Modelling the Effect of Temperature on Respiration Rate of Fresh Cut Papaya (Carica papaya L.) Fruits.

A respiration rate (RR) model based on Peleg’s equation was developed for predicting RRs of fresh cut papaya. Respiration data for fresh cut papaya at 3/4 maturity were generated at temperatures 5, 10, 15, 20, 25 and 30°C using a closed system. RRs was found to be significantly influenced by storage temperature and increased from 0.021 to 0.289 mL[O2]/kg·h and 0.063 to 0.393 mL[CO2]/kg·h as a function of O2 and CO2 gas concentrations, respectively. Peleg’s constant K 1 and K 2 were obtained from linear regression analysis using GraphPad Prism 5.0 software and regression coefficients have good fit with values close to unity. The model was verified to assess the capability of its predictability of the RRs over the temperatures. There was good agreement with the experimentally estimated RRs. Information derived from the model can contribute in the design of successful modified atmospheric systems for storage of fresh cut papaya

When do apples stop growing, and why does it matter?

Apples in the commercial food chain are harvested up to two weeks before maturity. We explore apple fruit development through the growing season to establish the point at which physical features differentiating those cultivars become evident. This is relevant both for the understanding of the growing process and to ensure that any identification and classification tools can be used both on ripened-on-tree and stored fruit. Current literature presents some contradictory findings on apple growth, we studied 12 apple cultivars in the Brogdale National Fruit Collection, UK over two seasons to establish patterns of growth. Fruit were sampled at regular time points throughout the growing season and four morphometrics (maximum length, maximum diameter, weight, and centroid size) were collected. These were regressed against growing degree days in order to appropriately describe the growth pattern observed. All four morphometrics were adequately described using log-log linear regressions, with adjusted R2 estimates ranging from 78.3% (maximum length) to 86.7% (weight). For all four morphometrics, a 10% increase in growing degree days was associated with a 1% increase in the morphometric. Our findings refine previous work presenting rapid early growth followed by a plateau in later stages of development and contrast with published expo-linear models. We established that apples harvested for commercial storage purposes, two weeks prior to maturity, showed only a modest decrease in size compared with ripened-on-tree fruit, demonstrating that size morphometric approaches are appropriate for classification of apple fruit at point of harvest

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

ATR-FTIR spectroscopy non-destructively detects damage-induced sour rot infection in whole tomato fruit

Main conclusion ATR-FTIR spectroscopy with subsequent multivariate analysis non-destructively identifies plant–pathogen interactions during disease progression, both directly and indirectly, through alterations in the spectral fingerprint. Plant–environment interactions are essential to understanding crop biology, optimizing crop use, and minimizing loss to ensure food security. Damage-induced pathogen infection of delicate fruit crops such as tomato (Solanum lycopersicum) are therefore important processes related to crop biology and modern horticulture. Fruit epidermis as a first barrier at the plant–environment interface, is specifically involved in environmental interactions and often shows substantial structural and functional changes in response to unfavourable conditions. Methods available to investigate such systems in their native form, however, are limited by often required and destructive sample preparation, or scarce amounts of molecular level information. To explore biochemical changes and evaluate diagnostic potential for damage-induced pathogen infection of cherry tomato (cv. Piccolo) both directly and indirectly, mid-infrared (MIR) spectroscopy was applied in combination with exploratory multivariate analysis. ATR-FTIR fingerprint spectra (1800–900 cm−1) of healthy, damaged or sour rot-infected tomato fruit were acquired and distinguished using principal component analysis and linear discriminant analysis (PCA–LDA). Main biochemical constituents of healthy tomato fruit epidermis are characterized while multivariate analysis discriminated subtle biochemical changes distinguishing healthy tomato from damaged, early or late sour rot-infected tomato indirectly based solely on changes in the fruit epidermis. Sour rot causing agent Geotrichum candidum was detected directly in vivo and characterized based on spectral features distinct from tomato fruit. Diagnostic potential for indirect pathogen detection based on tomato fruit skin was evaluated using the linear discriminant classifier (PCA–LDC). Exploratory and diagnostic analysis of ATR-FTIR spectra offers biological insights and detection potential for intact plant–pathogen systems as they are found in horticultural industries