Yarrowia lipolytica growth under increased air pressure: influence on enzymes production

Improvement of microbial cell cultures oxygenation can be achieved by the increase of total air pressure, which increases oxygen solubility in the medium. In this work, a pressurized bioreactor was used for Yarrowia lipolytica batch cultivation under increased air pressure from 1 to 6 bar. Cell growth was strongly enhanced by the pressure rise. Fivefold and 3.4-fold increases in the biomass production and in specific growth rate, respectively, were observed under 6 bar. The increase of oxygen availability caused the induction of the antioxidant enzyme superoxide dismutase, which indicates that the defensive mechanisms of the cells against oxidative stress were effective and cells could cope with increased pressure. The pregrowth of Y. lipolytica under increased pressure conditions did not affect the lipase production ability of the cells. Moreover, the extracellular lipase activity increased 96% using a 5-bar air pressure instead of air at 1- bar pressure during the enzyme production phase. Thus, air pressure increase in bioreactors is an effective mean of cell mass and enzyme productivity enhancement in bioprocess based in Y. lipolytica cultures

Parameter identification of the STICS crop model, using an accelerated formal MCMC approach

This study presents a Bayesian approach for the parameters’ identification of the STICS crop model based on the recently developed Differential Evolution Adaptive Metropolis (DREAM) algorithm. The posterior distributions of nine specific crop parameters of the STICS model were sampled with the aim to improve the growth simulations of a winter wheat (Triticum aestivum L.) culture. The results obtained with the DREAM algorithm were initially compared to those obtained with a Nelder-Mead Simplex algorithm embedded within the OptimiSTICS package. Then, three types of likelihood functions implemented within the DREAM algorithm were compared, namely the standard least square, the weighted least square, and a transformed likelihood function that makes explicit use of the coefficient of variation (CV). The results showed that the proposed CV likelihood function allowed taking into account both noise on measurements and heteroscedasticity which are regularly encountered in crop modellingPeer reviewe

Placenta-Like Structure of the Aphid Endoparasitic Wasp Aphidius ervi: A Strategy of Optimal Resources Acquisition

Aphidius ervi (Hymenoptera: Braconidae) is an entomophagous parasitoid known to be an effective parasitoid of several aphid species of economic importance. A reduction of its production cost during mass rearing for inundative release is needed to improve its use in biological control of pests. In these contexts, a careful analysis of its entire development phases within its host is needed. This paper shows that this parasitoid has some characteristics in its embryological development rather complex and different from most other reported insects, which can be phylogenetically very close. First, its yolkless egg allows a high fecundity of the female but force them to hatch from the egg shell rapidly to the host hemocoel. An early cellularisation allowing a rapid differentiation of a serosa membrane seems to confirm this hypothesis. The serosa wraps the developing embryo until the first instar larva stage and invades the host tissues by microvilli projections and form a placenta like structure able to divert host resources and allowing nutrition and respiration of embryo. Such interspecific invasion, at the cellular level, recalls mammal's trophoblasts that anchors maternal uterine wall and underlines the high adaptation of A. ervi to develop in the host body

Defect segmentation on 'Jonagold' apples using colour vision and a Bayesian classification method

This paper shows how the information enclosed in a colour image of a bi-colour apple can be used to segment defects. A method to segment pixels, based on a Bayesian classification process, is proposed. The colour frequency distributions of the healthy tissue and of the defects were used to estimate the probability distribution of each class. The results showed that most defects, namely bitter pit, fungi attack, scar tissue, frost damages, bruises, insect attack and scab, are segmented. However, russet was sometimes confused with the transition area between ground and blush colour. (C) 1999 Elsevier Science B.V. All rights reserved

Effects of design and kinematic parameters of rotary cultivators on soil structure

In comparison with drawn implements, rotary cultivators are of particular interest in final seedbed preparation. In this paper, a quantitative basis for the description of soil structure created by rotary tillers is given. Undisturbed Ap horizon samples were collected, impregnated with polyester resin, sectioned by sawing and analysed by means of image analysis. Total porosity, area and size of pores are related to the design and kinematic parameters of the rotary cultivator, arising from an analysis based upon the location of instant centres of velocity. It is shown that using a rotary cultivator with a higher ratio of peripheral to forward velocity leads to a smaller total mean porosity which is more homogeneous

Defects segmentation on 'Golden Delicious' apples by using colour machine vision

A method based on colour information is proposed to detect defects on 'Golden Delicious' apples. In a first step, a colour model based on the variability of the normal colour is described. To segment the defects, each pixel of ail apple image is compared with the model. If it matches the pixel, it is considered as belonging to healthy tissue, otherwise as a defect. Two other steps refine the segmentation, using either parameters computed on the whole fruit, or values computed locally. Some results are shown and discussed. The algorithm is able to segment a wide range of defects. (C) 1998 Elsevier Science B.V. All rights reserved

Line Cluster Detection Using A Variant Of The Hough Transform For Culture Row Localisation

An adaptation of the Hough transform was proposed for the detection of line clusters of known geometry. This method was applied in agriculture for the detection of sowing furrows created by a driller and of chicory plant rows during harvesting process. The sowing rows were revealed by a background correction, the background being obtained thanks to a median rank filter. The method was found efficient in eliminating the shadows. For the crop rows, a neural network was used to localise the plants. While the petiole and the leaves were easily separated from the soil, the chicory root and the soil having about the same colour and the lighting condition varying widely, it was more difficult to obtain a good contrast between those parts, which leaves place for some improvements. The adapted Hough transform consisted in computing one transform for each line in the cluster with, for reference, the position and direction of the theoretical position of the row. The different transforms were then added. It was found effective for both the sowing rows and the chicory rows. Results remained good even in very noisy conditions, when the rows were incomplete or when artefacts would lead its classical counter part to show several alignments other than the expected ones. The culture rows were localised with a precision of a few centimetres which was compatible with the proposed applications.RECOTRAC

A Real-Time Grading Method Of Apples Based On Features Extracted From Defects

This paper presents a hierarchical grading method applied to Jonagold apples. Several images covering the whole surface of the fruits were acquired thanks to a prototype grading machine. These images were then segmented and the features of the defects were extracted. During a learning procedure, the objects were classified into clusters by k-mean clustering. The classification probabilities of the objects were summarised and on this basis the fruits were graded using quadratic discriminant analysis. The fruits were correctly graded with a rate of 73 %. The errors were found having origins in the segmentation of the defects or for a particular wound, in a confusion with the calyx end.project D ½ - 5819A section

Selection of the most efficient wavelength bands for 'Jonagold' apple sorting

This paper presents a method based on quadratic discriminant analysis to select the best filters for detecting a wide range of defects in 'Jonagold' apple fruit using a multi-spectral vision system. Reflectance spectra of damaged and sound tissue were recorded using a visible/NIR spectrometer. Analysed defects consisted of scald, hail damage (with and without skin perforation), limb rubs, russets, scab tissue, frost damage, rot, visible flesh damage and recent bruises. Camera filter effects were approximated by summing the reflectances of all the wavelengths within the filter bandwidth. Combinations of three and four filters were tested and evaluated for discriminating damaged tissues from healthy ones. If a three-filter combination appeared sufficient to detect most of the damaged tissue, a four-filter combination should be considered for the complete sorting automation of this bicolour apple variety. A fourth filter was necessary to quantify the ratio between the blush and ground colours. Regarding recent bruise defects which represented the major difficulty, an image segmentation algorithm based on local contrast variations can enhance their detection. (C) 2003 Elsevier B.V. All rights reserved