Sustainable Viticulture: Current Practices and Future Developments

Since ancient times, viticulture has been developing in two opposite trends: quality and quantity. The origin of this paradox can be found in the Greek and Roman period and raises from the interaction between technical and cultural factors. Rather fertile grape varieties conducted on high training system have been chosen for high yield in suitable productive areas. In opposite parsimonious varieties together with lower training systems were used in more difficult environments. The dualism between productivity and quality which marked the history, the traditions and the customs of different regions has hardly been able to find a positive evolution, just because of this combination of social factors. In the next ten years, viticulture will not be very different from today\u27s one and it is very likely that the economic models will be more and more oriented toward the valorisation of terroir (Europe) or the emphasis on variety (New World). In the first case, the vineyard and the wine are part of a system trying to keep in balance social, environmental and economical components. When the protagonist is the grape variety, there is a much more simple and clearer message for the consumer; in this case the reputation of some noble varieties open new markets. Grapegrowing, winemaking and wine marketing are becoming more and more part of the same and complete concept. The grape growing techniques which have been dominating the last 50 years (soil cultivation, fertilisation, irrigation, etc...) have favoured an augmentation of the vigour with direct effect on the enological quality of grape and overall on the plant perenniality which has been dramatically reduced. World-wide a worrying increase of vine diseases (especially wood diseases) is also observed. Better balance between vegetation and production should be found with a better plant management (i.e. less and better wound on the plant). Soil also should be regarded with more attention to avoid further lost in production capacity, erosion problems, pollution with alien molecules, destruction of the structure or damage to the biomassa balance. Pest control will have to enter deeper into an integrated management of the vineyard with better attention toward the secondary effects on humans and environment. To progress however, it is necessary to improve the agronomic knowledge and general understanding of viticulture and it\u27s environment

3D vs. 2D MRI radiomics in skeletal Ewing sarcoma: Feature reproducibility and preliminary machine learning analysis on neoadjuvant chemotherapy response prediction

ObjectiveThe extent of response to neoadjuvant chemotherapy predicts survival in Ewing sarcoma. This study focuses on MRI radiomics of skeletal Ewing sarcoma and aims to investigate feature reproducibility and machine learning prediction of response to neoadjuvant chemotherapy. Materials and methodsThis retrospective study included thirty patients with biopsy-proven skeletal Ewing sarcoma, who were treated with neoadjuvant chemotherapy before surgery at two tertiary sarcoma centres. 7 patients were poor responders and 23 were good responders based on pathological assessment of the surgical specimen. On pre-treatment T1-weighted and T2-weighted MRI, 2D and 3D tumour segmentations were manually performed. Features were extracted from original and wavelet-transformed images. Feature reproducibility was assessed through small geometrical transformations of the regions of interest mimicking multiple manual delineations, and intraclass correlation coefficient >0.75 defined feature reproducibility. Feature selection also consisted of collinearity and significance analysis. After class balancing in the training cohort, three machine learning classifiers were trained and tested on unseen data using hold-out cross-validation. Results1303 (77%) 3D and 620 (65%) 2D radiomic features were reproducible. 4 3D and 4 2D features passed feature selection. Logistic regression built upon 3D features achieved the best performance with 85% accuracy (AUC=0.9) in predicting response to neoadjuvant chemotherapy. ConclusionCompared to 2D approach, 3D MRI radiomics of Ewing sarcoma had superior reproducibility and higher accuracy in predicting response to neoadjuvant chemotherapy, particularly when using logistic regression classifier

Detection of atrial fibrillation episodes using a wristband device

Objective: Undiagnosed atrial fibrillation (AF) patients are at high risk of cardioembolic stroke or other complications. The aim of this study was to analyze the blood volume pulse (BVP) signals obtained from a wristband device and develop an algorithm for discriminating AF from normal sinus rhythm (NSR) or from other arrhythmias (ARR). Approach: Thirty patients with AF, 9 with ARR and 31 in NSR were included in the study. The recordings were obtained at rest from Empatica E4 wristband device and lasted 10 min. The analysis, on a 2 min segment, included spectral, variability and irregularity analysis performed on the inter-diastolic interval series, and similarity analysis performed on the BVP signal. Main results and Significance: Variability parameters were the highest in AF, the lowest in NSR and intermediate for ARR, as an example pNN50 values were, respectively 81 ± 8, 20 ± 5, 55 ± (p < 0.05). The similarity parameters were the highest in NSR, the lowest in AF and intermediate for ARR, as an example using a threshold for assessing similarity of : Ï\u80/4: 0.90 ± 0.09, 0.40 ± 0.20, 0.58 ± 0.23 all p < 0.05. The rhythm classification was preceded by over-sampling (using synthetic minority over-sampling technique) the class of ARR, being it the smallest class. Then, the features selection was performed (using the sequential forward floating search algorithm) which identified two variability parameters (pNN70 and pNN40) as the best selection. The classification by the k-nearest neighbor classifier reached an accuracy of about 0.9 for NSR and AF, and 0.8 for ARR. Using pNN70 and pNN40, the specificity for the three rhythms was Spnsr = 0.928, Spaf = 0.963, Sparr = 0.768, while the sensitivity was Spnsr = 0.773, Spaf = 0.754, Sparr = 0.758

Effects of Land-Use Change on Soil Functionality and Biodiversity: Toward Sustainable Planning of New Vineyards

Sustainable agriculture largely depends on soil biodiversity and requires efficient methods to assess the effectiveness of agronomic planning. Knowledge of the landscape and relative pedosite is enriched by data on the soil microarthropod community, which represent useful bio-indicators for early soil-quality detection in land-use change (LUC). In the hilly Maremma region of Grosseto, Italy, two areas, a &gt;10ys meadow converted into a vineyard and an old biodynamic vineyard (no-LUC), were selected for evaluating the LUC effect. For maintaining soil vitality and ecosystem services by meadow, the vineyard was planted and cultivated using criteria of the patented “Corino method”. The aim was to evaluate the LUC impact, within one year, by assessing parameters characterizing soil properties and soil microarthropod communities after the vineyard was planted. The adopted preservative method in the new vineyards did not show a detrimental impact on the biodiversity of soil microarthropods, and in particular, additional mulching contributed to a quick recovery from soil stress due to working the plantation. In the short term, the adopted agricultural context confirmed that the targeted objectives preserved the soil quality and functionality

Rootstock and soil induce transcriptome modulation of phenylpropanoid pathway in grape leaves

Soil qualities and rootstocks are among the main factors that have been acknowledged to influence grape development as well as fruit and wine composition. Despite the role of soil and rootstock in establishing a successful vineyard in terms of grape quality, almost no molecular evidence linking soil and rootstock properties to the gene expression have been reported. The transcriptome variation in response to different soils and rootstocks was investigated through microarray technology. The cv. Pinot Noir was grown on different soils: sand, turf, and vineyard soil. The plants were grafted on the contrasting 101-14 and 1103 Paulsen rootstocks. The modulation of genes' expression in response to different soils and rootstocks was evaluated considering their potential impact on primary (carbohydrate) and secondary (phenylpropanoid) metabolisms. This study highlights a link among soil composition, rootstock, and gene expression. The results open a perspective for a molecular interpretation of the interaction between soil and grapevine

DataSheet_1_3D vs. 2D MRI radiomics in skeletal Ewing sarcoma: Feature reproducibility and preliminary machine learning analysis on neoadjuvant chemotherapy response prediction.pdf

ObjectiveThe extent of response to neoadjuvant chemotherapy predicts survival in Ewing sarcoma. This study focuses on MRI radiomics of skeletal Ewing sarcoma and aims to investigate feature reproducibility and machine learning prediction of response to neoadjuvant chemotherapy.Materials and methodsThis retrospective study included thirty patients with biopsy-proven skeletal Ewing sarcoma, who were treated with neoadjuvant chemotherapy before surgery at two tertiary sarcoma centres. 7 patients were poor responders and 23 were good responders based on pathological assessment of the surgical specimen. On pre-treatment T1-weighted and T2-weighted MRI, 2D and 3D tumour segmentations were manually performed. Features were extracted from original and wavelet-transformed images. Feature reproducibility was assessed through small geometrical transformations of the regions of interest mimicking multiple manual delineations, and intraclass correlation coefficient >0.75 defined feature reproducibility. Feature selection also consisted of collinearity and significance analysis. After class balancing in the training cohort, three machine learning classifiers were trained and tested on unseen data using hold-out cross-validation.Results1303 (77%) 3D and 620 (65%) 2D radiomic features were reproducible. 4 3D and 4 2D features passed feature selection. Logistic regression built upon 3D features achieved the best performance with 85% accuracy (AUC=0.9) in predicting response to neoadjuvant chemotherapy.ConclusionCompared to 2D approach, 3D MRI radiomics of Ewing sarcoma had superior reproducibility and higher accuracy in predicting response to neoadjuvant chemotherapy, particularly when using logistic regression classifier.</p