Jan Verwaeren

Dr. Jan Verwaeren

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Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 June 2017 in New Phytologist
Verified
Journal Article
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MAMaarten Ameye
Maarten Ameye
SASilke Allmann
Silke Allmann
JVJan Verwaeren
Jan Verwaeren
Guy SmaggheGuy Smagghe
Guy Smagghe
GHGeert Haesaert
Geert Haesaert
Kris AudenaertKris Audenaert
Kris Audenaert
Summary 666 I. Introduction 667 II. Biosynthesis 667 III. Meta‐analysis 669 IV. The type of stress influences the total amount of GLVs released 669 V. Herbivores can modulate the wound‐induced release of GLVs 669 VI. Fungal infection greatly induces GLV production 672 VII. Monocots and eudicots respond differentially to different types of stress 673 VIII. The type of stress does not influence the proportion of GLVs per chemical class 673 IX. The type of stress does influence the isomeric ratio within each chemical class 674 X. GLVs: from signal perception to signal transduction 676 XI. GLVs influence the C/N metabolism 677 XII. Interaction with plant hormones 678 XIII. General conclusions and unanswered questions 678 Acknowledgements 679 References 679 Summary: Plants respond to stress by releasing biogenic volatile organic compounds (BVOCs). Green leaf volatiles (GLVs), which are abundantly produced across the plant kingdom, comprise an important group within theBVOCs. They can repel or attract herbivores and their natural enemies; and they can induce plant defences or prime plants for enhanced defence against herbivores and pathogens and can have direct toxic effects on bacteria and fungi. Unlike other volatiles,GLVs are released almost instantly upon mechanical damage and (a)biotic stress and could thus function as an immediate and informative signal for many organisms in the plant's environment. We used a meta‐analysis approach in which data from the literature onGLVproduction during biotic stress responses were compiled and interpreted. We identified that different types of attackers and feeding styles add a degree of complexity to the amount of emittedGLVs, compared with wounding alone. This meta‐analysis illustrates that there is less variation in theGLVprofile than we presumed, that pathogens induce moreGLVs than insects and wounding, and that there are clear differences inGLVemission between monocots and dicots. Besides the meta‐analysis, this review provides an update on recent insights into the perception and signalling ofGLVs in plants.

1 March 2015 in Atmospheric Environment
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Journal Article
Closed access
JBJoris Van Den Bossche
Joris Van Den Bossche
JPJan Peters
Jan Peters
JVJan Verwaeren
Jan Verwaeren
DBDick Botteldooren
Dick Botteldooren
JTJan Theunis
Jan Theunis
Bernard De BaetsBernard De Baets
Bernard De Baets

1 September 2013 in Environmental Modelling & Software
Verified
Journal Article
Closed access
SFShinji Fukuda
Shinji Fukuda
Bernard De BaetsBernard De Baets
Bernard De Baets
WWWillem Waegeman
Willem Waegeman
JVJan Verwaeren
Jan Verwaeren
AMAns M. Mouton
Ans M. Mouton

1 September 2018 in Food Quality and Preference
Verified
Journal Article
Closed access
JSJoachim Schouteten
Joachim Schouteten
JVJan Verwaeren
Jan Verwaeren
SLSofie Lagast
Sofie Lagast
XGXavier Gellynck
Xavier Gellynck
Hans De SteurHans De Steur
Hans De Steur

1 May 2017 in Computers in Industry
Verified
Journal Article
Closed access
MVMike Vanderroost
Mike Vanderroost
PRPeter Ragaert
Peter Ragaert
JVJan Verwaeren
Jan Verwaeren
BMBruno De Meulenaer
Bruno De Meulenaer
BBBernard De Baets
Bernard De Baets
FDFrank Devlieghere
Frank Devlieghere

1 November 2014 in Journal of Dairy Science
Verified
Journal Article
Closed access
SJS. Jorjong
S. Jorjong
AKAriette.T.M. Van Knegsel
Ariette.T.M. Van Knegsel
JVJan Verwaeren
Jan Verwaeren
MLM.VAl Lahoz
M.VAl Lahoz
RBR.M. Bruckmaier
R.M. Bruckmaier
VFVeerle Fievez
Veerle Fievez
Most cows encounter a state of negative energy balance during the periparturient period, which may lead to metabolic disorders and impaired fertility. The aim of this study was to assess the potential of milk fatty acids as diagnostic tools of detrimental levels of blood plasma nonesterified fatty acids (NEFA), defined as NEFA concentrations beyond 0.6 mmol/L, in a data set of 92 early lactating cows fed a glucogenic or lipogenic diet and subjected to 0-, 30-, or 60-d dry period before parturition. Milk was collected in wk 2, 3, 4, and 8 (n = 368) and blood was sampled weekly from wk 2 to 8 after parturition. Milk was analyzed for milk fatty acids and blood plasma for NEFA. Data were classified as "at risk of detrimental blood plasma NEFA" (NEFA ≥ 0.6 mmol/L) and "not at risk of detrimental blood plasma NEFA" (NEFA <0.6 mmol/L). Concentrations of 45 milk fatty acids and milk fat C18:1 cis-9-to-C15:0 ratio were subjected to a discriminant analysis. Milk fat C18:1 cis-9 revealed the most discriminating variable to identify detrimental blood plasma NEFA. A false positive rate of 10% allowed us to diagnose 46% of the detrimental blood plasma NEFA cases based on a milk fat C18:1 cis-9 concentration of at least 230 g/kg of milk fatty acids. Additionally, it was assessed whether the milk fat C18:1 cis-9 concentrations of wk 2 could be used as an early warning for detrimental blood plasma NEFA risk during the first 8 wk in lactation. Cows with at least 240 g/kg of C18:1 cis-9 in milk fat had about 50% chance to encounter blood plasma NEFA values of 0.6 mmol/L or more during the first 8 wk of lactation, with a false positive rate of 11.4%. Profit simulations were based on costs for cows suffering from detrimental blood plasma NEFA, and costs for preventive treatment based on daily dosing of propylene glycol for 3 wk. Given the relatively low incidence rate (8% of all observations), continuous monitoring of milk fatty acids during the first 8 wk of lactation to diagnose detrimental blood plasma NEFA does not seem cost effective. On the contrary, milk fat C18:1 cis-9 of the second lactation week could be an early warning of cows at risk of detrimental blood NEFA. In this case, selective treatment may be cost effective.