Phenotyping winter wheat for early ground cover
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The relationship between the early ground cover and the grain yield in winter wheat is not yet fully understood. In a winter wheat breeding programme, selection for early ground cover is traditionally made using visual scoring. Although visual scoring is preferred as a phenotypic screening tool by wheat breeders, its output may not be reliable, as it requires experience. A smartphone camera-based digital image technique can be recommended as a feasible, reliable, repeatable, affordable, and fast selection tool for early ground cover in wheat as an alternative to visual scoring. For this purpose, two wheat trials were conducted in the 2017–2018 and 2019–2020 seasons. In both seasons, 215 wheat genotypes in total, together with three checks from spring wheat, were tested under rain-fed conditions in the spring wheat zone in Turkey. All the tested wheat genotypes were grouped into spring, facultative, and winter growth habit using visual scoring. Simultaneously, photos were taken from each plot with a smartphone camera, and the early ground cover (%) was estimated using the smartphone camera-based digital image technique. The relationships between grain yield, visual scoring, and early ground cover could so be estimated. In both seasons, significant negative correlation between grain yield and visual scoring (r = −0.679** and r = −0.704**, respectively) and significant positive correlation between the grain yield and the early ground cover (r = 0.745** and r = 0.747**, respectively) were observed. The correlation between visual scoring and early ground cover were negative (r = −0.862** and r = −0.926**, respectively). The broad sense heritability estimates in both seasons were 0.51 and 0.85, respectively, for early ground cover, 0.91 and 0.94 for visual scoring, and 0.86 and 0.69 for grain yield. In this study, we revealed that testing winter wheat genotypes in the spring wheat zone rather than in the winter wheat zone could be a more effective way to unveil the positive relationship between the early ground cover and the grain yield. We have shown that the smartphone-based digital image technique is a useful selection tool for early ground cover in winter wheat.

Allen R.G., Pereira L.S., Raes D., Smith M. (1998): Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper No. 56. Rome, FAO.
Ayalew H., Liu H., Liu C., Yan G. (2018): Identification of early vigor QTLs and QTL by environment interactions in wheat (Triticum eastivum L.). Plant Molecular Biology Reporter, 36: 399–405.
Baenziger P.S., Dweikat I., Gill K., Eskridge K., Berke T., Shah M., Campbell B.T., Ali M.L., Mengistu N., Mahmood A., Auvuchanon A., Yen Y., Rustgi S., Moreno-Sevilla B., Mujeeb-Kazi A., Morris M.R. (2011): Understanding grain yield: It is a journey, not a destination. Czech Journal of Genetics and Plant Breeding, 47: S77–S84.
Baresel J.P., Rischbeck P., Hu Y., Kipp S., Hu Y., Barmeier G., Mistele B., Schmidhalter U. (2017): Use of a digital camera as alternative method for non-destructive detection of the leaf chlorophyll content and the nitrogen nutrition status in wheat. Computers and Electronics in Agriculture, 140: 25–33.
Beil C.T., Anderson V.A., Morgounov A., Haley S.D. (2019): Genomic selection for winter survival ability among a diverse collection of facultative and winter wheat genotypes. Molecular Breeding, 39: 29.
Bellundagi A., Singh G.P., Prabhu K.V., Arora A., Jain N., Ramya P., Singh A.M., Singh P.K., Ahlawat A. (2013): Early ground cover and other physiological traits as efficient selection criteria for grain yield under moisture deficit stress conditions in wheat (Triticum aestivum L.). Indian Journal of Plant Physiology, 18: 277–281.
Braun H.J., Saulescu N.N. (2002): Breeding winter and facultative wheat. In: Curtis B.C., Rajaram S., MacPherson H. (eds.): Bread Wheat: Improvement and Production. FAO Plant Production and Protection Series. Rome, FAO.
Bodner G., Nakhforoosh A., Kaul H.P. (2015): Management of crop water under drought: A review. Agronomy for Sustainable Development, 35: 401–442.
Bourgault M., Webber H.A., Chenu K., Oleary G.J., Gaiser T., Siebert S., Dreccer F., Huth N., Fitzgerald G.J., Tausz M., Ewert F. (2020): Early vigour in wheat: Could it lead to more severe terminal drought stress under elevated atmospheric [CO2] and semi-arid conditions? Global Change Biology, 26: 4079–4093.
Cann D.J., Schillinger W.F., Hunt J.R., Porker K.D., Harris F.A.J. (2020): Agroecological advantages of early-sown winter wheat in semi-arid environments: A comparative case study from southern Australia and Pacific Northwest United States. Frontiers in Plant Science, 11: 568.
CANOPEO (2021): CANOPEO software. Available at (accessed May 1, 2021).
Capo-Chichi L.J.A., Eldridge S., Elakhdar A., Kubo T., Brueggeman R., Anyia A.O. (2021): QTL mapping and phenotypic variation for seedling vigour traits in barley (Hordeum vulgare L.). Plants, 10: 1149.
Casadesus J., Kaya Y., Bort J., Nachit M.M., Araus J.L., Amor S., Ferrazzano G., Maalouf F., Maccaferri M., Martos V., Ouabbou H., Villegas D. (2007): Using vegetation indices derived from conventional digital cameras as selection criteria for wheat breeding in water-limited environments. Annals of Applied Biology, 150: 227–236.
Casio (2021): Solar elevation angle. Available at (accessed May 1, 2021).
Chen S., Wang J., Deng G., Chen L., Cheng X., Xu H., Zhan K. (2018): Interactive effects of multiple vernalization (Vrn-1)- and photoperiod (Ppd-1)-related genes on the growth habit of bread wheat and their association with heading and flowering time. BMC Plant Biology, 18: 374.
Confalonieri R., Foi M., Casa R., Aquaro S., Tona E., Peterle M., Boldini A., De Carli G., Ferrari A., Finotto G., Guarneri T., Manzoni V., Movedi E., Nisoli A., Paleari L., Radici I., Suardi M., Veronesi D., Bregaglio S., Cappelli G., Chiodini M.E., Dominoni P., Francone C., Frasso N., Stella T., Acutis M. (2013): Development of an app for estimating leaf area index using a smartphone. Trueness and precision determination and comparison with other indirect methods. Computers and Electronics in Agriculture, 96: 67–74.
Cook J.P., Acharya R.K., Martin J.M., Blake N.K., Khan I.J., Heo H.Y., Kephart K.D., Eckhoff J., Talbert L.E., Sherman J.D. (2021): Genetic analysis of stay-green, yield, and agronomic traits in spring wheat. Crop Science, 61: 383–395.
Cullis B.R., Smith A.B., Coombes N.E. (2006): On the design of early generation variety trials with correlated data. Journal of Agricultural, Biological and Environmental Statistics, 11: 381.
Fowler D.B., Byrns B.M., Greer K.J. (2014): Overwinter low-temperature responses of cereals: Analyses and simulation. Crop Science, 54: 2395–2405.
Gao F., Liu J., Yang L., Wu X., Xiao Y., Xia X., He Z. (2016): Genome-wide linkage mapping of QTL for physiological traits in a Chinese wheat population using the 90K SNP array. Euphytica, 209: 789–804.
Hashjin J.M. (1992): Genotypic and Environmental Effects on Growth Habit in Wheat (Triticum aestivum L.): A Thesis Presented in Partial Fulfilment of the Requirements for the Degree of Master of Agricultural Science in Plant Science (Plant Breeding) at Massey University. [Ph.D. Thesis.] Palmerston North, Massey University.
Hendriks P.W., Gurusinghe S., Ryan P.R., Rebetzke G.J., Weston L.A. (2022): Competitiveness of early vigour wheat (Triticum aestivum L.) genotypes is established at early growth stages. Agronomy, 12: 377.
Hosseini M., Saidi A., Maali-Amiri R., Abbasi A., Khosravi-Nejad F. (2021): Developmental regulation and metabolic changes of RILs of crosses between spring and winter wheat during low temperature acclimation. Environmental and Experimental Botany, 182: 104299.
Hyles J., Bloomfield M.T., Hunt J.R., Trethowan R.M., Trevaskis B. (2020): Phenology and related traits for wheat adaptation. Heredity, 125: 417–430.
IWWIP (2021): International winter wheat improvement program. Available at (accessed May 1, 2021)
Jimenez-Berni J.A., Deery D.M., Rozas-Larraondo P., Condon A.G., Rebetzke G.J., James R.A., Bovill W.D., Furbank R.T., Sirault X.R.R. (2018): High throughput determination of plant height, ground cover, and above-ground biomass in wheat with LiDAR. Frontiers in Plant Science, 9: 237.
Jobson E.M., Johnston R.E., Oiestad A.J., Martin J.M., Giroux M.J. (2019): The impact of the wheat Rht-B1b semi-dwarfing allele on photosynthesis and seed development under field conditions. Frontiers in Plant Science, 10: 51.
Kaya Y. (2021): Winter wheat adaptation to climate change in Turkey. Agronomy, 11: 689.
Kipp S., Mistele B., Baresel P., Schmidhalter U. (2014): High-throughput phenotyping early plant vigour of winter wheat. European Journal of Agronomy, 52(B): 271–278.
Kling J., Merk H.L. (2021): Introduction to augmented experimental design. Available at (accessed May 1, 2021).
Kosova K., Prasil I.T., Vitamvas P. (2008): The relationship between vernalization- and photoperiodically-regulated genes and the development of frost tolerance in wheat and barley. Biologia Plantarum, 52: 601–615.
Li X.M., Chen X.M., Xiao Y.G., Xian X.C., Wang D.S., He Z.H., Wang H.J. (2014): Identification of QTLs for seedling vigor in winter wheat. Euphytica, 198: 199–209.
Limin A.E., Fowler D.B. (2000): Morphological and cytological characters associated with low-temperature tolerance in wheat (Triticum aestivum L. em Thell.) Canadian Journal of Plant Science, 80: 687–692.
Limin A.E., Fowler D.B. (2006): Low-temperature tolerance and genetic potential in wheat (Triticum aestivum L.): Response to photoperiod, vernalization, and plant development. Planta, 224: 360–366.
Lopez-Castaneda C., Richards R.A., Farquhar G.D., Williamson R.E. (1996): Seed and seedling characteristics contributing to variation in early vigor among temperate cereals. Crop Science, 36: 1257–1266.
Ma J., Li Y., Yunqiang C.Y., Du K., Zheng F., Zhang L., Sun Z. (2019): Estimating above ground biomass of winter wheat at early growth stages using digital images and deep convolutional neural network. European Journal of Agronomy, 103: 117–129.
Marone D., Rodriguez M., Saia S., Papa R., Rau D., Pecorella I., Laido G., Pecchioni N., Lafferty J., Rapp M., Longin F.H., De Vita P. (2020): Genome-wide association mapping of prostrate/erect growth habit in winter durum wheat. International Journal of Molecular Sciences, 21: 394.
Mason R.E., Addison C.K., Babar A., Acuna A., Lozada D., Subramanian N., Arguello M.N., Miller R.G., Brown-Guedira G., Guedira M., Johnson J. (2018): Diagnostic markers for vernalization and photoperiod loci improve genomic selection for grain yield and spectral reflectance in wheat. Crop Science, 58: 242–252.
Morgounov A., Gummadov N., Belen S., Kaya Y., Keser M., Mursalova J. (2014): Association of digital photo parameters and NDVI with winter wheat grain yield in variable environments. Turkish Journal of Agriculture and Forestry, 38: 624–632.
Mullan D.J., Reynolds M.P. (2010): Quantifying genetic effects of ground cover on soil water evaporation using digital imaging. Functional Plant Biology, 37: 703–712.
Patrignani A., Ochsner T.E. (2015): Canopeo: A powerful new tool for measuring fractional green canopy cover. Agronomy Journal, 107: 2312–2320.
Peel M.C., Finlayson B.L., McMahon T.A. (2007): Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences, 11: 1633–1644.
Pietragalla J., Mullan D., Dorame E.P. (2012): In-season biomass. In: Pask A.J.D., Pietragalla J., Mullan D., Reynolds M. (eds.): Physiological Breeding II: A Field Guide to Wheat Phenotyping El Batan, CIMMYT: 46–53. Available at (accessed May 1, 2021).
Rebetzke G.J., Richards R.A. (1999): Genetic improvement of early vigour in wheat. Australian Journal of Agricultural Research, 50: 291–302.
Rebetzke G.J., Zheng B., Chapman S.C. (2016): Do wheat breeders have suitable genetic variation to overcome short coleoptiles and poor establishment in the warmer soils of future climates? Functional Plant Biology, 43: 961–972.
Reynolds M., Chapman S., Crespo-Herrera L., Molero G., Mondal S., Pequeno D.N.L., Pinto F., Pinera-Chavez F.J., Poland J., Rivera-Amado C., Saint Pierre C., Sukumaran S. (2020): Breeder friendly phenotyping. Plant Science, 295: 110396.
Richards R.A., Watt M., Rebetzke G.J. (2007): Physiological traits and cereal germplasm for sustainable agricultural systems. Euphytica, 154: 409–425.
Rosello M., Royo C., Sanchez-Garcia M., Soriano J.M. (2019): Genetic dissection of the seminal root system architecture in Mediterranean durum wheat landraces by genome-wide association study. Agronomy, 9: 364.
Roy S.C., Shil P. (2020): Assessment of genetic heritability in rice breeding lines based on morphological traits and caryopsis ultrastructure. Scientific Reports, 10: 7830.
Shabannejad M., Bihamta M.R., Majidi-Hervan E., Ali-pour H., Ebrahimi A. (2020): A simple, cost-effective high-throughput image analysis pipeline improves genomic prediction accuracy for days to maturity in wheat. Plant Methods, 16: 146.
Stelmakh A.F. (1987): Growth habit in common wheat (Triticum aestivum L.). Euphytica, 36: 513–519.
Středa T., Haberle J., Klimešová J., Klimek-Kopyra A., Středová H., Bodner G., Chloupek O. (2020): Field phenotyping of plant roots by electrical capacitance – A standardized methodological protocol for application in plant breeding: a Review. International Agrophysics, 34: 173–184.
Tao M., Huang X., Liu C., Deng R., Liang K., Qi L. (2020): Smartphone-based detection of leaf color levels in rice plants. Computers and Electronics in Agriculture, 173: 105431.
TSMS (2021): Turkish State Meteorological Service. Available at (accessed May 1, 2021).
UPOV (2012): Wheat guidelines. Available at (accessed May 1, 2021).
Vukasovic S., Alahmad S., Christopher J., Snowdon R.J., Stahl A., Hickey L.T. (2022): Dissecting the genetics of early vigour to design drought-adapted wheat. Frontiers in Plant Science, 12: 754439.
Walter J., Edwards J., Cai J., McDonald G., Miklavcic S.J., Kuchel H. (2019): High-throughput field imaging and basic image analysis in a wheat breeding program. Frontiers in Plant Science, 10: 449.
Wolfinger R., Federer W.T., Cordero-Brana O. (1997): Recovering information in augmented designs, using SAS PROC GLM and PROC Mixed. Agronomy Journal, 89: 856–859.
Yang Y., Wan H., Yang F. Xiao C., Li J., Ye M., Chen C., Deng G., Wang Q., Li A., Mao L., Yang W., Zhou Y. (2020): Mapping QTLs for enhancing early biomass derived from Aegilops tauschii in synthetic hexaploid wheat. PLoS ONE, 15: e0234882.
Yu Z., Ustin S.L., Zhang Z., Liu H., Zhang X., Meng X., Cui Y. Guan H. (2020): Estimation of a new canopy structure parameter for rice using smartphone photography. Sensors, 20: 4011.
Yuan W., Li J., Bhatta M., Shi Y., Baenziger P.S., Ge Y. (2018): Wheat height estimation using LiDAR in comparison to ultrasonic sensor and UAS. Sensors, 18: 3731.
Zhao Z., Rebetzke G.J., Zheng B., Chapman S.C., Wang E. (2019): Modelling impact of early vigour on wheat yield in dryland regions. Journal of Experimental Botany, 70: 2535–2548.
Zheng B., Chenu K., Chapman S.C. (2016): Velocity of temperature and flowering time in wheat – assisting breeders to keep pace with climate change. Global Change Biology, 22: 921–933.
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