February 3, 2023

Publications 2022

Publications acknowledging WheatCAP support

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  1. Alarcón-Reverte R, Xie Y, Stromberger J, Cotter JD, Mason RE, Pearce S (2022) Induced mutations in ASPARAGINE SYNTHETASE-A2 reduce free asparagine concentration in the wheat grain. Crop Science 62:1484–1496. https://doi.org/10.1002/csc2.20760 
  2. Baenziger PS, Frels KA, Boehm J, Belamkar V, Rose DJ, Xu L, Wegulo SN, Regassa T, Easterly AC, Creech CF, Santra DK, Klein RN, Jin Y, Kolmer J, Chen MS, Guttieri MJ, Bai G, El-Basyoni Salah I, Masterson SD, Poland J (2022) Registration of ‘Epoch’ hard red winter wheat. Journal of Plant Registrations 16:613–621. https://doi.org/10.1002/plr2.20247 
  3. Chen H, Su Z, Tian B, Liu Y, Pang Y, Kavetskyi V, Trick HN, Bai G (2022) Development and optimization of a Barley stripe mosaic virus-mediated gene editing system to improve Fusarium head blight resistance in wheat. Plant Biotechnology Journal 20:1018–1020. https://doi.org/10.1111/pbi.13819 
  4. Chen H, Su Z, Tian B, Hao G, Trick HN, Bai G (2022) TaHRC suppresses the calcium-mediated immune response and triggers wheat Fusarium head blight susceptibility. Plant Physiology 190:1566–1569. https://doi.org/10.1093/plphys/kiac352 
  5. Chen Y, Liu Y, Zhang J, Torrance A, Watanabe N, Adamski NM, Uauy C (2022) The Triticum ispahanicum elongated glume locus P2 maps to chromosome 6A and is associated with the ectopic expression of SVP-A1. Theor Appl Genet 135:2313–2331. https://doi.org/10.1007/s00122-022-04114-y 
  6. Chu C, Wang S, Rudd JC, Ibrahim AMH, Xue Q, Devkota RN, Baker JA, Baker S, Simoneaux B, Opena G, Dong H, Liu X, Jessup KE, Chen MS, Hui K, Metz R, Johnson CD, Zhang ZS, Liu S (2022) A new strategy for using historical imbalanced yield data to conduct genome-wide association studies and develop genomic prediction models for wheat breeding. Mol Breeding 42:18. https://doi.org/10.1007/s11032-022-01287-8 
  7. Dang C, Zhang J, Dubcovsky J (2022) High-resolution mapping of Yr78, an adult plant resistance gene to wheat stripe rust. The Plant Genome, 15: e20212. https://doi.org/10.1002/tpg2.20212 .
  8. Debernardi JM, Woods DP, Li K, Li C, Dubcovsky J (2022) MiR172-APETALA2-like genes integrate vernalization and plant age to control flowering time in wheat. PLoS Genetics, 18: e1010157. https://doi.org/10.1371/journal.pgen.1010157.
  9. DeWitt N, Guedira M, Murphy JP, Marshall D, Mergoum M, Maltecca C, Brown-Guedira G (2022) A network modeling approach provides insights into the environment-specific yield architecture of wheat. Genetics 221(3) iyac076. https://doi.org/10.1093/genetics/iyac076
  10. Fan M, Zhang X, Nagarajan R, Fan M, Zhang X, Nagarajan R, Zhai W, Rauf Y, Jia H, Ma Z, Yan LL (2022) Natural variants and editing events provide insights into routes for spike architecture modification in common wheat. The Crop Journal. https://doi.org/10.1016/j.cj.2022.04.009 
  11. Gill HS, Halder J, Zhang J, Rana A, Kleinjan J, St. Amand P, Bernardo A, Bai G, Sehgal SK (2022) Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits. Theor Appl Genet 135:2953–2967. https://doi.org/10.1007/s00122-022-04160-6 
  12. Glenn P, Zhang J, Brown-Guedira G, DeWitt N, Cook JP, Li K, Akhunov E, Dubcovsky J (2022) Identification and characterization of a natural polymorphism in FT-A2 associated with increased number of grains per spike in wheat. Theor Appl Genet 135:679-692. https://doi.org/10.1007/s00122-021-03992-y 
  13. He F, Wang W, Rutter WB, KW Jordan, Ren J, Taagen E, DeWitt N, Sehgal D, Sukumaran S, Dreisigacker S, Reynolds M, Liu S, Chen J, Fritz A, Cook J, Brown-Guedira G, Pumphrey M, Carter A, Sorrells M, Dubcovsky J, Hayden MJ, Akhunova A, Morrell PL, Szabo L, Rouse M, Akhunov E (2022) Genomic variants affecting homoeologous gene expression dosage contribute to agronomic trait variation in allopolyploid wheat. Nat Commun 13:826. https://doi.org/10.1038/s41467-022-28453-y 
  14. Jiang D, Hua L, Zhang C, Li H, Wang Z, Li J, Wang G, Song R, Shen T, Li H, Bai S, Liu Y, Wanga J, Li H, Dubcovsky J, Chen S 2022. Mutations in the miRNA165/166 binding site of the HB2 gene result in pleiotropic effects on morphological traits in wheat. The Crop Journal. Online first. https://doi.org/10.1016/j.cj.2022.05.002 .
  15. Kissing Kucek L, Dawson JC, Darby H, Mallory E, Davis M, Sorrells ME (2021) Breeding wheat for weed-competitive ability: II–measuring gains from selection and local adaptation. Euphytica 217:203. https://doi.org/10.1007/s10681-021-02905-w 
  16. Kissing Kucek L, Mallory EB, Darby HM, Dawson JC, Sorrells ME (2021) Breeding wheat for weed-competitive ability: I. Correlated traits. Euphytica 217:202. https://doi.org/10.1007/s10681-021-02930-9 
  17. Kuzay S, Lin H, Li C, Chen S, Woods D, Zhang J, Dubcovsky J (2022) WAPO-A1 is the causal gene of the 7AL QTL for spikelet number per spike in wheat. PLOS Genetics 18:e1009747. https://doi.org/10.1371/journal.pgen.1009747 
  18. Larkin DL, Mason RE, Moon DE, Holder AL, Ward BP, Brown-Guedira G (2021) Predicting Fusarium Head Blight Resistance for Advanced Trials in a Soft Red Winter Wheat Breeding Program With Genomic Selection. Frontiers in Plant Science 12. https://doi.org/10.3389/fpls.2021.715314 
  19. Li H, Zhang F, Zhao J, Bai G, St. Amand P, Bernardo A, Ni Z, Sun Q, Su Z (2022) Identification of a novel major QTL from Chinese wheat cultivar Ji5265 for Fusarium head blight resistance in greenhouse. Theor Appl Genet 135:1867–1877. https://doi.org/10.1007/s00122-022-04080-5 
  20. Lopez SR, Wiersma AT, Strauss NM, Watkins T, Baik BK, Zhang G, Sehgal SK, Kolb FL, Poland JA, Mason RE, Carter AH, Olson EL (2022) Description of U6719-004 wheat germplasm with YrAS2388R stripe rust resistance introgression from Aegilops tauschii. Journal of Plant Registrations: https://doi.org/10.1002/plr2.20226 
  21. Luo J, Rouse MN, Hua L, Li H, Li B, Li T, Zhang W, Gao C, Wang Y, Dubcovsky J, Chen S (2022). Identification and characterization of Sr22b, a new allele of the wheat stem rust resistance gene Sr22 effective against the Ug99 race group. Plant Biotechnology Journal. 20: 554–563. https://doi.org/10.1111/pbi.13737.
  22. Morales N, Ogbonna AC, Ellerbrock BJ, Bauchet GJ, Tantikanjana T, et al. (57 co-authors including Jean-Luc Jannink, Clay Birkett, and David Waring) 2022. Breedbase: a digital ecosystem for modern plant breeding. G3. https://doi.org/10.1093/g3journal/jkac078 
  23. Moriconi JI, Silva M, Zhang J, Tranquilli GE, Santa-María GE (2022) A genome-wide association study unveils key chromosome regions involved in determining sodium accumulation in wheat under conditions of low potassium supply. Journal of Plant Physiology 275:153739. https://doi.org/10.1016/j.jplph.2022.153739 
  24. Peters Haugrud AR, Zhang Q, Green AJ, Xu SS, Faris JD (2022) Identification of stable QTL controlling multiple yield components in a durum × cultivated emmer wheat population under field and greenhouse conditions. G3 Genes|Genomes|Genetics jkac281. https://doi.org/10.1093/g3journal/jkac281 
  25. Prather S, Schneider T, Gaham Godoy J, Odubiyi S, Bosque-Perez NA, Rashed A, Rynearson S, Pumphrey MO (2022) Reliable DNA Markers for a Previously Unidentified, Yet Broadly Deployed Hessian Fly Resistance Gene on Chromosome 6B in Pacific Northwest Spring Wheat Varieties. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.779096 
  26. Rivera-Burgos LA, Brown-Guedira G, Johnson J, Mergoum M, Cowger, C (2022) Accounting for heading date gene effects allows detection of small-effect QTL associated with resistance to Septoria nodorum blotch in wheat. PloS one 17(5) e0268546.
  27. Rooney TE, Kunze KH, Sorrells ME (2022a) Genome-wide marker effect heterogeneity is associated with a large effect dormancy locus in winter malting barley. The Plant Genome:e20247. https://doi.org/10.1002/tpg2.20247 
  28. Rooney TE, Sweeney DW, Sorrells ME (2022b) Time series barley germination is predictable and associated with known seed dormancy loci. Crop Science 62:100–119. https://doi.org/10.1002/csc2.20638 
  29. Sandhu KS, Merrick LF, Sankaran S, Zhang Z, Carter AH (2022) Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs. Frontiers in Genetics 12. https://doi.org/10.3389/fgene.2021.829131 
  30. Sandhu KS, Mihalyov PD, Lewien MJ, Pumphrey MO, Carter AH (2021) Genomic Selection and Genome-Wide Association Studies for Grain Protein Content Stability in a Nested Association Mapping Population of Wheat. Agronomy 11:2528. https://doi.org/10.3390/agronomy11122528 
  31. Sandhu KS, Patil SS, Aoun M, Carter AH (2022) Multi-Trait Multi-Environment Genomic Prediction for End-Use Quality Traits in Winter Wheat. Frontiers in Genetics 13. https://doi.org/10.3389/fgene.2022.831020 
  32. Sandro P, Kucek LK, Sorrells ME, Dawson JC, Gutierrez L (2022) Developing high-quality value-added cereals for organic systems in the US Upper Midwest: hard red winter wheat (Triticum aestivum L.) breeding. Theor Appl Genet. https://doi.org/10.1007/s00122-022-04112-0 
  33. Sweeney DW, Kunze KH, Sorrells ME (2022) QTL x environment modeling of malting barley preharvest sprouting. Theor Appl Genet 135:217–232. https://doi.org/10.1007/s00122-021-03961-5 
  34. Sweeney DW, Rooney TE, Sorrells ME (2021) Gain from genomic selection for a selection index in two-row spring barley. The Plant Genome 14:e20138. https://doi.org/10.1002/tpg2.20138 
  35. Sweeney DW, Rooney TE, Walling JG, Sorrells ME (2022) Interactions of the barley SD1 and SD2 seed dormancy loci influence preharvest sprouting, seed dormancy, and malting quality. Crop Science 62:120–138. https://doi.org/10.1002/csc2.20641 
  36. Taagen E, Jordan K, Akhunov E, Sorrells ME, Jannink JL (2022) If It Ain’t Broke, Don’t Fix It: Evaluating the Effect of Increased Recombination on Response to Selection for Wheat Breeding. G3 Genes|Genomes|Genetics jkac291. https://doi.org/10.1093/g3journal/jkac291 
  37. Venegas J, Guttieri MJ, Boehm Jr. JD, Graybosch R, Bai G, St. Amand PC, Palmer N, Hussain W, Blecha S, Baenziger PS (2022) Genetic architecture of the high-inorganic phosphate phenotype derived from a low-phytate mutant in winter wheat. Crop Science 62:1228–1241. https://doi.org/10.1002/csc2.20738 
  38. Wu J, Qiao L, Liu Y, Fu B, Nagarajan R, Rauf Y, Jia H, Yan LL (2022) Rapid identification and deployment of major genes for flowering time and awn traits in common wheat. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.992811 
  39. Xu Y, La G, Fatima N, Liu Z, Zhang L, Zhao L, Chen MS, Bai G (2021) Precise mapping of QTL for Hessian fly resistance in the hard winter wheat cultivar ‘Overland.’ Theor Appl Genet 134:3951–3962. https://doi.org/10.1007/s00122-021-03940-w 
  40. Zhang G, Martin TJ, Fritz AK, Li Y, Seabourn BW, Chen RY, Bai G, Bowden RL, Chen M-S, Rupp J, Jin Y, Chen X, Kolmer JA, Marshall DS (2022) Registration of ‘KS Hamilton’ hard red winter wheat. Journal of Plant Registrations 16:73–79. https://doi.org/10.1002/plr2.20190 
  41. Zhang J (2022) Check CRISPR editing events in transgenic wheat with next-generation sequencing. In: Wani SH, Kumar A (eds) Genomics of Cereal Crops. Springer US, New York, NY, pp 95–106
  42. Zhang J, Gill HS, Brar NK, Halder J, Ali S, Liu X, Bernardo A, St. Amand P, Bai G, Gill US, Turnipseed B, Sehgal SK (2022) Genomic prediction of Fusarium head blight resistance in early stages using advanced breeding lines in hard winter wheat. The Crop Journal. https://doi.org/10.1016/j.cj.2022.03.010 
  43. Zhang J, Gill HS, Halder J, Brar NK, Ali S, Bernardo A, St. Amand P, Bai G, Turnipseed B, Sehgal SK (2022) Multi-locus genome-wide association studies to characterize Fusarium Head Blight (FHB) resistance in Hard Winter Wheat. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.946700 
  44. Zhang L, Xu Y, Chen M-S, Su Z, Liu Y, Xu Y, La G, Bai G (2022) Identification of a major QTL for Hessian fly resistance in wheat cultivar ‘Chokwang.’ The Crop Journal 10:775–782. https://doi.org/10.1016/j.cj.2021.08.004 
  45. Zhang XY, Jia HY, Li T, Wu JZ, Nagarajan R, Lei L, Powers C, Kan CC, Hua W, Liu ZY, Chen C, Carver BF, Yan LL (2022) TaCol-B5 modifies spike architecture and enhances grain yield in wheat. Science 376:180–183. https://doi.org/10.1126/science.abm0717 
  46. Zhao L, Ge W, Lyu Z, Xu S, Xu Y, Bernardo A, Zhang Q, Xu S, Wang H, Kong L, Bai G (2022) Development and validation of diagnostic markers for the wheat Fusarium head blight resistance gene Fhb7. Crop Science 62:1903–1911. https://doi.org/10.1002/csc2.20754 
  47. Zhao L, Su P, Hou B, Wu H, Fan Y, Li W, Zhao J, Ge W, Xu S, Wu S, Ma X, Li A, Bai G, Wang H, Kong L (2022) The Black Necrotic Lesion Enhanced Fusarium graminearum Resistance in Wheat. Frontiers in Plant Science 13. https://doi.org/10.3389/fpls.2022.926621

Ten basic advices for positional cloning

Contributed by Jorge Dubcovsky
  1. Spend some time identifying the conditions were the differences between for HIFs show maximum difference. For spikelet number photoperiod and temperature seem essential. We have found with Saarah that the differences are very compressed when we grow things in the GH in the summer… If you find a GH or chamber condition where you can differentiate your HIFs you will accelerate your project several years! If you depend on the field, do multiple environments, and try to identify the ones that are more reproducible. Always include several homozygous A and homozygous B as controls to be sure that the phenotype is visible in that environment.
  2. Do enough replications in the progeny tests to Mendelize the phenotype. For the GPC-B1 we used 20 reps in the field, for the Rht18 we are using 100 plants in the field.
  3. Adjust the number of segregating lines you study for recombination to get a manageable number of recombinants in each stage. If your interval is 5 cM you will have 10 recombinants per 100 F2. If you can handle 50 recombinants go for 500 F2. The number you can handle depends on the size of the Progeny Tests you need to run to get a clear Mendelian phenotype. Do the mapping in Phases. After a good mapping of this first 50 recombinant you can probably reduce the interval to 0.5 cM, so now to get 50 recombinants again you need to screen 5000 F2…
  4. It is more important to have a few crossovers you are 100% sure, than a lot of recombination events that you are not certain. It is better to move at slower pace but with certainty. If you make a mistake in 1 crossover, you may end up walking in the wrong direction for a couple of years ( I did this twice!).
  5. Positional cloning is not about measuring a large number of plants and running a QTL program. It is about cutting the region with crossovers and being 100% certain of the location of the phenotype relative to each of these recombination events. Do progeny tests of the size that need to be done to reduce the environmental variation to a point that you can determine the phenotype as a clear A, H or B allele. For each progeny test run an ANOVA using the genotypic data, if you have a significant segregation then it is an H. If no segregation is A or B. If you P values are between 0.4 and 0.12 repeat the experiment! You need to be certain.
  6. The secret of positional cloning is to do your genetics well (PERFECTLY WELL I would say)
  7. To reduce the genotypic variation, the more advance the HIF the cleaner the data. If you start with an F5 looking for recombinants, next generation  use the F6 HH to generate new and more advance HIFs, repeat each generation to keep purifying the genetic background.
  8. If you are generating HIFs from an early generation, test 3-5 HIF families to see if there is a specific background where the differences are more evident. Then move ahead using that family. THERE ARE MULTIPLE EPISTATIC INTERACTIONS WE DO NOT KNOW. Your phenotype may be visible in one background but not in another one. You need to figure that out early on the game.
  9. Genetic variability is  reduced  by sellfing or backcrossing, environmental variability is reduced by replication number in the PT.
  10. Use the resources  we are providing. By now Eduard Akhunov has sequenced all the parental lines by EXOME CAPTURE. Jean Luc is working on tools to mine this data but you can get the raw data and do your analyses. Developing markers in the region is no longer a limitation!!!!


Spectral Canopy Reflectance


04/04/2011 – 09:41 — Dubcovsky – Welcome to the Canopy Spectral Reflectance (CSR) forum, a support tool to the CSR Workshop that will be held in Denver, CO on April 8, 2011.  You are invited to browse the contents of this forum. To make comments or start a new topic thread, you have to request permission.

04/11/2011 – 19:48 — Dubcovsky -Here you have two more presentations (PDF) with instructions for using the Jaz:

04/11/2011 – 21:09 — Dubcovsky – Here you a procedure on how to make a low cost reflectance standard with barium sulphate and white paint. Prepared by Nick Knighton and Bruce Bugbee.

04/12/2011 – 05:08 — mgttri  I have been working some with Unscrambler from Camo in doing NIR work. The Vers 9 is miserable for data organization, but Vers X is a wonderful creation.


This is very powerful software for multivariate analysis of spectral data and may be helpful on this project. Understand that I am SAS user from back in the DOS days, and I do all the standard analyses of variance in SAS very comfortably, but my graphical skills in SAS are very limited– therefore I appreciate the graphical capabilities of this software, particularly given that we are working with spectral data.  The project will generate far more data than we can maintain in Excel and the programming to utilize the data effectively within a database may be more than we want to invest in. If all that the project intends to do is use previously reported indices, this kind of software would not be as helpful. But if the project intends to do more with the data- to use all the data that the Jaz will generate- this kind of software could be helpful. This is not the such software available to us- it is one that I came to via Perten Instruments. There is a 30 – day trial download of Vers X, and Camo does do some generous academic discounting.  Mary

Boxcare Smoothing
04/13/2011 – 14:16 — Tyson Howell – Hello all, I have done some preliminary analysis using the boxcar setting on our Jaz unit, and a comparison of that to a smoothing of the raw data done in excel. I am attaching an excel sheet to this post so that you can look at the data yourself if you would like. I used two different methods for boxcar smoothing in Excel, named “Excel boxcar 5” and “Excel boxcar 10”. The two sizes were used because I was not sure of the exact definition of boxcar width, i.e. whether boxcar 10 meant 10 pixels total, or 10 each side (21 total) of the pixel of interest. Based on this analysis I am confident it is the latter. The spectrum of the Jaz values for boxcar 10 looks very close to the spectrum for excel boxcar 10, in which I took the target pixel + 10 pixels from either side (for a total of 21 pixels). The excel boxcar 5 spectrum (11 pixels total) looks quite different, intermediate between no smoothing and the Jaz boxcar 10 smoothing.  Areas of high standard deviation are centered around the reflectance peaks (see graph in sheet “graph” in attachment. peaks are around 544 and 613nm). Despite the differences in the standard deviation, the % difference between the two methods is low (<2.5% for all but 3 points, located near the very end of the spectrum where we know it is more variable anyway). Higher standard deviations are expected in areas of higher intensity. The basic shapes of the spectra from each of the smoothing methods is mostly similar (peaks in the same places), but there is some change in the relative heights of the two main peaks. When no boxcar smoothing is used, the second (and more narrow) main peak present is of the highest intensity, while when using a boxcar smoothing width of 10, the first (and broader) main peak is the highest in intensity. Using excessively high boxcar widths will reduce the intensity of sharp peaks much faster than that of wide peaks (This is why it helps with reducing noise, but it may also result in data loss if smoothing is used aggressively). We may want to retain some of the smaller peaks, particularly if we will be developing new indices. We feel it would be good practice to keep the amount of initial (on the Jaz unit) boxcar smoothing low, probably a boxcar of 1 or 2 which would average the values over approximately .5 to .75nm depending on the part of the spectrum (a boxcar of 2 would average values over ~1-1.5nm). This would allow for some noise reduction in the spectrum without any additional processing, but would also allow us to apply further smoothing at a later stage if it was deemed necessary. I will also look into the effects of taking variable numbers of averages. This boxcar analysis was done by pointing the jaz unit at a colored piece of paper in my office (to get the highest amount of consistency between reads, reducing the amount of variation do to light fluctuations rather than boxcar smoothing methods). I will do the averaging tests either on grass or wheat plots outside to get a better idea of how averaging affects variation on actual plants though. I have so far established that the amount of time it takes for a read is mainly dependent upon the integration time, which will be variable depending on the amount of light (i.e. taking measurements will take longer on a cloudy day than a sunny day). In my office it took approx 7 seconds to take reads with an averaging value of 100, corresponding to 70ms for each averaged read, so averaging excessively large numbers of reads will be prohibitive, and may even lead to errors if the fiber optic cable is moved during that time.  The file is too big in .xls format and I cannot upload .xlsx files to this forum, so below is a link to the file. Please let me know if anyone has problems accessing it.

Height/Area Calculation
04/13/2011 – 04:31 — mgttri  – Would whoever has the spreadsheet that does the measurement height vs area calculation please post that spreadsheet so that we all have access to it?We need to resolve a measurement height, in part because this will set a minimum lateral distance from any support that we use to hold the sensors. Thanks, Mary

Measurement height and spot diameter
04/18/2011 – 13:30 — Tyson Howell – Attached is an excel file containing the values for the distance of the fiber optic to the target (reference/sample) and the corresponding spot diameter. For those of you that would like to calculated this yourself, this is the information we received from the Ocean Optics representative:

The equation for getting the spot size at a given distance to the ground is tan Ø = x/y; where y is the distance to the ground & x = y tan 12.7. For example, the half angle of the fibers FOV is 12.7, take that 30cm above the ground tan Ø = X/30 –> 30 tan 12.7=x –> x=6.76 –> 13.5cm.

Jaz configuration
04/29/2011 – 08:56 — Tyson Howell – Hello all, We have had a bit of time to play with our Jaz unit, and have some things we do and do not recommend purchasing for when you are trying to put together your order. If you use the Dubcovsky invoice to order your JAZ modify the following:

QP600-2-VIS-BX (the fiber optic of 600) is too big and it saturates. We replaced it for a QP200-2-VIS-BX (we use a 100um for down-welling and 200um for up-welling). We also have a 400um cable, it saturates during sunny days though. Integration time can always be increased on days with less light (up to 56s), but can only be reduced to a minimum of about 2 ms on sunny days.

WS-1-SL Diffuse Reflectance Std, Spectralon 0. ELIMINATE. It is just a few cm wide so useless. The control needs to have the same size of the measurement. We ordered the Barium Sulfate and we will see if we can prepare white surfaces for the rest…We are using a white cardboard (foam core) meanwhile… This saves you $340

JAZ-SPL Scripting Language. WE are still not sure if it is useful. You can order it later, not now  INTSMA-050 Interchangeable. . ELIMINATE. It is too big for the level of radiation we have Spectrasuite software. We have yet to use this software since we are doing all of our data collection away from a computer, it may be helpful for visualizing data later though. Thus far we have been fine using excel.  Let us know if there are any additional questions.

Jaz specifications
06/03/2011 – 11:13 — Tyson Howell – There have been several questions regarding Jaz specifications. Below is a link to our order invoice, detailing what we ordered for our drought CSR work.

Dubcovsky Lab Jaz Invoice

Some notes/recommendations:  We ordered grating #4 for both of our channels, which is ideal for our water indices and vegetative index estimators. You may want a different grating depending on your application (e.g. grating #3 for Nitrogen measurement)

We have two spectrometer channels to measure reflected as well as incoming light. We are looking into using the incoming light information to correct reflectance values, but we still have significant results without this correction so two channels may be of limited use (unless you plan to take water and nitrogen measurements simultaneously, it may be useful to have two channels, each with a different grating). You will only need the CC3 cosine corrector if you are going to be taking downwelling measurements.  Thus far, we haven’t found any of the software we purchased to be essential, or even particularly useful. We have had no problems doing our data analysis in excel. Regarding the JSL scripting language, it seems that we can distribute the scripting engine (that must be loaded onto the Jaz) along with any programs we may send out, so we would recommend against purchasing that. We have not used the spectra suite software, it seems more oriented towards using the Jaz in a lab, it doesn’t seem critical for the viewing or analysis of our field data.  We have not used the external battery that we ordered, the amount of time that the sun is in an optimal position throughout the day is less than the life of the battery. The Jaz pack is useful, it has a nice little shade cover on it so that you can actually see the screen outside (it is VERY hard to see the screen when it is in direct sunlight). It is also nice to have a case so that you don’t get the spectrometer dirty, and it has a neck strap so that you don’t drop it. The core fiber diameters on our invoice are for 400 and 600 um, but these let in far too much light. We have been using a 100um core diameter for downwelling measurements and a 200 um core diameter for upwelling measurements, and that seems to be working well so far. We recommend the more expensive fibers with the metal jacketing. The spectralon reference standard is pretty much useless, it is far too small for our purposes, we do not recommend purchasing it. I think that’s about it, let me know if there are any questions or comments. -Tyson

White reference plate (Barium Sulphate)
04/11/2011 – 13:25 — kiran – Hello, I would like to know how to procure Barium sulphate white reference plates for our research on CSR… I appreciate if any body gives their ideas or experiences…. Kiran

Jaz menu walk-through
06/07/2011 – 15:09 — Tyson Howell – Several people have asked me for a walkthrough of the jaz menus, which can be somewhat daunting the first couple of times you do it since there are so many things you need to set up before you can start taking measurements. I created a few slides walking through the menus, as well as a summary at the end that you can copy to a word  document and print out for reference if you would like. Hope this is helpful, let me know if anyone has any questions or sees any errors. I may update this with some more info when I have the time.  jaz menu walk-through

Pole Ideas for suspending the optical fibers above the plot and materials used to build it.
05/10/2011 – 06:25 — jwheeler1976 – Have we figured out a system to suspend the optical fibers onto some type of adjustable pole?  I know that we kind of drew some basic ideas, but has anyone actually constructed the adjustable pole.  If so, what materials were used and where can I purchase them to build it myself.

Jaz data parser
08/10/2011 – 10:02 — Tyson Howell – One of our PhD students here, Iago Lowe, has written a perl script to parse the standard output from the jaz unit. You will need to install ActivePerl (free) on your computer to run the scripts. Please read the documentation before using.


Jaz Scripting Language (JSL) program for 2-channel jaz
04/27/2011 – 13:43 — Tyson Howell – Hello all, While working with JSL to write a program which would allow us to take measurements from both upwelling and downwelling channels simultaneously, I encountered some problems with the scripting language. It seems that JSL has very limited file handling capabilities, which means we may or may not be able to actually use the scripting language for our purposes. I emailed Ocean Optics, and received this response: “You cannot change the name of a file out side of the variables declaration area. That is one major limitation of JSL…JSL wants to know all file names up front and does not let you name them dynamically…. I don’t know if readrealvector or readtable will work for this….the JSL file related functions were more geared to spectral data and saving results, not for reading configurations or data in…. You could try just writing out a single value to a file, that should work. then you could try reading it back as an array of one(1) value….that might work. But it is not very pretty….or easy to do….When JSL does an Open file it basically recreates the file for you for your convenience….

JSL was not written to do too much with files …especially not folders and the likes of that kind of complexity.

I really don’t think that there is a good way to do this that I could guarantee works… I know this is not the answer you want to hear…BUT, JSL just does not have the functionality for this sort of thing..  Sorry.”   There may still be one option that will work, I will update you once I find out. If we cannot track file names, however, there is no way to prevent the Jaz unit from overwriting old files each time it is turned off and then back on, which is a huge problem.

Keep in mind, this only pertains to the scripting language. We can still use the Jaz in its default mode, but it may be somewhat cumbersome. I will keep you updated.  -Tyson