Quality evaluation of six varieties of strawberry (Frutilla x ananassa Duchense) at harvest and postharvest

[SPA] La frutilla ocupa el principal lugar de la producción de “berries” en la Argentina. Por ser un fruto de alta perecibilidad, es necesario evaluar el comportamiento en precosecha y poscosecha de los cultivares que dominan el mercado y compararlos con los nuevos genotipos. La calidad final depende del sistema de producción y del cuidado durante cosecha, acondicionamiento y almacenamiento. El objetivo del presente trabajo fue evaluar el comportamiento en precosecha y poscosecha de seis variedades de frutilla. Los materiales utilizados fueron plantines frescos de Chandler, Festival, Plarionfre, Sweet Charlie, Camarosa y Earlibrite. El diseño experimental utilizado fue completamente aleatorizado con tres repeticiones a campo, y cuatro repeticiones en poscosecha. A cosecha se evaluó rendimiento, tamaño medio de frutos y precocidad. En poscosecha, los frutos se acondicionaron en canastas plásticas de 250 gramos y almacenaron en cajas de cartón a 1ºC y 90% HR durante 14 días. Los índices de calidad evaluados a cosecha y durante la conservación fueron sólidos solubles, porcentaje de materia seca, color, firmeza y calidad. La cosecha fue escalonada y se extendió durante 45 días en primavera. En rendimiento y precocidad, la variedad Plarionfre se diferenció significativamente del resto desde la segunda a la décima cosecha (56% de la producción total). A partir de allí y hasta el final del ciclo, el testigo Chandler registra similar nivel productivo. Earlibrite obtuvo los menores rendimientos comportándose las otras variedades en situación intermedia. A cosecha, Festival y Camarosa se destacaron significativamente del resto por su firmeza. No se encontraron diferencias significativas en porcentaje de materia seca y sólidos solubles. Las mayores pérdidas de peso se produjeron en Chandler y Plarionfre. En cuanto a color de los frutos, Camarosa y Sweet Charlie presentaron mayor intensidad de color rojo tanto a cosecha como en poscosecha. Según escala de calidad durante el almacenamiento, se destacaron las variedades Chandler y Camarosa. [ENG] Strawberry occupies the main position of "berries" production in Argentina. As the fruits are highly perishable, it is necessary to evaluate the behaviour of the most important varieties in the our market at harvest and post-harvest comparing them with new varieties. Strawberry quality depends on the production system and the management of the fruits at harvest and during packaging and storage. The objective of this study was to evaluate the preharvest and post-harvest behaviour of six varieties of strawberry. Fresh transplants of Chandler, Festival, Plarionfre, Sweet Charlie, Camarosa and Earlibrite varieties were used. A randomized design at open-field with three replicates and during storage with four replicates were used. Yield, average size of fruits and earliness were evaluated at harvest. Fruits were packed in plastic baskets (250 grams) and stored in cardboard boxes (1ºC/90%HR) for 14 days. Soluble solids, dry matter, colour, firmness and visual quality at harvest and during storege period were evaluated. Harvest period was extended 45 days on Spring. Yield and earliness of Plarionfre variety showed significant differences since the second to the tenth harvest (56% of total production). After this harvest to the end of the crop, Chandler (control variety) recorded a similar production level. Earlbrite obtained the lowest yield and the others varieties were between them. At harvest, fruit firmness of Festival and Camarosa showed significant differences. No differences in dry matter and soluble solids were found among varieties. Chandler and Plarionfre recorded the highest weigth losses. Camarosa and Sweet Charlie fruits showed a deep red colour at harvest and postharvest. Chandler and Camarosa fruits mantained the best visual quality during the storage period.Los autores agradecen la financiación de este trabajo a través de los subsidios UBACYT G- 025 y FONCYT – PICT 11193

A look at the past to draw lessons for the future: how the case of an urgent ICU transfer taught us to always be ready with a plan B

Objective: The urgent transfer of an intensive care unit (ICU) is particularly challenging because it carries a high clinical and infectious risk and is a critical node in a hospital’s patient flow. In early 2017, exceptional rainfall damaged the roof of the tertiary hospital in Udine, necessitating the relocation of one of the three ICUs for six months. We decided to assess the impact of this transfer on quality of care and patient safety using a set of indicators, primarily considering the incidence of healthcare-associated infections (HAIs) and mortality rates. Methods: We performed a retrospective, observational analysis of structural, process, and outcome indicators comparing the pre- and posttransfer phases. Specifically, we analyzed data between July 2016 and June 2017 for the transferred ICU and examined mortality and the incidence of HAI. Results: Despite significant changes in structural and organizational aspects of the unit, no differences in mortality rates or cumulative incidence of HAIs were observed before/after transfer. We collected data for all 393 patients (133 women, 260 men) admitted to the ICU before (49.4%) and after transfer (50.6%). The mortality rate for 100 days in the ICU was 1.90 (34/1791) before and 2.88 (37/1258) after transfer (p = 0.063). The evaluation of the occurrence of at least one HAI included 304 patients (102 women and 202 men), as 89 of them were excluded due to a length of stay in the ICU of less than 48 h; again, there was no statistical difference between the two cumulative incidences (13.1% vs. 6.9%, p = 0.075). Conclusion: In the case studied, no adverse effects on patient outcomes were observed after urgent transfer of the injured ICU. The indicators used in this study may be an initial suggestion for further discussion

Hacia una horticultura sustentable : el cultivo de tomate cherry

p.83-86El objetivo del presente trabajo fue evaluar indicadores cuantitativos en una variedad de tomate "cherry" (Lycopersicon esculentum var. cerasiforme) en sistemas de producción convencionales, de bajos insumos y orgánicos. Se evaluaron: número de frutos cosechados por metro cuadrado, rendimiento, peso medio de frutos y particionamiento de materia seca. El rendimiento por planta y pro unidad de superficie fue superior en el sistema de producción convencional y orgánico con incorporación de estiércol, diferenciándose significativamente del sistema de bajos insumos y del orgánico: rastrojos de maíz. El antecesor avena mostró los menores rendimiento

An easy, prompt and reproducible methodology to manage an unexpected increase of incident reports in surgery theatres

Surgery is a high-risk hospital area for adverse events (AEs) occurrence. This study aims to develop an effectiveness and reactive methodology to manage an unexpected increase of AEs in the operating rooms (ORs) of a large Academic Hospital providing about 30\u2009000 surgeries per year

Implications of an intensive care unit urgent transfer in terms of clinical and infectious risk

Background and Objectives: Proper functioning of an intensive care unit (ICU) contributes to efficient hospital management, but what happens when the ICU needs urgent transfer? Considering that healthcare-associated infections (HAIs) are one of the most important factors that can negatively impact patient outcomes in an ICU, we retrospectively reviewed cases that occurred in an ICU in our hospital on January 6, 2017. We assessed the cumulative incidence of HAIs in patients admitted to the ICU before and after transfer, and overall impact on the three hospital’s ICUs. Methods: The clinical records of inpatients admitted to the ICU in the 6 months before and after transfer were analyzed to assess the occurrence of HAI. 482 Demographic data were collected to describe the patients. The overall impact on ICU activity was analyzed considering six-month mortality rates for the period 2015-2019. Descriptive statistics and a multivariable model were performed including all parameters that were significantly correlated with HAI occurrence in the univariate analysis. Results: The revision was conducted on 393 clinical records. The number of patients included in the study of the occurrence of at least one HAI was 304, as 89 patients were excluded because their length of stay in the ICU was less than 48 hours. HAIs occurred in 13.1% of patients before and in 6.9% after transfer. Pneumonia accounted for 52.9% of HAIs, bloodstream infections for 29.4%, urinary tract infections for 14.7%. No significant difference in incidence was observed between the two periods. The presence of a central venous catheter was significantly associated with the occurrence of at least one HAI (p=0.045). Conclusions: Urgent transfer of the ICU did not appear to have an impact on clinical and infectious risk, as no difference in infectious disease incidence and mortality was observed likely due to the dedicated work of the healthcare staff

Machine learning using the extreme gradient boosting (XGBoost) algorithm predicts 5-day delta of SOFA score at ICU admission in COVID-19 patients

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary out- come the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs . 0.69, P < 0.01 [paired t -test with 95% confidence interval]). Conclusions: The XGBoost model predicted the change in SOFA score in critically ill COVID-19 patients admitted to the ICU and can guide clinical decision support systems (CDSSs) aimed at optimizing available resources