Phenotyping Knowledge

Below are some examples of literature on various phenotyping related topics. If you wish to suggest topics and references please send them to Plant Phenomics Australia.

Phenomics Reviews

Furbank R.T. & Tester M. (2011) Phenomics - technologies to relieve the phenotyping bottleneck. Trends in Plant Science, 16, 635-644.10. DOI: 1016/j.tplants.2011.09.005

Fiorani F, Schurr U. 2013. Future Scenarios for Plant Phenotyping. Annual Review of Plant Biology 64: 267-291. DOI: 10.1146/annurev-arplant-050312-120137

Modelling

Baret F, Houles V, Guerif M. 2007. Quantification of plant stress using remote sensing observations and crop models: the case of nitrogen management. Journal of Experimental Botany 58(4): 869-880. DOI: 10.1093/jxb/erl231

Messina CD, Jones JW, Boote KJ, Vallejos CE. 2006. A gene-based model to simulate soybean development and yield responses to environment. Crop Science 46(1): 456-466. DOI: 10.2135/cropsci2005.04-0372

Messina CD, Podlich D, Dong ZS, Samples M, Cooper M. 2011. Yield-trait performance landscapes: from theory to application in breeding maize for drought tolerance. Journal of Experimental Botany 62(3): 855-868. DOI: 10.1093/jxb/erq329

Podlich DW, Cooper M. 1998. QU-GENE: a simulation platform for quantitative analysis of genetic models. Bioinformatics 14(7): 632-653. DOI: 10.1093/bioinformatics/14.7.632

White JW, Hoogenboom G. 1996. Simulating effects of genes for physiological traits in a process-oriented crop model. Agronomy Journal 88(3): 416-422.

Hammer G, Cooper M, Tardieu F, Welch S, Walsh B, van Eeuwijk F, Chapman S, Podlich D. 2006. Models for navigating biological complexity in breeding improved crop plants. Trends in Plant Science 11(12): 587-593. DOI:10.1016/j.tplants.2006.10.006

Hyperspectral Imaging

Jones H.G. & Vaughan R.A. (2010) Remote sensing of vegetation : principles, techniques, and applications. Oxford University Press, New York.

High Throughput Phenotyping

Arvidsson S., Perez-Rodriguez P. & Mueller-Roeber B. (2011) A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects. New Phytologist, 191, 895-907.

Campbell MT, Knecht AC, Berger B, Brien CJ, Wang D, Walia H (2015) Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice. Plant Physiology 168(4), 1476-1489.

Neumann K., Klukas C., Friedel S., Rischbeck P., Chen D., Entzian A., Stein N., Graner A. & Kilian B. (2015) Dissecting spatiotemporal biomass accumulation in barley under different water regimes using high-throughput image analysis. Plant Cell and Environment, 38, 1980-1996.

Fahlgren N., Gehan M.A. & Baxter I. (2015) Lights, camera, action: high-throughput plant phenotyping is ready for a close-up. Current Opinion in Plant Biology, 24, 93-99.

Data Standards

Krajewski P., Chen D.J., Cwiek H., van Dijk A.D.J., Fiorani F., Kersey P., Klukas C., Lange M., Markiewicz A., Nap J.P., van Oeveren J., Pommier C., Scholz U., van Schriek M., Usadel B. & Weise S. (2015) Towards recommendations for metadata and data handling in plant phenotyping. Journal of Experimental Botany, 66, 5417-5427.

Hunt L.A., White J.W. & Hoogenboom G. (2001) Agronomic data: advances in documentation and protocols for exchange and use. Agricultural Systems, 70, 477-492.

Image Analysis

Fahlgren N., Feldman M., Gehan Malia A., et al. (2015) A Versatile Phenotyping System and Analytics Platform Reveals Diverse Temporal Responses to Water Availability in Setaria. Molecular Plant, 8, 1520-1535.

Klukas C., Chen D. & Pape J.-M. (2014) Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping. Plant Physiology, 165, 506-518.

Goff S.A., Vaughn M., McKay S. et al. (2011) The iPlant collaborative: cyberinfrastructure for plant biology. Frontiers in Plant Science, 2.

Field Phenomics

White J.W., Andrade-Sanchez P., Gore M.A., Bronson K.F., Coffelt T.A., Conley M.M., Feldmann K.A., French A.N., Heun J.T., Hunsaker D.J., Jenks M.A., Kimball B.A., Roth R.L., Strand R.J., Thorp K.R., Wall G.W. & Wang G. (2012) Field-based phenomics for plant genetics research. Field Crops Research, 133, 101-112.

Araus J.L. & Cairns J.E. (2014) Field high-throughput phenotyping: the new crop breeding frontier. Trends in Plant Science, 19, 52-61.

Mobile Phenotyping Platforms

Comar A., Burger P., de Solan B., Baret F., Daumard F. & Hanocq J.-F. (2012) A semi-automatic system for high throughput phenotyping wheat cultivars in-field conditions: description and first results. Functional Plant Biology, 39, 914-924.

Montes J.M., Technow F., Dhillon B.S., Mauch F. & Melchinger A.E. (2011) High-throughput non-destructive biomass determination during early plant development in maize under field conditions. Field Crops Research, 121, 268-273.

Andrade-Sanchez P., Gore M.A., Heun J.T., Thorp K.R., Carmo-Silva A.E., French A.N., Salvucci M.E. & White J.W. (2014) Development and evaluation of a field-based high-throughput phenotyping platform. Functional Plant Biology, 41, 68-79.

Busemeyer L., Mentrup D., Möller K., Wunder E., Alheit K., Hahn V., Maurer H., Reif J., Würschum T., Müller J., Rahe F. & Ruckelshausen A. (2013) BreedVision — A Multi-Sensor Platform for Non-Destructive Field-Based Phenotyping in Plant Breeding. Sensors, 13, 2830.

Barker J., Zhang N., Sharon J., Steeves R., Wang X., Wei Y. & Poland J. (2016) Development of a field-based high-throughput mobile phenotyping platform. Comput. Electron. Agric., 122, 74-85.

Unmanned Aerial Vehicles

Berni J.A.J., Zarco-Tejada P.J., Suarez L. & Fereres E. (2009) Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle. Ieee Transactions on Geoscience and Remote Sensing, 47, 722-738.

Colomina I. & Molina P. (2014) Unmanned aerial systems for photogrammetry and remote sensing: A review. Isprs Journal of Photogrammetry and Remote Sensing, 92, 79-97.