Plant Phenotyping Resources
The open access, world-class capabilties of the APPF have become an essential resource for plant scientists all over the world.
As one of the first plant phenotyping facilities worldwide, the APPF has been a pioneer in developing and providing plant phenotyping technologies in since 2010. Using a multi-disciplinary approach, we have designed and commissioned complex phenotyping platforms for use in controlled environments and in the field, software to facilitate data management, analysis and visualisation, and developed extensive technical experience, to undertake large-scale phenomics studies.
By sharing our resources and knowledge, the APPF enables plant scientists to investigate plant performance at a scale and level of detail not previously possible, accelerating research outcomes to lead to new discoveries, and contributing to Australia’s reputation as a world-class leader in innovative agricultural science.
Our resources page is organic and will continue to grow and evolve as we develop, innovate and discover new software technologies and educational tools.
Brochures and Fact Sheets
Our brochures, technology fact sheets and corporate publications are available to download. You will also find the fact sheets in their relevant section on our Technology page. If you have any questions, or need any further information, just contact us – we’d love to help!
Corporate brochure
Learn about the APPF and how our technology and services can support your research.
APPF summary
A single sheet summary about our national facility, its phenotyping technology and services.
Adelaide node
A summary of the technology and services offered at our Adelaide node, The Plant Accelerator®, located at the University of Adelaide.
Canberra node
A summary of the technology and services offered at our Canberra node, the Plant Phenomics Group, located at the Australian National University.
APPF Strategic Plan 2019-2023
The APPF Strategic Plan highlights who we are, what we do, our goals and priorities for 2019 to 2023.
Prospectus
A new National Research Infrastructure partnership transforming Australia’s crop-based food systems and driving innovation in plant science
Smarthouses
Fully automated, high-throughput watering and phenotyping of up to 2,400 plants per day with RGB, fluorescence and hyperspectral imaging.
Growth capsules
Shipping container based high precision chambers with independent control of temperature, relative humidity, multispectral LED light and CO2.
Grain Phenomics Climate Facility
Shipping container-based high-precision Growth Capsules
Drought + heat
Twin fully automated, controlled environment rooms enabling parallel experiments with diverse watering protocols and drought + heat scenarios.
X-Ray CT Scanner
The new X-Ray Computed Tomography (CT) scanner provides advanced phenotyping technology to look inside the plant, head (spike) and seed.
FieldExplorer
Ground-based phenotyping platform to measure plant growth and crop health in filed trials non-destructively.
Virtual and Augmented Reality
Systems for visualising phenomics and environmental sensing data and point clouds in virtual an augmented reality (VR and AR)
Hyperspectral
Hand-held to field-scale hyperspectral platforms for early detection of biotic and abiotic plant stresses in agriculture, horticulture and viticulture.
APPF style guide and acknowledgement guidelines
We welcome acknowledgements and the use of APPF branding in relevant publications and projects. Our brand is really important to us so the correct application is essential. These guidelines will enable the correct use of the logo and acknowledgement of APPF and NCRIS.
Further information please contact us: appf@plantphenomics.org.au
Along with open access to its cutting edge infrastructure, the Australian Plant Phenomics Facility promotes the sharing of data and knowledge, driving best practice, innovation, collaboration and education to advance progress in global plant research.
Experts, tools and suppliers
Find tools and suppliers
The list below contains links to recommended suppliers of a range of phenotyping tools and services that may support your research needs.
Research Publications
Stabilisation of soil organic matter with rock dust partially counteracted by plants Buss, W, Hasemer, H, Ferguson, S and Borevitz, J (2024). Global Change Biology 30, DOI: 10.1111/gcb.17052
The auxin efflux carrier PIN1a regulates vascular patterning in cereal roots Fusi, R, Milner, SG, Rosignoli, S, Bovina, R, De Jesus Vieira Teixeira, C, Lou, H, Atkinson, BS, Borkar, AN, York, LM, Jones, DH, Sturrock, CJ, Stein, N, Mascher, M, Tuberosa, R, et al. (2024). New Phytologist n/a, DOI: 10.1111/nph.19777
Acclimation of thermal tolerance in juvenile plants from three biomes is suppressed when extremes co-occur Harris, RJ, Alvarez, PR, Bryant, C, Briceño, VF, Cook, AM, Leigh, A and Nicotra, AB (2024). Conservation Physiology 12, DOI: 10.1093/conphys/coae027
Introgression of early shoot vigour in wheat modifies root systems, increases competitiveness and provides options for integrated weed management Hendriks, P-W, Gurusinghe, S, Weston, PA, Ryan, PR, Delhaize, E, Weston, LA and Rebetzke, GJ (2024). Plant and Soil, DOI: 10.1007/s11104-024-06653-3
Reduced tillering and dwarfing genes alter root traits and rhizo-economics in wheat Li, X, He, D, White, RG, Delhaize, E, Ryan, PR, Ingvordsen, CH, Scafaro, AP, Atkin, OK, Wasson, A and Richards, R (2024). Physiologia Plantarum 176, DOI: 10.1111/ppl.14336
Machine vision solutions for monitoring pest snails in Australian no-till cropping fields: An exploration of spectral characteristics and detectability Liu, H, Perry, KD, Lu, T-F, Wu, T and Buhl, C (2024). Journal of Agriculture and Food Research 16, DOI: 10.1016/j.jafr.2024.101146
Late maturity α-amylase (LMA) in gibberellin-insensitive, semi-dwarf wheat (Triticum aestivum L.) Mares, D, Derkx, A and Mrva, K (2024). Journal of Cereal Science 116, DOI: 10.1016/j.jcs.2024.103858
Diversity in bread and durum wheat stigma morphology and linkage of increased stigma length to dwarfing gene Rht14 Pallotta, M, Okada, T, Roy, S, Pearson, A, Baumann, U and Whitford, R (2024). Theoretical and Applied Genetics 137, DOI: 10.1007/s00122-024-04663-4
Hyperspectral imaging detects biological stress of wheat for early diagnosis of crown rot disease Xie, Y, Plett, D, Evans, M, Garrard, T, Butt, M, Clarke, K and Liu, H (2024). Computers and Electronics in Agriculture 217, DOI: 10.1016/j.compag.2023.108571
Heat tolerance of a tropical–subtropical rainforest tree species Polyscias elegans: time-dependent dynamic responses of physiological thermostability and biochemistry Zhu, L, Scafaro, AP, Vierling, E, Ball, MC, Posch, BC, Stock, F and Atkin, OK (2024). New Phytologist 241, DOI: 10.1111/nph.19356
Transpiration Responses to Potential Volatile Signals and Hydraulic Failure in Single Leaves of Vitis Vinifera (CV. Shiraz) and Arabidopsis Thaliana (Col 0) Utilising Sensitive Liquid Flow and Simultaneous Gas Exchange Balacey, SL, Capone, DL, Sullivan, W and Tyerman, SD (2023). bioRxiv, DOI: 10.1101/2023.01.24.525440
Image-based growth evaluation and K+/Na+ ratio of transgenic rice lines harboring AtAVP1 gene under salinity stress Chairunisa, Rachmat, A, Perdani, AY, Sulistyowati, Y, Herliana, L and Roy, SJ (2023). AIP Conference Proceedings 2972, DOI: 10.1063/5.0182839
A chromosome-level genome assembly of Plantago ovata Herliana, L, Schwerdt, JG, Neumann, TR, Severn-Ellis, A, Phan, JL, Cowley, JM, Shirley, NJ, Tucker, MR, Bianco-Miotto, T, Batley, J, Watson-Haigh, NS and Burton, RA (2023). Scientific Reports 13, DOI: 10.1038/s41598-022-25078-5
Sunlight and red to far-red ratio impact germination of tropical montane cloud forest species Hoyle, GL, Stevens, AV, Guja, LK, Sommerville, KD, Worboys, S and Crayn, DM (2023). Australian Journal of Botany, DOI: 10.1071/BT22126
Editorial: Machine vision and machine learning for plant phenotyping and precision agriculture Liu, H and Xu, Z (2023). Frontiers in Plant Science 14, DOI: 10.3389/fpls.2023.1331918
Deciphering Salt Stress Responses in Solanum pimpinellifolium through High-Throughput Phenotyping Morton, M, Fiene, G, Ahmed, HI, Rey, E, Abrouk, M, Angel, Y, Johansen, K, Saber, NO, Malbeteau, Y, Al-Mashharawi, S, Ziliani, MG, Aragon, B, Oakey, H, Berger, B, et al. (2023). bioRxiv, DOI: 10.1101/2023.08.15.553433
Transcriptional acclimation to warming temperatures of the Australian alpine herb Wahlenbergia ceracea Notarnicola, RF, Arnold, PA, Feng, Z-P, Hamilton, J, Jones, AW, Loke, S, Nicotra, AB, Schwessinger, B and Ganguly, DR (2023). bioRxiv, DOI: 10.1101/2023.09.27.559694
Remote sensing for monitoring rangeland condition: Current status and development of methods Retallack, A, Finlayson, G, Ostendorf, B, Clarke, K and Lewis, M (2023). Environmental and Sustainability Indicators 19, DOI: 10.1016/j.indic.2023.100285
HvSL1 and HvMADS16 promote stamen identity to restrict multiple ovary formation in barley Selva, C, Yang, X, Shirley, NJ, Whitford, R, Baumann, U and Tucker, MR (2023). Journal of Experimental Botany, DOI: 10.1093/jxb/erad218
MADS8 is indispensable for female reproductive development at high ambient temperatures in cereal crops Shen, C, Zhang, Y, Li, G, Shi, J, Wang, D, Zhu, W, Yang, X, Dreni, L, Tucker, MR and Zhang, D (2023). The Plant Cell 36, DOI: 10.1093/plcell/koad246
Differences in Root Morphologies of Contrasting Wheat (Triticum aestivum) Genotypes Are Robust of a Drought Treatment Si, Z, Delhaize, E, Hendriks, P-W and Li, X (2023). Plants 12, DOI: 10.3390/plants12020275
Barley FASCIATED EAR genes determine inflorescence meristem size and yield traits Wang, C, Yang, X, Zhang, Y, Shen, C, Shi, J, Xia, C, Fang, T, Tu, Q, Li, L, Zhou, X, Zhang, D and Li, G (2023). The Crop Journal 11, DOI: 10.1016/j.cj.2022.10.001
Advances and applications of multivariate statistics and soil-crop sensing to improve nutrient use efficiency and monitor carbon cycling (2023) Pullanagari, R.R. and Cavalli, D. Nutrient Cycling in Agroecosystems. DOI: 10.1007/s10705-023-10310-z
Non-invasive assessment of cultivar and sex of Cannabis sativa L. by means of hyperspectral measurement (2023) Andrea Matros, Patrick Menz, Alison R. Gill, Armando Santoscoy, Tim Dawson, Udo Seiffert, Rachel A. Burton, Plant-Environment Interactions 2023;00:1–17. DOI: 10.1002/pei3.10116
Natural variation in HvAT10 underlies grain cell wall-esterified phenolic acid content in cultivated barley (2023) Houston, K., Learmonth, A., Hassan, A.S., Lahnstein, J., Looseley, M., Little, A., Waugh, R., Burton, R.A. and Halpin, C. Frontiers in Plant Science, 14. doi.org/10.3389/fpls.2023.1095862
Evidence of Bi-Directional Volatile-Mediated Communication between Drought-Stressed and Well-Watered Grapevines (Vitis vinifera L.) (2023) Midzi, J., Jeffery, D.W., Baumann, U., Capone, D.L., Rogiers, S.Y. and Pagay, V. Agronomy, 13, 1747. doi.org/10.3390/agronomy13071747
Working towards the SDGs through Research Infrastructure: Projects, Program and a Perspective on the Brno Declaration from Australia. Myra Cheng, Stefanie Kethers, Tim Brown & LDaCA (The Language Data Commons of Australia) (2023), United Nations Department of Economic and Social Affairs eighth annual Multi-Stakeholder Forum on Science, Technology and Innovation for the Sustainable Development Goals https://sdgs.un.org/sites/default/files/2023-05/B53%20-%20Cheng%20-%20Working%20towards%20the%20SDGs%20through%20Research%20Infrastructure.pdf
Consistently high heat tolerance acclimation in response to a simulated heatwave across species from the broadly distributed Acacia genus. Andrew, SC, Arnold, PA, Simonsen, AK and Briceño, VF (2023). Functional Plant Biology 50, DOI:https://doi.org/10.1071/FP22173
Arbuscular mycorrhizae are important for phosphorus uptake and root biomass, and exudation for nitrogen uptake in tomato plants grown under variable water conditions. Bicharanloo, B, Salomon, MJ, Cavagnaro, TR, Keitel, C, Brien, C, Jewell, N, Berger, B, Lines, T and Dijkstra, FA (2023). Plant and Soil, DOI:10.1007/s11104-023-06078-4
The role of SWEET4 proteins in the post-phloem sugar transport pathway of Setaria viridis sink tissues. Chen, L, Ganguly, DR, Shafik, SH, Danila, F, Grof, CPL, Sharwood, RE and Furbank, RT (2023). Journal of Experimental Botany, DOI:10.1093/jxb/erad076
PHOSPHORUS-STARVATION TOLERANCE 1 (OsPSTOL1) is prevalent in upland rice and enhances root growth and hastens low phosphate signaling in wheat. Kettenburg, AT, Lopez, MA, Yogendra, K, Prior, MJ, Rose, T, Bimson, S, Heuer, S, Roy, SJ and Bailey-Serres, J (2023). Plant, Cell & Environment n/a, DOI:https://doi.org/10.1111/pce.14588
Physical Mapping of QTLs for Root Traits in a Population of Recombinant Inbred Lines of Hexaploid Wheat. Li, X, Wasson, AP, Zwart, AB, Whan, A, Ryan, PR, Forrest, K, Hayden, M, Chin, S, Richards, R and Delhaize, E (2023). International Journal of Molecular Sciences 24, DOI:doi:10.3390/ijms241310492
High-throughput shoot phenotyping reveals temporal growth responses to nitrogen and inorganic and organic phosphorus sources in tomato. Ngo, HTT, Cavagnaro, TR, Jewell, N, Brien, CJ, Berger, B and Watts-Williams, SJ (2023). AoB PLANTS 15, DOI:10.1093/aobpla/plad011
Efficacy of Pendimethalin Rates on Barnyard Grass (Echinochloa crus-galli (L.) Beauv) and Their Effect on Photosynthetic Performance in Rice. Onwuchekwa-Henry, CB, Coe, R, Ogtrop, FV, Roche, R and Tan, DKY (2023). Agronomy 13, DOI:doi:10.3390/agronomy13020582
Development of methods to overcome physiological seed dormancy of temperate annual pasture legumes to assist speed breeding. Peck, DM, Humphries, AW and Ballard, RA (2023). Crop and Pasture Science 74, DOI:https://doi.org/10.1071/CP22314
Ovule cell wall composition is a maternal determinant of grain size in barley. Yang, X, Wilkinson, LG, Aubert, MK, Houston, K, Shirley, NJ and Tucker, MR (2023). New Phytologist n/a, DOI:https://doi.org/10.1111/nph.18714
Meeting the Challenges Facing Wheat Production: The Strategic Research Agenda of the Global Wheat Initiative. Langridge, P, Alaux, M, Almeida, NF, Ammar, K, Baum, M, Bekkaoui, F, Bentley, AR, Beres, BL, Berger, B, Braun, H-J, Brown-Guedira, G, Burt, CJ, Caccamo, MJ, Cattivelli, L, et al. (2022). Agronomy 12, DOI:https://doi.org/10.3390/agronomy12112767
Improved Salinity Tolerance-Associated Variables Observed in EMS Mutagenized Wheat Lines. Lethin, J, Byrt, C, Berger, B, Brien, C, Jewell, N, Roy, S, Mousavi, H, Sukumaran, S, Olsson, O and Aronsson, H (2022). International Journal of Molecular Sciences 23, DOI:https://doi.org/10.3390/ijms231911386
Differences in Root Morphologies of Contrasting Wheat (Triticum aestivum) Genotypes Are Robust of a Drought Treatment. Si, Z, Delhaize, E, Hendriks, P-W and Li, X (2023). Plants 12,
Mapping the long-term influence of river discharge on coastal ocean chlorophyll-a. Auricht, H, Mosley, L, Lewis, M and Clarke, K (2022). Remote Sensing in Ecology and Conservation n/a, DOI:https://doi.org/10.1002/rse2.266
Hyperspectral imaging predicts yield and nitrogen content in grass–legume polycultures. Ball, KR, Liu, H, Brien, C, Berger, B, Power, SA and Pendall, E (2022). Precision Agriculture, DOI:10.1007/s11119-022-09920-4
Reduction of bundle sheath size boosts cyclic electron flow in C4 Setaria viridis acclimated to low light. Bellasio, C and Ermakova, M (2022). The Plant Journal n/a, DOI:https://doi.org/10.1111/tpj.15915
Domain invariant covariate selection (Di-CovSel) for selecting generalized features across domains. Diaz, VF, Mishra, P, Roger, J-M and Saeys, W (2022). Chemometrics and Intelligent Laboratory Systems 222, DOI:https://doi.org/10.1016/j.chemolab.2022.104499
Development of new wine-, dried- and tablegrape scions and rootstocks for Australian viticulture: past, present and future. Dry, IB, Davies, C, Dunlevy, JD, Smith, HM, Thomas, MR, Walker, AR, Walker, RR and Clingeleffer, PR (2022). Australian Journal of Grape and Wine Research 28, DOI:https://doi.org/10.1111/ajgw.12552
Physiological and morphological responses of industrial hemp (Cannabis sativa L.) to water deficit. Gill, AR, Loveys, BR, Cowley, JM, Hall, T, Cavagnaro, TR and Burton, RA (2022). Industrial Crops and Products 187, DOI:https://doi.org/10.1016/j.indcrop.2022.115331
Gene Region Association Analysis of Longitudinal Quantitative Traits Based on a Function-On-Function Regression Model. Li, S, Li, S, Su, S, Zhang, H, Shen, J and Wen, Y (2022). Frontiers in Genetics 13, DOI:10.3389/fgene.2022.781740
A Bayesian random regression method using mixture priors for genome-enabled analysis of time-series high-throughput phenotyping data. Qu, J, Morota, G and Cheng, H (2022). Plant Genome, DOI:10.1002/tpg2.20228
Elucidating the role of SWEET13 in phloem loading of the C4 grass Setaria viridis. Chen, L., Ganguly, D.R., Shafik, S.H., Ermakova, M., Pogson, B.J., Grof, C.P.L., Sharwood, R.E. and Furbank, R.T. (2022). The Plant Journal, 109, 615-632.
Detecting Crown Rot Disease in Wheat in Controlled Environment Conditions Using Digital Color Imaging and Machine Learning. Xie, Y., Plett, D. and Liu, H. (2022). AgriEngineering, 4, 141-155.
Better late than never: the formation of distinctive pepper aromas in cool-climate Shiraz. Barter, S., Siebert, T., Bramley, R., Herderich, M. and Krstic, M. (2022). WINE & VITICULTURE JOURNAL, V37N31.
Investigating the effects of elevated temperature on salinity tolerance traits in grapevine rootstocks using high-throughput phenotyping. Dunlevy, J.D., Blackmore, D.H., Betts, A., Jewell, N., Brien, C., Berger, B., Walker, R.R., Edwards, E.J. and Walker, A.R. (2022). Australian Journal of Grape and Wine Research.
Landsat historical records reveal large-scale dynamics and enduring recovery of seagrasses in an impacted seascape. Fernandes, M.B., Hennessy, A., Law, W.B., Daly, R., Gaylard, S., Lewis, M. and Clarke, K. (2022). Science of The Total Environment, 813, 152646.
Sensor-based phenotyping of above-ground plant-pathogen interactions. Tanner, F., Tonn, S., de Wit, J., Van den Ackerveken, G., Berger, B. and Plett, D. (2022). Plant Methods, 18, 35.
Enhancement of sorghum grain yield and nutrition: A role for arbuscular mycorrhizal fungi regardless of soil phosphorus availability. Watts-Williams, S.J., Gill, A.R., Jewell, N., Brien, C.J., Berger, B., Tran, B.T.T., Mace, E., Cruickshank, A.W., Jordan, D.R., Garnett, T. and Cavagnaro, T.R. PLANTS, PEOPLE, PLANET, 4, 143-156.
The first long-read nuclear genome assembly of Oryza australiensis, a wild rice from northern Australia. Phillips, A.L., Ferguson, S., Watson-Haigh, N.S., Jones, A.W., Borevitz, J.O., Burton, R.A. and Atwell, B.J. Scientific Reports, 12, 10823.
The genetics of vigour-related traits in chickpea (Cicer arietinum L.): insights from genomic data. Nguyen, D.T., Hayes, J.E., Atieno, J., Li, Y., Baumann, U., Pattison, A., Bramley, H., Hobson, K., Roorkiwal, M., Varshney, R.K., Colmer, T.D. and Sutton, T. Theoretical and Applied Genetics, 135, 107-124.
Assessing Rice Salinity Tolerance: From Phenomics to Association Mapping. In A. Bandyopadhyay and R. Thilmony (Eds.). Al-Tamimi, N., Oakey, H., Tester, M. and Negrão, S. (2021). Rice Genome Engineering and Gene Editing: Methods and Protocols (pp. 339-375). New York, NY: Springer US https://doi.org/10.1007/978-1-0716-1068-8_23
Novel Salinity Tolerance Loci in Chickpea Identified in Glasshouse and Field Environments. Atieno, J, Colmer, TD, Taylor, J, Li, Y, Quealy, J, Kotula, L, Nicol, D, Nguyen, DT, Brien, C, Langridge, P, Croser, J, Hayes, JE and Sutton, T (2021). Frontiers in Plant Science 12, DOI:10.3389/fpls.2021.667910
Integrating Ecological Stoichiometry to Understand Nutrient Limitation and Potential for Competition in Mixed Pasture Assemblages. Ball, K. R., Woodin, S. J., Power, S. A., Brien, C., Berger, B., Smith, P. and Pendall, E. (2021). Journal of Soil Science and Plant Nutrition https://doi.org/10.1007/s42729-021-00539-4
Identifying the genetic control of salinity tolerance in the bread wheat landrace Mocho de Espiga Branca. Borjigin, C., Schilling, R. K., Jewell, N., Brien, C., Sanchez-Ferrero, J. C., Eckermann, P. J., Watson-Haigh, N. S., Berger, B., Pearson, A. S. and Roy, S. J. (2021). Functional Plant Biology (pp. -)https://doi.org/10.1071/FP21140.
Identification of a low CO2 responsive mutant from chemical mutagenesis of Setaria viridis shows that reduced carbonic anhydrase severely limits C4 photosynthesis. Chatterjee, J, Coe, RA, Acebron, K, Thakur, V, Yennamalli, RM, Danila, F, Lin, H-C, Balahadia, CP, Bagunu, E, Padhmapreiya, POS, Bala, S, Yin, X, Rizal, G, Dionora, J, et al. (2021). Journal of Experimental Botany, DOI:10.1093/jxb/erab039
Genes That Mediate Starch Metabolism in Developing and Germinated Barley Grain. Collins, H. M., Betts, N. S., Dockter, C., Berkowitz, O., Braumann, I., Cuesta-Seijo, J. A., Skadhauge, B., Whelan, J., Bulone, V. and Fincher, G. B. (2021). Frontiers in Plant Science (Vol. 12) https://doi.org/10.3389/fpls.2021.641325
Frequency Versus Quantity: Phenotypic Response of Two Wheat Varieties to Water and Nitrogen Variability. Cousins, OH, Garnett, TP, Rasmussen, A, Mooney, SJ, Smernik, RJ, Brien, CJ and Cavagnaro, TR (2021). Journal of Soil Science and Plant Nutrition, DOI:10.1007/s42729-021-00467-3
Bundle sheath suberisation is required for C4 photosynthesis in a Setaria viridis mutant. Danila, FR, Thakur, V, Chatterjee, J, Bala, S, Coe, RA, Acebron, K, Furbank, RT, von Caemmerer, S and Quick, WP (2021). Communications Biology 4, DOI:10.1038/s42003-021-01772-4
Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR. Deery, D. M., Smith, D. J., Davy, R., Jimenez-Berni, J. A., Rebetzke, G. J. and James, R. A. (2021). Plant Phenomics (Vol. 2021, pp. 9842178): AAAS10.34133/2021/9842178.
Wheat physiology predictor: predicting physiological traits in wheat from hyperspectral reflectance measurements using deep learning. Furbank, R. T., Silva-Perez, V., Evans, J. R., Condon, A. G., Estavillo, G. M., He, W., Newman, S., Poiré, R., Hall, A. and He, Z. (2021). Plant Methods (Vol. 17, pp. 108) https://doi.org/10.1186/s13007-021-00806-6
The phosphoproteome of rice leaves responds to water and nitrogen supply. Hamzelou, S, Melino, VJ, Plett, DC, Kamath, KS, Nawrocki, A, Larsen, MR, Atwell, BJ and Haynes, PA (2021). bioRxiv, DOI:10.1101/2021.03.15.435047
Generative Adversarial Network Synthesis of Hyperspectral Vegetation Data. Hennessy, A., Clarke, K. and Lewis, M. (2021). Remote Sensing (Vol. 13, pp. 2243) https://doi.org/10.3390/rs13122243.
MADS1 maintains barley spike morphology at high ambient temperatures. Li, G., Kuijer, H. N. J., Yang, X., Liu, H., Shen, C., Shi, J., Betts, N., Tucker, M. R., Liang, W., Waugh, R., Burton, R. A. and Zhang, D. (2021). Nature Plants https://doi.org/10.1038/s41477-021-00957-3.
Proximal detecting invertebrate pests on crops using a deep residual convolutional neural network trained by virtual images. Liu, H and Chahl, JS (2021). Artificial Intelligence in Agriculture, DOI:https://doi.org/10.1016/j.aiia.2021.01.003
Genome-wide association study reveals the genetic complexity of fructan accumulation patterns in barley grain. Matros, A, Houston, K, Tucker, MR, Schreiber, M, Berger, B, Aubert, MK, Wilkinson, LG, Witzel, K, Waugh, R, Seiffert, U and Burton, RA (2021). Journal of Experimental Botany, DOI:10.1093/jxb/erab002
Paternal leakage inheritance and a fitness cost are associated with the chloroplastic psbA gene controlled metribuzin tolerance in lentil (Lens culinaris). McMurray, L. S., Preston, C., Vandenberg, A., Munoz-Santa, I., Mao, D., Bett, K. E., Michelmore, S. and Paull, J. G. (2021). Euphytica (Vol. 217, pp. 103) https://10.1007/s10681-021-02841-9.
Nitrogen depletion enhances endodermal suberization without restricting transporter-mediated root NO3- influx. Melino, VJ, Plett, DC, Bendre, P, Thomsen, HC, Zeisler-Diehl, VV, Schreiber, L and Kronzucker, HJ (2021). Journal of Plant Physiology 257, DOI:https://doi.org/10.1016/j.jplph.2020.153334
Proton-pumping pyrophosphatase homeolog expression is a dynamic trait in bread wheat (Triticum aestivum). Menadue, D. J., Riboni, M., Baumann, U., Schilling, R. K., Plett, D. C. and Roy, S. J. (2021). Plant Direct (Vol. 5, pp. e354)https://doi.org/10.1002/pld3.354.
Genetic analysis of boron tolerance in burr medic (Medicago polymorpha L.). Peck, D. M., Michelmore, S. and Sutton, T. (2021). Crop and Pasture Science (Vol. 72, pp. 634-640)https://doi.org/10.1071/CP20263.
Wheat respiratory O2 consumption falls with night warming alongside greater respiratory CO2 loss and reduced biomass. Posch, B. C., Zhai, D., Coast, O., Scafaro, A. P., Bramley, H., Reich, P. B., Ruan, Y.-L., Trethowan, R., Way, D. A. and Atkin, O. K. (2021). Journal of Experimental Botany https://doi.org/10.1093/jxb/erab454
Continuous monitoring of plant sodium transport dynamics using clinical PET. Ruwanpathirana, GP, Plett, DC, Williams, RC, Davey, CE, Johnston, LA and Kronzucker, HJ (2021). Plant Methods 17, DOI:10.1186/s13007-021-00707-8
Evaluation of commercial composts and potting mixes and their ability to support arbuscular mycorrhizal fungi with maize (Zea mays) as host plant. Salomon, M. J., Watts-Williams, S. J., McLaughlin, M. J., Brien, C. J., Jewell, N., Berger, B. and Cavagnaro, T. R. (2021). Waste Management (Vol. 134, pp. 187-196)https://doi.org/10.1016/j.wasman.2021.08.018.
APETALA2 functions as a temporal factor together with BLADE-ON-PETIOLE2 and MADS29 to control flower and grain development in barley. Shoesmith, JR, Solomon, CU, Yang, X, Wilkinson, LG, Sheldrick, S, van Eijden, E, Couwenberg, S, Pugh, LM, Eskan, M, Stephens, J, Barakate, A, Drea, S, Houston, K, Tucker, MR, et al. (2021). Development 148, DOI:10.1242/dev.194894
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Wong G, Alonso‐Peral M, Li B, Li J, Millar AA (Oct 2018). Plant Direct, Vol 2, Issue 10, DOI: org/10.1002/pld3.88
Genetic mapping of Stb19, a new resistance gene to Zymoseptoria tritici in wheat
Yang N, Theoretical and Applied Genetics, Vol 131, Issue 12, pg 2765-2773, DOI: org/10.1007/s00122-018-3189-0
Salinity tolerance in Australian wild Oryza species varies widely and matches that observed in O. sativa
Yichie Y, Brien C, Berger B, Roberts TH, Atwell BJ (Dec 2018). Rice 11:66 2018, DOI: org/10.1186/s12284-018-0257-7
Plasticity of photosynthetic heat tolerance in plants adapted to thermally contrasting biomes
Zhu L, Bloomfield KJ, Hocart CH, Egerton JJG, O’Sullivan OS, Penillard A, Weerasinghe LK, Atkin OK (Jun 2018). Plant, Cell & Environment, Volume 41, Issue 6, pg 1251-1262, DOI: org/10.1111/pce.13133
Other reading
Book chapter: Tackling nitrogen use efficiency in cereal crops using high-throughput phenotyping
Hansen NJS, Plett D, Berger B, Garnett T (2018). In: Shrawat A., Zayed A., Lightfoot D. (eds) Engineering Nitrogen Utilization in Crop Plants. Springer, Cham, DOI: org/10.1007/978-3-319-92958-3_7
Book chapter: Perspectives in high-throughput phenotyping of qualitative traits at the whole-plant level
Oksana S, Zivcak M, Olsovska K, Brestic M (Mar 2018). In: Sengar RS, Singh A (eds.) Eco-friendly Agro-biological Techniques for Enhancing Crop Productivity. Springer Nature Singapore, DOI: org/10.1007/978-981-10-6934-5_10
Book chapter: Genomic and genetic studies of abiotic stress tolerance in barley
Saade S, Negrão S, Plett D, Garnett T, Tester M (Aug 2018). In: Stein N and Muehlbauer GJ (eds.), The Barley Genome, Compendium of Plant Genomes, © Springer International Publishing AG, part of Springer Nature 2018, DOI: org/10.1007/978-3-319-92528-8_15
Genomic diversity guides conservation strategies among rare terrestrial orchid species when taxonomy remains uncertain
Ahrens CW, Supple MA, Aitken NC, Cantrill DJ, Borevitz JO, James EA (Mar 2017), Annals of Botany, Volume 119, Issue 8, 1 June 2017, Pages 1267–1277. DOI: org/10.1093/aob/mcx022
Exploring genetic variation for salinity tolerance in chickpea using image-based phenotyping
Atieno J, Li Y, Langridge P, Dowling K, Brien CJ, Berger B, Varshney RK, Sutton T (May 2017), Scientific Reports, DOI: 10.1038/s41598-017-01211-7
Chloroplast function and ion regulation in plants growing on saline soils: Lessons from halophytes
Bose J, Munns R, Shabala S, Gilliham M, Pogson BJ, Tyerman SD (Jun 2017), Journal of Experimental Botany, Volume 68, Issue 12, 1 June 2017, Pages 3129–3143, DOI: org/10.1093/jxb/erx142
Emerging insights into the functions of pathogenesis-related protein 1
Breen S, Williams SJ, Outram M, Kobe B, Solomon PS (Oct 2017). Trends in Plant Science, volume 22, issue 10, pg 871-879, DOI: org/10.1016/j.tplants.2017.06.013
The sensitivity of photosynthesis to O2 and CO2 concentration identifies strong Rubisco control above the thermal optimum
Busch FA, Sage R F (Feb 2017), New Phytologist 213: 1036–1051, DOI:
Intraspecific diversity of terpenes of Eucalyptus camaldulensis (Myrtaceae) at a continental scale
Bustos-Segura C, Dillon S, Keszei A, Foley WJ, Külheim C (May 2017), Australian Journal of Botany, DOI: org/10.1071/BT16183#sthash.iNS5rrWr.dpuf
A comprehensive image-based phenomic analysis reveals the complex genetic architecture of shoot growth dynamics in rice (Oryza sativa)
Campbell MT, Du Q, Liub K, Brien CJ, Berger B, Zhang C, Walia H (Jun 2017), The Plant Genome, DOI: 10.3835/plantgenome2016.07.0064
An approach to detect branches and seedpods based on 3D image in low-cost plant phenotyping platform
Cao T, Panjvani K, Dinh A, Wahid K, Bhowmik P (Jun 2017), IEEE Xplore, DOI: 10.1109/CCECE.2017.7946593
The tomato / gene for Fusarium wilt resistance encodes an atypical leucine-rich repeat receptor-like protein whose function is nevertheless dependent on SOBIR1 and SERK3/BAK1
Catanzariti A-M, Do HTT, Bru P, de Sain M, Thatcher LF, Rep M, Jones DA (Mar 2017), The Plant Journal 89, 6: 1195-1209, DOI: 10.1111/tpj.13458
Novel resampling improves statistical power for multiple-trait QTL mapping
Cheng R, Doerge RW, Borevitz J (Mar 2017), , DOI: 10.1534/g3.116.037531
Functional Genomics-guided discovery of a light activated phytotoxin in the wheat pathogen Parastagonospora nodorum via pathway activation
Chooi Y-H, Zhang G, Hu J, Muria-Gonzalez MJ, Tran P, Pettitt A, Maier A, Barrow RA, Solomon PS ( May 2017), Environmental Microbiology, 19 (5): 1975-1986, DOI: 10.1111/1462-2920.13711
Rapid recovery gene downregulation during excess-light stress and recovery in Arabidopsis
Crisp PA, Ganguly D, Smith AB, Murray KD, Estavillo GM, Searle IR, Ford E, Bogdanović O, Lister R, Borevitz JO, Eichten SR, Pogson BJ (Jul 2017), The Plant Cell, DOI: org/10.1105/tpc.16.00828
Relationship between hydraulic and stomatal conductance and its regulation by root and leaf aquaporins under progressive water stress and recovery and exogenous application of ABA in Vitis vinifera L. ‘Syrah’
Dayer S, Tyerman SD, Garnett T, Pagay V. (Dec 2017), Acta Horticulturae 1188, 227-234, DOI: 10.17660/ActaHortic.2017.1188.29
Changes in the chloroplastic CO2 concentration explain much of the observed Kok effect: A model
Farquar GD, Busch FA, (Apr 2017), New Phytologist 214, 2: 570-584, DOI: 10.1111/nph.14512
Differential expression of microRNAs and potential targets under drought stress in barley
(Jan 2017), Plant, Cell & Environment, DOI:
Drought-inducible expression of Hv-miR827 enhances drought tolerance in transgenic barley
Ferdous J, Whitford R, Nguyen M et al. (May 2017), Functional & Integrative Genomics 17:2-3 pp 279-292, DOI: org/10.1007/s10142-016-0526-8
Water and temperature stress define the optimal flowering period for wheat in south-eastern Australia
Flohr BM, Hunt JR, Kirkegaard JA, Evans JR (Aug 2017), Field Crops Research 209:108-119, DOI: org/10.1016/j.fcr.2017.04.012
The Arabidopsis DNA methylome is stable under transgenerational drought stress
Ganguly DR, Crisp PA, Eichten SR, Pogson BJ (Dec 2017). Plant Physiology, 175 (4) 1893-1912, DOI: 10.1104/pp.17.00744
A MEM1-like motif directs mesophyll cell-specific expression of the gene encoding the C4 carbonic anhydrase in Flaveria
Gowik U, Schulze S, Saladie M, Rolland V, Tanz SK, Westhoff P, Ludwig M (Jan 2017), Journal of Experimental Botany 68(2): 311-320, DOI: org/10.1093/jxb/erw475
Carbon dioxide and water transport through plant aquaporins: CO2 and water transport through plant aquaporins
Groszmann M, Osborn HL, and Evans JR, (Jun 2017), Plant, Cell & Environment 40(6) pp 938-961, DOI: 10.1111/pce.12844
Functional differences in transport properties of natural HKT1;1 variants influence shoot Na+ exclusion in grapevine rootstocks
Henderson SW, Dunlevy JD, Wu Y, Blackmore DH, Walker RR, Edwards EJ, Gilliham M, Walker AR (Nov 2017), New Phytologist, DOI:
Cellulose synthesis and cell expansion are regulated by different mechanisms in growing Arabidopsis hypocotyls
Ivakov A, Flis A, Apelt F, Funfgeld F, Scherer U, Stitt M, Kragler F, Vissenberg K, Persson S, Suslov D (Jun 2017), The Plant Cell , DOI: 10.1105/tpc.16.00782
The genome of Chenopodium quinoa
Jarvis DE, Ho YS, Lightfoot DJ, Schmöckel SM, Li B, Borm TJA, Ohyanagi H, Mineta K, Michell CT, Saber N, Kharbatia NM, Rupper RR, Sharp AR, Dally N, Boughton BA, Woo YH, Gao G, Schijlen EGWM, Guo X, Momin AA, Negrão S, Al-Babili S, Gehring C, Roessner U, Jung C, Murphy K, Arold ST, Gojobori T, van der Linden CG, van Loo EN, Jellen EN, Maughan PJ, Tester M (Feb 2017), Nature, DOI:10.1038/nature21370
A practical method using a network of fixed infrared sensors for estimating crop canopy conductance and evaporation rate
Jones HG, Hutchinson PA, May T, Jamali H, Deery DM (Oct 2017), Biosystems Engineering, DOI: org/10.1016/j.biosystemseng.2017.09.012
Development of the first consensus genetic map of intermediate wheatgrass (Thinopyrum intermedium) using genotyping-by-sequencing
Kantarski T, Larson S, Zhang X, DeHaan L, Borevitz J, Anderson J, Poland J, (Jan 2017), Theoretical and Applied Genetics 130(1) pp 137-150, DOI: org/10.1007/s00122-016-2799-7
Ethylene signalling is important for isoflavonoid meditated resistance to Rhizoctonia solani in Medicago truncatula
Liu Y, Hassan S, Kidd BN, Garg G, Mathesius U, Singh KB, Anderson JP (Sep 2017), Molecular Plant-Microbe Interactions 30 (9): 691-700, DOI: 10.1094/MPMI-03-17-0057-R
Crops in Silico: Generating virtual crops using an integrative and multi-scale modelling platform
Marshall-Colon A, Long SP, Allen DK, Allen G, Beard DA, Benes B, Von Caemmerer S, Christensen AJ, Cox DJ, Hart JC, Hirst PM, Kannan K, Katz DS, Lynch J, Millar AJ, et al. (May 2017), Frontiers in Plant Science Vol 8 pg 786, DOI: 10.3389/fpls.2017.00786
Diurnal solar energy conversion and photoprotection in rice canopies
Meacham K, Sirault X, Quick WP, von Caemmerer S, Furbank R (Jan 2017), Plant Physiology 173 (1):495–508, DOI: org/10.1104/pp.16.01585
Growth curve registration for evaluating salinity tolerance in barley
Meng R, Saade S, Kurtek S, Berger B, Brien CJ, Pillen K, Tester M, Sun Y (Mar 2017), Plant Methods, DOI: 10.1186/s13007-017-0165-7
kWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity
Murray KD, Webers C, Ong CS, Borevitz J, Warthmann N (Sep 2017), PLoS Computational Biology 13(9), DOI: 10.1371/journal.pcbi.1005727
Photosynthesis: ancient, essential, complex, diverse … and in need of improvement in a changing world
Niinemets Ü, Berry JA, von Caemmerer S, Ort DR, Parry MAJ, Poorter H (Jan 2017), New Phytologist 213(1): 43-47, DOI: 10.1111/nph.14307
Variation in leaf respiration rates at night correlates with carbohydrate and amino acid supply
O’Leary BM, Lee CP, Atkin OK, Cheng R, Brown TB, Millar AH (Aug 2017), Plant Physiology 174: 2261-2273, DOI: org/10.1104/pp.17.00610
Effects of reduced carbonic anhydrase activity on CO2 assimilation rates in Setaria viridis: a transgenic analysis
Osborn HL, Alonso-Cantabrana H, Sharwood RE, Covshoff S, Evans JR, Furbank RT, von Caemmerer S (Jan 2017), Journal of Experimental Botany 68(2) pp 299-310, DOI: org/10.1093/jxb/erw357
Nitrogen assimilation system in maize is regulated by developmental and tissue-specific mechanisms
Plett D, Holtham L, Baumann U, Kalashyan E, Francis K, Enju A, Toubia J, Roessner U, Bacic A, Rafalski A, Dhugga KS, Tester M, Garnett T, Kaiser BN (Oct 2016). Plant Molecular Biology, volume 92, issue 3, pp 293-312, DOI: org/10.1007/s11103-016-0512-5
A chloroplast retrograde signal, 3’-phosphoadenosine 5’-phosphate, acts as a secondary messenger in abscisic acid signaling in stomatal closure and germination
Pornsiriwong W, Estavillo GM, Chan KX, Tee EE, Ganguly D, Crisp PA, Phua SY, Zhao C, Qiu J, Park J, Yong MT, Nisar N, Yadav AK, Schwessinger B, Rathjen J, Cazzonelli CI, Wilson PB, Gilliham M, Chen Z-H, Pogson BJ (Mar 2017), eLife 2017;6:e23361, DOI: 10.7554/eLife.23361
Detecting spikes of wheat plants using neural networks with Laws texture energy
Qiongyan L, Cai J, Berger B, Okamoto M, Miklavcic SJ (Oct 2017), Plant Methods, DIO: org/10.1186/s13007-017-0231-1
Leaf photosynthetic parameters related to biomass accumulation in a global rice diversity survey
Qu M, Zheng G, Hamdani S, Essemine J, Song Q, Wang H, Chu C, Sirault X, Zhu XG (Sep 2017), Plant Physiology 175 (1) 248–258, DOI:
High-throughput phenotyping technologies allow accurate selection of stay-green
Rebetzke GJ, Jimenez-Berni JA, Bovill WD, Deery DM, James RA (Sep 2016). Journal of Experimental Botany, volume 67, issue 17, pp 4919–4924, DOI: org/10.1093/jxb/erw301
Transition from a maternal to external nitrogen source in maize seedlings
Sabermanesh K, Holtham LR, George J, Roessner U, Boughton BA, Heuer S, Tester M, Plett DC, Garnett TP (Apr 2017), Journal of Integrative Plant Biology, DOI: 10.1111/jipb.12525(2017). Journal of Integrative Plant Biology, DOI: 10.1111/jipb.12525
The combination of gas-phase fluorophore technology and automation to enable high-throughput analysis of plant respiration
Scafaro AP, Negrini ACA, O’Leary B, Millar AH, Ahmed Rashid FA, Hayes L, Fan Y, Zhang Y, Chochois V, Badger MR, Atkin OK (Mar 2017), Plant Methods 13:16, DOI: 10.1186/s13007-017-0169-3
Biochemical Model of C3 photosynthesis applied to wheat at different temperatures
Silva-Perez V, Furbank RT, Condon AG, Evans JR (Aug 2017), Plant, Cell & Environment, 40: 1552–1564, DOI:
Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat
Silva-Perez
Phenomic approaches and tools for phytopathologists
Simko I, Jimenez-Berni JA, Sirault XRR (Jan 2017), Phytopathology 107 (1):6–17, DOI: org/10.1094/PHYTO-02-16-0082-RVW
Have we finally opened the door to understanding Septoria tritici blotch disease in wheat?
Solomon PS (Apr 2017), New Phytologist 214(2): 493-495, DOI: 10.1111/nph.14502
Transition from heterothallism to homothallism is hypothesised to have facilitated speciation among emerging Botryosphaeriaceae wheat-pathogen
Thynne E, McDonald MC, Solomon PS (Dec 2017). Fungal Genetics and Biology, volume 109, pg 36-45, DOI: org/10.1016/j.fgb.2017.10.005
Fungal phytopathogens encode functional homologues of plant rapid alkalinisation factor (RALF) peptides
Thynne E, Saur I, Simbaqueba J, Ogilvie HA, Gonzalez-Cendales Y, Mead O, Taranto A, Catanzariti AM, Mcdonald MC, Schwessinger B, Jones DA, Rathjen JP, Solomon PS (Jun 2016). Molecular Plant Pathology, 18(6), DOI: 10.1111/mpp.12444
Variation in shoot tolerance mechanisms not related to ion toxicity in barley
Tilbrook J, Schilling RK, Berger B, Garcia AF, Trittermann C, Coventry S, Rabie H, Brien CJ, Nguyen M, Tester M and Roy SJ (Sep 2017), Functional Plant Biology, DIO: org/10.1071/FP17049
Measuring CO2 and HCO3− permeabilities of isolated chloroplasts using a MIMS-18O approach
Tolleter D, Chochois V, Poiré R, Price GD, Badger MR (Jun 2017), Journal of Experimental Botany, Volume 68, Issue 14, 1 June 2017, pages 3915–3924, DOI: org/10.1093/jxb/erx188
rosettR: protocol and software for seedling area and growth analysis
Tomé F, Jansseune K, Saey B, Grundy J, Vandenbroucke K, Hannah MA and Redestig H (Mar 2017), Plant Methods, DOI: org/10.1186/s13007-017-0163-9
Efficient in-field plant phenomics for row-crops with an autonomous ground vehicle
Underwood J, Wendel A, Schofield B, McMurray L, Kimber R (May 2017), Journal of Field Robotics, DOI: 10.1002/rob.21728
Convergence of mitochondrial and chloroplastic ANAC017/PAP-dependent retrograde signalling pathways and suppression of programmed cell death
van Aken O, Pogson BJ (May 2017), Cell Death and Differentiation, 24(6): 955-960, DOI: 10.1038/cdd.2017.68
C4 photosynthesis: 50 years of discovery and innovation
von Caemmerer S, Ghannoum O, Furbank R, (Jan 2017), Journal of Experimental Botany volume 68, issue 2, 1 January 2017, pages 97–102. DOI: 10.1093/jxb/erw491
The Transcription factor MYB29 is a regulator of alternative oxidase 1a
Zhang X, , , , , , , , , , , , , , , , , ,
Other reading
Review paper: Multiphase experiments in practice: A look back
Brien CJ (Dec 2017), Australian & New Zealand Journal of Statistics 59: 327–352, DOI:10.1111/anzs.12221
Book chapter: Chlorophyll fluorescence for high-throughput screening of plants during abiotic stress, aging, and genetic perturbation
Nath K, O’Donnell JP, Lu Y (May 2017). In: Hou H., Najafpour M., Moore G., Allakhverdiev S. (eds) Photosynthesis: Structures, Mechanisms, and Applications. Springer, Cham, Springer International Publishing, DOI: 10.1007/978-3-319-48873-8_12
Review paper: Nitrate uptake and its regulation in relation to improving nitrogen use efficiency in cereals
Plett DC, Holtham LR, Okamoto M, Garnett TP (Aug 2017), Seminars in Cell & Developmental Biology, DOI: org/10.1016/j.semcdb.2017.08.027
Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping
Al-Tamimi N, Brien C, Oakey H, Berger B, Saade S, Ho YS, Schmöckel SM, Tester M, Negrao S (Nov 2016), Nature Communications 7, DOI: 10.1038/ncomms13342
Using phenocams to monitor our changing Earth: toward a global phenocam network
Brown TB, Hultine KR, Steltzer H, Denny EG, Denslow MW, Granados J, Henderson S, Moore D, Nagai S, SanClements M, Sánchez-Azofeifa A, Sonnentag O, Tazik D, Richardson AD (Mar 2016), Frontiers in Ecology and the Environment 14:2 pp 84-93, DOI: org/10.1002/fee.1222
Quantifying the onset and progression of plant senescence by color image analysis for high throughput applications
Cai J, Okamoto M, Atieno J, Sutton T, Li Y, Miklavcic SJ (Jun 2016), PLOS, DOI: org/10.1371/journal.pone.0157102
Reconsidering plant memory: Intersections between stress recovery, RNA turnover, and epigenetics
Crisp PA, Ganguly D, Eichten SR, Borevitz JO, Pogson BJ (Feb 2016), Science Advances 19;2(2):e1501340, DOI: 10.1126/sciadv.1501340
Methodology for high-throughput field phenotyping of canopy temperature using airborne thermography
Deery DM, Rebetzke GJ, Jimenez-Berni JA, James RA, Condon AG, Bovill WD, Hutchinson P, Scarrow J, Davy R, Furbank RT (Dec 2016), Frontiers in Plant Science 7:1808, DOI: 10.3389/fpls.2016.01808
DNA methylation profiles of diverse Brachypodium distachyon align with underlying genetic diversity
Eichten SR, Stuart T, Srivastava A, Lister R, Borevitz JO (Sep 2016), Genome Research 26(11):1520-1531, DOI:
Small amounts of ammonium (NH4+) can increase growth of maize (Zea mays)
George J, Holtham L, Sabermanesh K, Heuer S, Tester M, Plett D, Garnett T (Sep 2016). Journal of Plant Nutrition and Soil Science, vol 179, issue 6, pp 717-725, DOI: org/10.1002/jpln.201500625
Image Harvest: An open-source platform for high-throughput plant image processing and analysis
Knecht AC, Campbell MT, Caprez A, Swanson DR, Walia H (May 2016), Journal of Experimental Biology 67(11):3587–3599, DOI: 10.1093/jxb/erw176
Diurnal solar energy conversion and photo-protection in rice canopies
Meacham K, Sirault X, Quick WP, von Caemmerer S, Furbank R (Nov 2016), Plant Physiology, DOI:10.1104/pp.16.01585
Reviews and syntheses: Australian vegetation phenology: new insights from satellite remote sensing and digital repeat photography
Moore CE, Brown T, Keenan TF, Duursma RA, van Dijk AIJM, Beringer J, Culvenor D, Evans B, Huete A, Hutley LB, Maier S, Restrepo-Coupe N, Sonnentag O, Specht A, Taylor JR, van Gorsel E, Liddell MJ (Sep 2016), Biogeosciences 13, 5085-5102, DOI: org/10.5194/bg-13-5085-2016
3D scanning system for automatic high-resolution plant phenotyping
Nguyen CV, Fripp J, Lovell DR, Furbank R, Kuffner P, Daily H, Sirault X (Dec 2016), 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA) 30 Nov-2 Dec 2016, QLD Australia, DOI: 10.1109/DICTA.2016.7796984
Population and phylogenomic decomposition via genotyping-by-sequencing in Australian Pelargonium
Nicotra AB, Chong C, Bragg JG, Ong CR, Aitken NC, Chuah A, Lepschi B, Borevitz (May 2016), Molecular Ecology 25(9):2000-14, DOI: 10.1111/mec.13584
Maize maintains growth in response to decreased nitrate supply through a highly dynamic and developmental stage‐specific transcriptional response
Plett D, Baumann U, Schreiber AW, Holtham L, Kalashyan E, Toubia J, Nau J, Beatty M, Rafalski A, Dhugga KS, Tester M, Garnett T, Kaiser BN (Jan 2016). Plant Biotechnology Journal, volume 14, issue 1, pp 342-353, DOI: org/10.1111/pbi.12388
Using phenomic analysis of photosynthetic function for abiotic stress response gene discovery
Rungrat T, Awlia M, Brown T, Cheng R, Sirault X, Fajkus J, Trtilek M, Furbank B, Badger M, Tester M, Pogson BJ, Borevitz JO, Wilson P (Sep 2016), The Arabidopsis Book 14: e0185. 2016, DOI: org/10.1199/tab.0185
Temperature responses of Rubisco from Paniceae grasses provide opportunities for improving C3 photosynthesis
Sharwood RE, Ghannoum O, Kapralov MV, Gunn LH, Whitney SM (Nov 2016), Nature Plants 2: 16186, DOI:10.1038/nplants.2016.186
Heat susceptibility of grain filling in wheat (Triticum aestivum L.) linked with rapid chlorophyll loss during a 3-day heat treatment
Shirdelmoghanloo H, Lohraseb I, Rabie HS, Brien C, Parent B, Collins NC (Aug 2016), Acta Physiologiae Plantarum 38: 208, DOI: 10.1007/s11738-016-2208-5
A QTL on the short arm of wheat (Triticum aestivum L.) chromosome 3B affects the stability of grain weight in plants exposed to a brief heat shock early in grain filling
Shirdelmoghanloo H, Taylor JD, Lohraseb I, Rabie HS, Brien C, Timmins A, Martin P, Mather DE, Emebiri L, Collins NC (Apr 2016), BMC Plant Biology 16:100, DOI:10.1186/s12870-016-0784-6
Non-destructive phenotyping of lettuce plants in early stages of development with optical sensors
Simko I, Hayes RJ and Furbank RT (Dec 2016), Frontiers in Plant Science 7:1985, DOI: 10.3389/fpls.2016.01985
Genomic variation across landscapes: insights and applications
Bragg JG, Supple MA, Andrew RL, Borevitz JO (Sep 2015), New Phytologist 207:4 pp 953-967, DOI: 10.1111/nph.13410
Integrating image-based phenomics and association analysis to dissect the genetic architecture of temporal salinity responses in rice
Campbell MT, Knecht AC, Berger B, Brien CJ, Wang D, Walia H (Aug 2015), Plant Physiology 168(4), DOI: 10.1104/pp.15.00450
PhenoMeter: a metabolome database search tool using statistical similarity matching of metabolic phenotypes for high-confidence detection of functional links
Carroll AJ, Zhang P, Whitehead L, Kaines S, Tcherkez G, Badger MR (Jul 2015), Frontiers in Bioengineering and Biotechnology, 29 July 2015, DOI: org/10.3389/fbioe.2015.00106
Improving photosynthesis and yield potential in cereal crops by targeted genetic manipulation: Prospects, progress and challenges
Furbank RT, Quick WP, Sirault XRR (Oct 2015), Field Crops Research vol 182 pp 19-29, DOI: 10.1016/j.fcr.2015.04.009
Variation for N uptake system in maize: genotypic response to N supply
Garnett T, Plett D, Conn V, Conn S, Rabie H, Rafalksi A, Dhugga K, Tester M, Kaiser B (Nov 2015), Frontiers in Plant Science, DOI: org/10.3389/fpls.2015.00936
Genetic approaches to enhancing nitrogen-use efficiency (NUE) in cereals: challenges and future directions
Garnett T, Plett D, Heuer S, Okamoto M (Aug 2015), Functional Plant Biology 42(10): 921-941, DIO: doi.org/10.1071/FP15025
Partially dissecting the steady-state electron fluxes in Photosystem I in wild-type and pgr5 and ndh mutants of Arabidopsis
Kou J, Takahashi S, Fan DY, Badger MR, Chow WS (Sep 2015), Frontiers in Plant Science, DOI: org/10.3389/fpls.2015.00758
Novel MtCEP1 peptides produced in vivo differentially regulate root development in Medicago truncatula
Mohd-Radzman NA, Binos S, Truong TT, Imin N, Mariani M, Djordjevic MA (Aug 2015), Journal of Experimental Botany 66(17) pp 5289–5300, DOI: org/10.1093/jxb/erv008
Utilization of a high-throughput shoot imaging system to examine the dynamic phenotypic responses of a C4 cereal crop plant to nitrogen and water deficiency over time
Neilson EH, Edwards AM, Blomstedt CK, Berger B, Lindberg Møller B, Gleadow RM (Apr 2015), Journal of Experimental Biology 66(7) pp 1817-1832, DOI: 10.1093/jxb/eru526
Flavonoids and auxin transport inhibitors rescue symbiotic nodulation in the Medicago truncatula cytokinin perception mutant cre1
Ng JLP, Hassan, S, Truong TT, Hocart CH, Laffont C, Frugier F, Mathesius U (Aug 2015), Plant Cell 27: 2210-2226, DOI:
Combining field performance with controlled environment plant imaging to identify the genetic control of growth and transpiration underlying yield response to water-deficit stress in wheat
Parent B, Shahinnia F, Maphosa L, Berger B, Rabie H, Chalmers K, Kovalchuk A, Langridge P, Fleury D (Sep 2015), Journal of Experimental Botany 66(18) pp 5481-5492, DOI: 10.1093/jxb/erv320
Inhibiting plant microRNA activity: molecular SPONGEs, target MIMICs and STTMs all display variable efficacies against target microRNAs
Reichel M, Li Y, Li J and Millar AA (Sep 2015), Plant Biotechnology Journal 13(7) pp 915-926,
Specificity of plant microRNA target MIMICs: Cross-targeting of miR159 and miR319
Reichel M, Millar AA (May 2015), Journal of Plant Physiology vol 180 pp 45-48, DOI: org/10.1016/j.jplph.2015.03.010
Genomic breeding for food, environment and livelihoods
Rivers J, Warthmann N, Pogson BJ, Borevitz JO (Apr 2015), Food Security 7(2) pp 375-382, DOI: 10.1007/s12571-015-0431-3
SensorDB: a virtual laboratory for the integration, visualization and analysis of varied biological sensor data
Salehi A, Jimenez-Berni J, Deery DM, Doug Palmer D, Holland E, Rozas-Larraondo P, Chapman SC, Georgakopoulos D, Furbank RT (Dec 2015), Plant Methods 11:53, DOI: org/10.1186/s13007-015-0097-z
Different NaCl-induced calcium signatures in the Arabidopsis thaliana ecotypes Col-0 and C24
Schmöckel SM, Garcia AF, Berger B, Tester M, Webb AAR, Roy SJ (Feb 2015), PLOS One, 10(2), 9 pages, DOI: org/10.1371/journal.pone.0117564
Detection of decay in fresh-cut lettuce using hyperspectral imaging and chlorophyll fluorescence imaging
Simko I, Berni JAJ, Furbank RT (Aug 2015), Postharvest Biology and Technology vol 106 pp 44-52, DOI: org/10.1016/j.postharvbio.2015.04.007
“Rolled-upness”: phenotyping leaf rolling in cereals using computer vision and functional data analysis approaches
Sirault XRR, Condon AG, Wood JT, Farquhar GD, Rebetzke GJ (Nov 2015), Plant Methods 11:52, DOI: org/10.1186/s13007-015-0095-1
Comparison of Leaf Sheath Transcriptome Profiles with Physiological Traits of Bread Wheat Cultivars under Salinity Stress
Takahashi F, Tilbrook J, Trittermann C, Berger B, Roy SJ, Seki M, Shinozaki K, Tester M (Aug 2015), PLOS One, DOI: 10.1371/journal.pone.0133322
Feature matching in stereoimages encouraging uniform spatial distribution
Tan X, Sun C, Sirault XRR , Furbank RT, Pham TD (Aug 2015), Pattern Recognition 48(8) pp 2530-2542, DOI: org/10.1016/j.patcog.2015.02.026
A model-based approach to recovering the structure of a plant from images
Ward B, Bastian J, van den Hengel A, Pooley D, Bari R, Berger B, Tester M (Mar 2015), arXiv:1503.03191v2 (Open access to e-prints in Physics, Mathematics, Computer Science, Quantitative Biology, Quantitative Finance and Statistics)
Improving recombinant Rubisco biogenesis, plant photosynthesis and growth by coexpressing its ancillary RAF1 chaperone
Whitney SM, Birch R, Kelso C, Beck JL, Kapralov MV (Mar 2015), PNAS 2015 112 (11) 3564-3569, DOI: 10.1073/pnas.1420536112
Of growing importance: combining greater early vigour and transpiration efficiency for wheat in variable rainfed environments
Wilson PB, Rebetzke GR, Condon AG (Nov 2015), Functional Plant Biology 42(12) 1107-1115, DOI: 10.1071/FP15228 2.69
Pyramiding greater early vigour and integrated transpiration efficiency in bread wheat; trade-offs and benefits
Wilson PB, Rebetzke GR, Condon AG (Nov 2015), Field Crops Research, Volume 183, November 01, 2015, Pages 102-110, DOI: 10.1016/j.fcr.2015.07.002
Genomic Diversity and Climate Adaptation in Brachypodium
Wilson PB, Streich JC, Borevitz JO (2015), Chapter in: Genetics and Genomics of Brachypodium. Ed: John Vogel, Springer International, DOI:
Examining the efficacy of a genotyping-by-sequencing technique for population genetic analysis of the mushroom Laccaria bicolor and evaluating whether a reference genome is necessary to assess homology
Wilson AW, Wickett NJ, Grabowski P, Fant J, Borevitz J, Mueller GM (2015), Mycologia vol 107 (1), DOI: org/10.3852/13-278
TraitCapture: Genomic and environment modelling of plant phenomic data
Brown TB, Cheng R, Sirault XRR, Rungrat T, Murray KD, Trtilek M, Furbank RT, Badger M, Pogson BJ, Borevitz JO (Apr 2014), Current Opinion in Plant Biology 18 pp 73-79, DOI: org/10.1016/j.pbi.2014.02.002
Online oxygen kinetic isotope effects using membrane inlet mass spectrometry can differentiate between oxidases for mechanistic studies and calculation of their contributions to oxygen consumption in whole tissues
Cheah MH, Millar AH, Myers RC, Day DA, Roth J, Hillier W, Badger MR (May 2014), Analytical Chemistry 86(10) pp 5171–5178, DOI: 10.1021/ac501086n
Proximal remote sensing buggies and potential applications for field-based phenotyping
Deery D, Jimenez-Berni J, Jones H, Sirault X, Furbank R (Jul 2014), Agronomy 4(3) pp 349-379, DOI: 10.3390/agronomy4030349
An assessment of near surface CO2 leakage detection techniques under Australian conditions
Feitz A, Jenkins C, Schacht U, McGrath A, Berko H, Schroder I, Noble R, et al. (2014), Energy Procedia 63 pp 3891-3906, DOI: org/10.1016/j.egypro.2014.11.419
bHLH05 is an interaction partner of MYB51 and a novel regulator of glucosinolate biosynthesis in Arabidopsis
Frerigman, H, Berger B, Gigolashvili T (Sep 2014), Plant Physiology 166(1), 349-369, DOI: 10.1104/pp.114.240887
Image-based phenotyping for non-destructive screening of different salinity tolerance traits in rice
Hairmansis A, Berger B, Tester M, Roy SJ (Aug 2014), Rice 2014 7:16, DOI: 10.1186/s12284-014-0016-3
High-Throughput Phenotyping to Detect Drought Tolerance QTL in Wild Barley Introgression Lines
Honsdorf N, March TJ, Berger B, Tester M, Pillen K (May 2014), PLoS ONE 9(5): e97047, DOI: 10.1371/journal.pone.0097047
A novel P700 redox kinetics probe for rapid, non‐intrusive and whole‐tissue determination of photosystem II functionality, and the stoichiometry of the two photosystems in vivo
Jia H, Dwyer SA, Fan DY, Han Y, Badger MR, von Caemmerer S, Chow WS (Nov 2014), Physiologia Plantarum 152(3) pp 403–413, DOI:
Review – Scaling of thermal images at different spatial resolution: The mixed pixel problem
Jones HG, Sirault XRR (Apr 2014), Agronomy 2014, 4(3), 380-396, DOI: 10.3390/agronomy4030380
The 2HA line of Medicago truncatula has characteristics of an epigenetic mutant that is weakly ethylene insensitive
Kurdyukov S, Mathesius U, Nolan KE, Sheahan MB, Goffard N, Carroll BJ, Rose RJ (Jun 2014), BMC Plant Biology 14:174, DOI: org/10.1186/1471-2229-14-174
Transplastomic integration of a cyanobacterial bicarbonate transporter into tobacco chloroplasts
Pengelly J, Förster B, von Caemmerer S, Badger M, Price G, Whitney S (July 2014), Journal of Experimental Botany 65(12) pp 3071–3080, DOI: org/10.1093/jxb/eru156
Digital imaging approaches for phenotyping whole plant nitrogen and phosphorus response in Brachypodium distachyon
Poiré R, Chochois V, Sirault XRR, Vogel JP, Watt M, Furbank RT (Aug 2014), Journal of Integrative Plant Biology 56(8) pp 781-796, DOI:
Study on spike detection of cereal plants
Qiongyan L, Cai J, Berger B, Miklavcic S (Dec 2014), 13th International Conference on Control Automation Robotics and Vision (ICARCV 2014) pp 228-233), Institute of Electrical and Electronics Engineers Inc, DOI: 10.1109/ICARCV.2014.7064309
Expression of the Arabidopsis vacuolar H+-pyrophosphatase gene (AVP1) improves the shoot biomass of transgenic barley and increases grain yield in a saline field
Schilling RK, Marschner P, Shavrukov Y, Berger B, Tester M, Roy SJ, Plett DC (Apr 2014), Plant Biotechnology Journal 12(3), 378-386, DOI: 10.1111/pbi.12145
Leaf hyperspectral reflectance spectra as a tool to measure photosynthetic characters in wheat
Silva-Pérez V, Evans JR, Molero G, Condon T, Furbank R, Reynolds M (Mar 2014), Proceedings of the IV International Wheat Yield Consortium, CIMMYT Mexico, pp 154 of pdf or pp 163 of document page numbering
Wheat variability in photosynthetic capacity and efficiency for increased yield potential
Silva-Pérez V, Evans JR, Molero G, Condon T, Furbank R, Reynolds M (Mar 2014), Proceedings of the IV International Wheat Yield Consortium, CIMMYT Mexico, pp 145 of pdf or pp 154 of document page numbering
Stereo matching using cost volume watershed and region merging
Tan X, Sun C, Sirault X, Furbank R, Pham TD (Nov 2014), Signal Processing: Image Communication 29 (10) pp 1232–44, DOI: org/10.1016/j.image.2014.06.002
A Sinorhizobium meliloti-specific N-acyl homoserine lactone quorum-sensing signal increases nodule numbers in Medicago truncatula independent of autoregulation
Veliz-Vallejos DF, van Noorden GE, Mengqi Y and Mathesius U (Oct 2014), Frontiers in Plant Science vol 5 pp 551, DOI: org/10.3389/fpls.2014.00551
Accounting for variation in designing greenhouse experiments with special reference to greenhouses containing plants on conveyer systems
Brien CJ, Berger B, Rabie H, Tester M (2013). Plant Methods 2013, 9:5. DOI: org/10.1186/1746-4811-9-5
Germanium as a tool to dissect boron toxicity effects in barley and wheat
Hayes JE, Pallotta M, Baumann U, Berger B, Langridge P, Sutton T (2013). Functional Plant Biology 40(6) 618-627. DOI: org/10.1071/FP12329
3D plant modelling via hyperspectral imaging
Liang J, A Zia, J Zhou, Sirault X (Dec 2013), IEEE International Conference on Computer Vision Workshops 2013 (ICCVW), 172–77, ISBN 978-1-4799-3022-7, DOI: 10.1109/ICCVW.2013.29
A holistic high-throughput screening framework for biofuel assessment that characterises variations in soluble sugar and cell wall composition in Sorghum bicolour
Martin AP, Palmer WM, Byrt CS, Furbank RT, Grof CPL (2013). Biotechnology for Biofuels 2013, 6:186. DOI: org/10.1186/1754-6834-6-186
Expression of the Arabidopsis vacuolar H+-pyrophosphatase gene (AVP1) improves the shoot biomass of transgenic barley and increases grain yield in a saline field
Schilling RK, Marschner P, Shavrukov Y, Berger B, Tester M, Roy SJ, Plett DC (2013). Plant Biotechnol J, 12: 378–386. DOI:
PlantScann™: A three-dimensional phenotyping platform for capturing the structural dynamic of plant development and growth
Sirault X, Fripp J, Paproki A, Guo J, Kuffner P, Daily H, Li R, Furbank R (Jun 2013), Proceedings of the 7th International Conference on Functional-Structural Plant Models, Saariselka, Finland, 9-14 June 2013, pp 45-48, ISBN 978-951-651-408-9
Resiliences to water deficit in a phenotyping platform and in the field: How related are they in maize?
Chapuis R, Delluc C, Debeuf R, Tardieu F, Welcker C (Oct 2012), European Journal of Agronomy vol 42, pp 59-67, DOI: org/10.1016/j.eja.2011.12.006
Infrared thermography in plant phenotyping for salinity tolerance
James RA, Sirault XRR (2012), In: Shabala S., Cuin T. (eds) Plant Salt Tolerance, Methods in Molecular Biology (Methods and Protocols), vol 913. Humana Press, Totowa, NJ, DOI: org/10.1007/978-1-61779-986-0_11
A novel mesh processing based technique for 3D plant analysis
Paproki A, Sirault X, Berry S, Furbank R, Fripp J (May 2012), BMC Plant Biology 12:63, DOI: org/10.1186/1471-2229-12-63
Down-regulation of Glucan, Water-Dikinase activity in wheat endosperm increases vegetative biomass and yield
Ral JP, Bowerman AF, Li Z, Sirault X, Furbank R, Pritchard JR, Bloemsma M, Cavanagh CR, Howitt CA, Morell MK (Sep 2012), Plant Biotechnology Journal 10(7) pp 871-882, DOI: 10.1111/j.1467-7652.2012.00711.x
Cross image inference scheme for stereo matching
Tan X, Sun C, Sirault X, Furbank R, Pham TD (Nov 2012), Computer Vision – ACCV 2012, Lecture Notes in Computer Science, vol 7727 pp 217-230, Springer, Berlin, Heidelberg, DOI: org/10.1007/978-3-642-37447-0_17
Tree structural watershed for stereo matching
Tan X, Sun C, Sirault X, Furbank R, Pham TD (Nov 2012), Proceedings of the 27th Conference on Image and Vision Computing New Zealand (IVCNZ 2012) pp 340-345, DOI: 10.1145/2425836.2425903
Natural genetic variation for growth and development revealed by high-throughput phenotyping in Arabidopsis thaliana
Zhang X, Hause RJ, Borevitz JO (Jan 2012),
C4 Plants as biofuel feedstocks: Optimising biomass production and feedstock quality from a lignocellulosic perspective
Byrt CS, Grof CPL, Furbank, RT (Jan 2011), Journal of Integrative Plant Biology 53/120-135, DOI:
Phenomics – technologies to relieve the phenotyping bottleneck
Furbank RT, Tester M (Dec 2011), Trends in Plant Science 16/12 pp 635-644, DOI: org/10.1016/j.tplants.2011.09.005
Accurate inference of shoot biomass from high-throughput images of cereal plants
Golzarian MR, Frick RA, Rajendran K, Berger B, Roy S, Tester M, Lun DS (Feb 2011), Plant Methods 7:2, DOI: org/10.1186/1746-4811-7-2
Automated 3D segmentation and analysis of cotton plants
Paproki A, Fripp J, Salvado O, Sirault X, Berry S, Furbank R (Dec 2011), International Conference on Digital Image Computing: Techniques and Applications, Noosa, QLD, pp 555–560, DOI: 10.1109/DICTA.2011.99
Raising yield potential of wheat. II. Increasing photosynthetic capacity and efficiency
Parry MAJ, Reynolds M, Salvucci ME, Raines C, Andralojc PJ, Zhu X, Price D, Condon AG and Furbank RT (Jan 2011), Journal of Experimental Botany 62/2, pp 453–467, DOI: org/10.1093/jxb/erq304
Functional analysis of corn husk photosynthesis
Pengelly JJL, Kwasny S, Bala S, Evans JR, Voznesenskaya EV, Koteyeva NK, Edwards GE, Furbank RT and von Caemmerer S (Jun 2011), DOI:
Raising yield potential of wheat. I. Overview of a consortium approach and breeding strategies
Reynolds M, Bonnett D, Chapman SC, Furbank RT, Manes Y, Mather DE and Parry MAJ (Jan 2011), Journal of Experimental Botany 62/2, pp 439–452, DOI: org/10.1093/jxb/erq311
A SOS3 homologue maps to HvNax4, a barley locus controlling an environmentally-sensitive Na+ exclusion trait
Rivandi J, Miyazaki J, Hrmova M, Pallotta M, Tester M, Collins NC (Jan 2011), Journal of Experimental Botany 62/3, pp 1201–1216, DOI: org/10.1093/jxb/erq346
Genetic analysis of abiotic stress tolerance in crops
Roy SJ, Tucker EJ, Tester M (Jun 2011), Current Opinion in Plant Biology 14/3, pp 232-239, DOI: org/10.1016/j.pbi.2011.03.002
High-throughput shoot imaging to study drought responses
Berger B, Parent B, Tester MA (Aug 2010), Journal of Experimental Botany 61/13: 3519-3528, DOI: org/10.1093/jxb/erq201
The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets
Carroll AJ, Badger MR, Millar AH (Jul 2010), BMC Bioinformatics 11: 376, DOI: org/10.1186/1471-2105-11-376
Sodium exclusion QLT associated with improved seedling growth in bread wheat under salinity stress
Genc Y, Oldach K, Verbyla AP, Lott G, Hassan M, Tester M, Wallwork H, McDonald GK (Sep 2010), Theoretical and Applied Genetics 121: 877-894, DOI: 10.1007/s00122-010-1357-y
A water-centred framework to assess the effects of salinity on the growth and yield of wheat and barley
Harris BN, Sadras VO, Tester MA (Nov 2010), Plant and Soil volume 336, Issue 1–2, pp 377–389, DOI: doi.org/10.1007/s11104-010-0489-9
PODD: an ontology-driven data repository for collaborative phenomics research
Li Y-F, Kennedy G, Davies F, Hunter J, eds (Nov 2010), School ITEE, The University of Queensland, The Role of Digital Libraries in a Time of Global Change, ICADL 2010, Lecture Notes in Computer Science, vol 6102, Springer, Berlin, Heidelberg, DOI: org/10.1007/978-3-642-13654-2_22
New phenotyping methods for screening wheat and barley for beneficial responses to water deficit
Munns R, James RA, Sirault XRR, Furbank RT, Jones HG (Aug 2010), Journal of Experimental Botany 61/13: 3499-3507, DOI: org/10.1093/jxb/erq199
Growth of the C4 dicot Flaveria bidentis: Photosynthetic acclimation to low light through shifts in leaf anatomy and biochemistry
Pengelly JJL, Sirault XRR, Tazoe Y, Evans JR, Furbank RT, von Caemmerer S (Sep 2010), Journal of Experimental Botany, 61: 4109-4122, DOI: org/10.1093/jxb/erq226
HvNax3 – a locus controlling shoot sodium exclusion derived from wild barley (Hordeum vulgare ssp. spontaneum)
Shavrukov Y, Gupta NK, Miyazaki J, Baho MN, Chalmers KJ, Tester M, Langridge P, Collins, NC (May 2010), Functional & Integrative Genomics 10/2: 277-291, DOI: org/10.1007/s10142-009-0153-8
Breeding technologies to increase crop production in a changing world
Tester MA, Langridge P (Feb 2010), Science vol. 327, issue 5967, pp 818-822, DOI: 10.1126/science.1183700
With ‘phenomics’ plant scientists hope to shift breeding into overdrive
Finkel E (Jul 2009), Science vol 325, issue 5939, pp 380-381, DOI: 10.1126/science.325_380
Plant phenomics: from gene to form and function
Furbank, RT, ed. (Nov 2009), Functional Plant Biology 36(11) v – vi (forward), DOI: org/10.1071/FPv36n11_FO
C4 rice: a challenge for plant phenomics
Furbank RT, von Caemmerer S, Sheehy J and Edwards G (Nov 2009), Functional Plant Biology 36(11) 845-856, DOI: org/10.1071/FP09185
Quantifying the three main components of salinity tolerance in cereals
Rajendran K, Tester MA, Roy SJ (Mar 2009), Plant, Cell and Environment 32:237-249, DOI:
A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography
Sirault XRR, James RA and Furbank RT (Nov 2009), Functional Plant Biology 36(11) 970-977, DOI: org/10.1071/FP09182
Resource for reference ontologies, plant genomics and phenomics
The Planteome database: An integrated resource for reference ontologies, plant genomics and phenomics
The Planteome is a unique resource for both basic plant biology researchers such as evolutionary or molecular biologists and geneticists, and also for plant breeders who are interested in selecting for various traits of interest. The Planteome project is an international collaborative effort and is supported by primary funding (IOS:1340112 award) from the National Science Foundation of USA.
The novel aspect of the Planteome lies in the semantic strength of the integrated ontology network, which can be traversed computationally. Planteome allows plant scientists in various fields to identify traits of interest, and locate data, including germplasm, QTL and genes associated with a given trait, and can help in building hypotheses, confirming observations, data sharing and inter- and intra-specific comparisons.
The Planteome project provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others.
The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. It provides integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is also developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser and the data repository. Read more.