Determining Juice Quality in Relation to HLB Infection

Transcription

1 Determining Juice Quality in Relation to HLB Infection M Irey, G Thelwell, H Hou, D VanStrijp, P Sun SGC/USSC L Baldwin, A Plotto, W Zhao, S Raithore, J Bai, J Manthey USDA ARS Quick Update on the Southern Gardens GMO Trials M Irey, R Kress, G Thelwell, J Kurimai, J Snively, R Terra, B Ingram

2 Determining Juice Quality in Relation to HLB Infection M Irey, G Thelwell, H Hou, D VanStrijp, P Sun SGC/USSC L Baldwin, A Plotto, W Zhao, S Raithore, J Bai, J Manthey USDA ARS

3 What do we know (or what do we think we know )?

4 Juice Quality in Relation to HLB What we know Off flavors are worse in Hamlin than in Valencia Subtle but there More so early in the season The levels of the bitter compounds nomilin and limonin are related to perceived offflavors Most likely related to, but not directly responsible for the off flavors Brix tends to go down as a result of HLB infection Trend towards higher acid and lower ratio What we don t know.. What compound(s) cause(s) the off flavors As a result, we don t know what to measure For what we do measure, we don t know the critical thresholds that parallel the perceived off flavors Complex matrix Metabolites change during season The ranges overlap 4

5 Baldwin/Plotto 5

6 Managing Quality With respect to HLB, off flavors are correlated to the amount of symptomatic fruit in the mix More symptomatic = more off flavors Controlled studies have shown that it is possible to blend out the off-flavors (25:75 symptomatic to healthy, above that, trained panelists can tell a difference) But where do you get the healthy fruit? All groves are infected to some degree, many groves up to 100% infected We need a way to measure the potential to produce off flavors It would be nice to have a real time assay If we had a way to measure the potential we may be able to manage the harvest or processing to minimize the negative quality effects of HLB 6

7 Possible Parameters to Measure as Indicators Fruit size Limonin and Nomilin PCR on orange juice Patent pending test to measure DNA in orange juice 1

8 Use of qpcr to predict quality of orange juice affected by HLB Elizabeth Baldwin, Wei Zhao, Jinhe Bai, Anne Plotto, John Manthey, Smita Raithore and Mike Irey US Horticultural Research Laboratory, Ft. Pierce, FL

9 Corr Li/HLB Corr LJ/HLB Corr Li/Bitter Corr LJ/Bitter Corr Li/metallic Corr LJ/metallic Corr LI/sweet Corr LJ/sweet Corr LI/sour Corr Coor LI/sour LJ/sour CorrLI/stale Corr LJ stale Corr grape/li Corr grape/lj fruity non cit/li Fruity non cit/lj Li\orange LJ/orange Li /green LJ/green Li/orange peel LJ/orange peel Li/oxid oil LJ/Oxid oil Li/umami LJ/umami Li/body LJ/body Li/tingly LJ/tingly Li/astringent LJ/astringent Li/burning LJ/burning Li/aft bitter LJ/aft bitter Li/aft astring LJ/after astring Li/aft burn LJ/aft burn Li/Sum aft LJ/sum aft LI/sum pos LJ/sum pos Li/sum neg LJ sum neg

10 Ct: Bigger number = better quality Smaller number = lower quality

11 So what did we do for Crop? Once a week collected random juice samples from the loads coming to the plant Total of 778 samples Analyses 305 E/M samples 455 Valencia samples Limonin/Nomilin by HPLC Ct value by real time PCR (qpcr) Brix, acid, ratio, pieces per box: plant data Electronic tongue Week of crop (December 1 used as starting point for week calculation) Principal Component Analysis 15

12 Electronic tongue 7 Electronic sensors Sensors map to sensory descriptors Sourness Metallic Saltiness Umami Spiciness Sweetness Bitterness Can be calibrated to standards (if available) 16

13 Principal Component Analysis Principal component analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. 17

14 Principal Component Analysis Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset. It's often used to make data easy to explore and visualize. Is a variable reduction technique Is used when variables are highly correlated Reduces the number of observed variables to a smaller number of principal components which account for most of the variance of the observed variables The first principal component accounts for most of the variance in the data. The second component accounts for the second largest amount of variance in the data and is uncorrelated with the first principal component, and so on. In PCA, observed variables are standardized, e.g. mean = 0 18

15 Correlation Matrix E/M Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset. It's often used to make data easy to explore and visualize. Variables SRS GPS STS UMS SPS SWS BRS Acid Brix Ratio Pcs/Box Limonin Nomilin Ct Week SRS GPS STS UMS SPS SWS BRS Acid Brix Ratio Pcs/Box Limonin Nomilin Ct Week Values in bold are different from 0 with a significance level alpha=

16 Principal Component Analysis Principal component analysis (PCA) is a technique used to emphasize variation and bring out strong patterns in a dataset. It's often used to make data easy to explore and visualize. 20

17 Week of Crop Early Mids 12/9/2014 2/5/

18 Early Mids All weeks Initial PCA looked at all parameters and then re-ran with only those parameters that were most important in the first two components Used a threshold of 0 on the first component and grouped in to two categories Worse (high lim/nom, low Ct) Better (low lim/nom, high Ct) Low Lim/Nom High Ct Better High Lim/Nom Low Ct Worse 22

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21 Why are the Worse E/M s skewed to the front of the crop If you had two blocks, one with excessive drop and one without, which would you pick first? 25

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23 December 2, 2014, 3 replications, 3 tree plots, 5 treatments: Healthy tree, Healthy shaken left on tree, healthy shaken on ground, infected shaken on tree, infected shaken on ground

24 December 2, 2014, 3 replications, 3 tree plots, 5 treatments: Healthy tree, Healthy shaken left on tree, healthy shaken on ground, infected shaken on tree, infected shaken on ground

25 December 2, 2014, 3 replications, 3 tree plots, 5 treatments: Healthy tree, Healthy shaken left on tree, healthy shaken on ground, infected shaken on tree, infected shaken on ground Healthy Unshaken Healthy Tree Healthy Ground HLB Tree HLB Ground P-value Plotto/Baldwin Orange 4.4 a 4.5 a 3.8 b 3.1 c 2.1 d < Grapefruit 2.9 c 2.5 c 2.5 c 4.4 b 5.9 a < Fruity-non-citrus 1.8 a 1.7 ab 1.4 bc 1.1 c 1.1 c Orange peel 2.3 b 2.1 b 2.0 b 2.5 ab 2.9 a Green 2.4 b 2.4 b 2.4 b 2.8 ab 3.1 a Stale 2.4 b 2.6 b 2.6 b 3.3 ab 4.1 a Oxidized oil 1.6 b 1.6 b 1.5 b 2.2 ab 2.7 a Typical HLB 4.1 c 4.0 c 4.3 c 7.6 b 10.2 a < Sweetness 5.5 a 5.1 ab 4.6 b 4.1 c 3.2 d < Sourness 5.0 ab 4.6 b 4.8 b 5.2 ab 5.6 a 0.04 Umami 2.3 b 2.2 b 2.4 b 2.8 ab 3.4 a Bitterness 4.1 c 3.1 c 3.4 c 7.1 b 9.3 a < Metallic 2.4 c 2.0 c 2.1 c 3.1 b 4.3 a < Body 4.9 a 4.5 ab 4.3 b 4.4 ab 4.7 ab Tingling 1.8 bc 1.6 c 1.5 c 2.3 ab 2.7 a Astringent 2.3 b 1.8 b 2.1 b 3.4 a 3.9 a < Burning 1.4 b 1.2 b 1.2 b 2.1 a 2.5 a AfterBitter 2.0 c 1.6 c 2.0 c 4.5 b 6.0 a < AfterAstringent 1.3 b 1.3 b 1.1 b 2.6 a 3.1 a < AfterBurning 0.8 bc 0.6 c 0.8 bc 1.3 ab 1.7 a 0.001

26 Valencia All Weeks High Lim/Nom Low Ct Worse Low Lim/Nom High Ct Better March 2,2015 May 5,

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30 So how can this approach be used to manage the harvest? Used the same basic PCA approach but basically did it in 2-3 weeks where possible Where not possible to group, looked at individual weeks Used the same basic Better / Worse threshold approach for the component that explained the Ct and Lim/Nom variability Group 1 = Better Group 2 = Worse Averaged the Group rating by grower 3 Categories Better (<1.4) = Green OK (>1.4 <1.6) = Yellow Worse (>1.6) = Red 34

31 Early/Mids 35

32 Valencia 36

33 Combined Quality (as defined by the PCA analysis using Ct and Lim/Nom as the criteria for grouping) appears to vary by grower Consistent during the season Consistent between varieties Going forward Need to go down another level (grove) to see if there are consistent differences there Need to go compare a couple of years to see if the trends are consistent 37

34 Conclusions Although no one parameter by itself is sufficient to measure quality, PCA using a combination of wet chemistry, electronic tongue (as a proxy for sensory), and molecular technologies appears promising as a means of evaluating quality Ct may be a rough indicator Quality (as it relates to HLB associated off flavors) appears to vary by grower Harvesting patterns could potentially affect quality Incentives are opposite 38

35 Thank You / Questions? 39

36 Quick Update on the Southern Gardens GMO Trials M Irey, R Kress, G Thelwell, J Kurimai, J Snively, R Terra, B Ingram

37 Upon the discovery of HLB, Southern Gardens decided to: Use the opinions of the best experts available 3 pronged approach Open our diagnostic lab to the industry at no cost Now partially funded by CRDF Work with Federal, State and private researchers to develop solutions Establish our own projects to develop a long term solution to HLB Multiple partners Multiple projects Multiple approaches 41

38 Southern Gardens Research Texas A & M University Disease resistant plants Integrated Plant Genetics Disease resistant plants Cornell University Insect resistant plants AgroMed LLC Identification of synthetic resistance genes University of Florida Gene delivery system USDA Screening of potential genes, juice quality 42

39 Transgenic Trees Stable integration-long term Multiple projects Antimicrobial peptides Integrated Plant Genetics Gene from a bacteriophage Agromed Synthetics Texas A & M Spinach defensins (multiple) Resistance to ACP Cornell Hirsutellin Lectins 43

40 Transgenic Trees Ideally, looking for immunity Process involves screening many lines (200+) Testing Greenhouse Field Field testing is done under USDA-APHIS-BRS permits 3 years Defined conditions EPA and FDA not involved in permitting (unless EUP is required) 44

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45 Transgenic Rohde Red Val Non-transgenic Rohde Red Val

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49 Texas Project Spinach defensins Has been a learning curve Generations 1, 2, 3, 4, 5,.. Multiple genes With and without signal peptides Different codon optimizations schemes Corrected sequences Alone or stacked All trees created in Texas at Texas A & M, Weslaco by Dr. Erik Mirkov Hamlin, Valencia, Lemons, Mexican Lime, Grapefruit, rootstocks 53

50 Texas Project FDACS Regulatory Process Since trees were created in Texas, they were subject to CGIP Issues: Time delay Overloading of the system» Would not be a good use of FDACS resources given that the majority of the lines would not make it (200+ lines and more still coming) Over time and multiple iterations, a system was developed that worked Protected the Florida industry Allowed us to move material to Florida 54

51 So where are we with the deregulation process - EUP EUP- allows for greater than 10ac of trials For the transgenic tree defensin project, we have an EUP that allows: 400 ac in Florida 200 ac in Texas Two defensins 4 Plant lines 2 Sweet Oranges 1 Grapefruit 1 Lemon 55

52 Temporary Tolerance Exemption Temporary tolerances are granted by the EPA to allow holders of an EUP to use the products that come off the trials in the EUP A petition for a temporary tolerance or an exemption must be submitted with the application for the EUP (if not a crop destruct) In the case of spinach defensins in transgenic trees, a tolerance exemption was granted Based on the data that was submitted, there were no toxicity issues Already in the food chain 56

53 Going forward.. We have many more lines being tested and it is likely that we may have lines better than those in the current EUP The EUP process is: Tedious Costly Takes time Is restrictive Specific lines Specific constructs 57

54 Going forward.. Have a new EUP amendment submission Multiple events (i.e. not restricted to 4 lines) as long as they were restricted to certain constructs First step towards a by construct approach This will be necessary going forward In the process of: EUP for spinach defensin using viral vector Temporary tolerance for 3 spinach defensins in CTV Temporary tolerance for all spinach defensins 58

55 Other efforts Global approval Have started the process to determine the landscape for approval of a transgenic tree-based commercialization of spinach defensins 5 key markets in addition to the US Canada Japan Korea Israel EU 59

56 Other efforts Also working on: Consumer acceptance Proactively to improve general acceptance Consumers Retailers Legal preparation for the eventual law suits Freedom to operate Stewardship issues Defensins plus Second mode of action 60

57 Thank you (again..) / Questions 61