invasive technique of visible/near infra-red reflectance spectroscopy. Six representative classifiers were evaluated under realistic experimental conditions. The classifiers include representatives of classic parametric (logistic and multiple linear regression), non-parametric distance based methods (K-nearest neighbors), correlation-based (partial least squares), ensemble methods (random forests) and maximum margin classifiers (support vector machines). The classifiers were assessed against metrics such as accuracy, Cohen's Kappa, F-Measure, and the area under the precision recall curve (AUC) in a 10 x 10-fold cross-validation plan. For result analysis non-parametric statistical test of hypotheses were employed. A total of 4880 fruit samples from different origins, maturation states, and harvest years were considered. The main conclusion is that the maximum margin classifier outperforms all the others studied ones, including the commonly used partial least squares. The conclusion holds for both a reflectance spectrum with 1024 features and for a 128 subsample of these. An estimate of the out-of-sample performance for the best classifier is also provided.
- Sensory evaluation and spectra evolution of two kiwifruit cultivars during cold storagePublication . Afonso, Andreia M.; Guerra, Rui; Cruz, Sandra; Antunes, Maria D.Kiwifruit consumption has increased due to its rich nutritional properties. Although ‘Hayward’ continues to be the main cultivar, others, such as yellow fleshed ‘Jintao’, are of increasing interest. The objective of this research was to evaluate the acceptability and storage performance of these two cultivars. Sensory evaluation of green ‘Hayward’ and yellow ‘Jintao’ kiwifruit were performed along cold storage for three seasons/years to follow the organoleptic characteristics through ripening, as well as the acquisition of their spectra by Vis-NIR. For ‘Jintao’ were performed two sensory evaluations per year at 2.5- and 4.5-months’ storage and for ‘Hayward’ at 2.5-, 4.5- and 5.5-months’ storage. The nonparametric Mann–Whitney test and Kruskal–Wallis ANOVA were performed to test the significant differences between the mean ranks among the storage time. A non-metric multidimensional scaling plot method using the ALSCAL algorithm in a seven-point Likert scale was applied to determine the relationships in the data, and a new approach using the receiver operating characteristic (ROC) analysis was tested. The last revealed that, for both cultivars, sweetness, acidity and texture were the variables with better scores for General flavor. Aroma was also important on ‘Jintao’. A strong correlation between soluble solids content (SSC) and reflectance was found for both cultivars, with the 635–780 nm range being the most important. Regarding firmness, a good correlation with reflectance spectra was observed, particularly in ‘Hayward’ kiwifruit. Based on these results, Vis-NIR can be an objective alternative to explore for determination of the optimum eating-ripe stage.
- On the application of spatially resolved reflectance and diffuse light backscattering goniometry to the prediction of firmness in apple ‘bravo de esmolfe’Publication . Guerra, Rui Manuel Farinha das Neves; Almeida, Sandro; Cavaco, A. M.; Antunes, Maria Dulce; Nunes, CarlaIn this study we have made exploratory tests on a set of 40 apples (Malus domestica Borkh.) ‘Bravo de Esmolfe’, using spatially resolved reflectance (SRR) and diffuse light backscattering goniometry (DLBG). The objective was to test the potential of DLBG for firmness prediction, as compared with SRR, whose potential has been already proved in the literature. SRR is performed with a red diode laser and a CMOS camera. DLBG uses the same laser shining on the apple and a photomultiplier tube collecting the light reemitted from a small area, at angles ranging from 90 deg (tangent to the surface) to 180 deg (normal to the surface). From the measurements several parameters have been calculated (e.g. decay exponent for SRR profiles, anisotropy factor for the DLBG angular distributions) and Partial Least squares (PLS) models for the prediction of firmness were build. The model based on DLBG variables (only) and on SRR variables (only) gave similar results. From here we conclude that, within the obvious statistical limitations of the test, DLBG seems to match the potential of SRR for firmness prediction. The possibility of combining both measures in one model is also discussed.
- Non-destructive soluble solids content determination for ‘Rocha’ Pear Based on VIS-SWNIR spectroscopy under ‘Real World’ sorting facility conditionsPublication . Passos, Dário; Rodrigues, Daniela; Cavaco, Ana M.; Antunes, Maria Dulce; Guerra, Rui Manuel Farinha das NevesIn this paper we report a method to determine the soluble solids content (SSC) of 'Rocha' pear (Pyrus communis L. cv. Rocha) based on their short-wave NIR reflectance spectra (500-1100 nm) measured in conditions similar to those found in packinghouse fruit sorting facilities. We obtained 3300 reflectance spectra from pears acquired from different lots, producers and with diverse storage times and ripening stages. The macroscopic properties of the pears, such as size, temperature and SSC were measured under controlled laboratory conditions. For the spectral analysis, we implemented a computational pipeline that incorporates multiple pre-processing techniques including a feature selection procedure, various multivariate regression models and three different validation strategies. This benchmark allowed us to find the best model/preproccesing procedure for SSC prediction from our data. From the several calibration models tested, we have found that Support Vector Machines provides the best predictions metrics with an RMSEP of around 0.82 ∘ Brix and 1.09 ∘ Brix for internal and external validation strategies respectively. The latter validation was implemented to assess the prediction accuracy of this calibration method under more 'real world-like' conditions. We also show that incorporating information about the fruit temperature and size to the calibration models improves SSC predictability. Our results indicate that the methodology presented here could be implemented in existing packinghouse facilities for single fruit SSC characterization.
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