Leaf area prediction model for sugar beet (Beta vulgaris L.) cultivars

Abstract

In two successive years (2003 and 2004), a set of 16 commercial sugar beet cultivars was established in Randomized Complete Block experiments at two sites in central Greece. Cultivar combination was different between years, but not between sites. Leaf sampling took place once during the growing season and leaf area, LA [cm 2 ], leaf midvein length, L [cm] and maximum leaf width, W [cm] were determined using an image analysis system. Leaf parameters were mainly affected by cultivars. Leaf dimensions and their squares (L 2 , W 2 ) did not provide an accurate model for LA predictions. Using L×W as an independent variable, a quadratic model (y = 0.003 x 2 -1.3027 x + 296.84, r 2 = 0.970, p<0.001, n = 32) provided the most accurate estimation of LA. With compromises in accuracy, the linear relationship between L×W and LA (y = 0.5083 x + 31.928, r 2 = 0.948, p<0.001, n = 32) could be used as a prediction model thanks to its simplicity.Additional key words: leaf length; leaf width; morphology; non-destructive methods.

Leaf area estimation by simple measurements and evaluation of leaf area prediction models in Cabernet-Sauvignon grapevine leaves

“…When accuracy is not a matter, linear functions should be preferred for establishing an LA prediction model due to its simplicity and applicability even under field conditions (Lu et al 2004, Tsialtas and Maslaris 2007, 2008. A strong, linear relationship between L and LA [LA = 18.379 L -151.41, r 2 = 0.97, p<0.001, n = 18] Williams and Martinson (2003), the relationship between W and LA had a lower r 2 than that of L-LA function and thus it was of lower accuracy (Fig.…”

Allometric models for leaf area estimation across different leaf-age groups of evergreen broadleaved trees in a subtropical forest

“…However, accurate LA measurement of a large number of leaves, especially in the field, is time-consuming, laborious, and usually destructive (Beerling and Fry 1990). Thus, nondestructive and easily applied models were widely developed for LA estimation based on simple measurements of L and/or W mainly for fruit trees (Ramkhelawan and Bratwaite 1990, Potdar and Pawar 1991, Williams and Martinson 2003, Demirsoy et al 2004, Cittadini and Peri 2006, Serdar and Demirsoy 2006, Mendoza-de Gyves et al 2007, Demirsoy 2009, Demirsoy and Lang 2010, Mazzini et al 2010 or crop species (Rouphael et al 2006, 2007, 2010a, 2010b, Salerno et al 2005, Peksen 2007, Antunes et al 2008, Tsialtas and Maslaris 2008, Fascella et al 2009, Kandiannan et al 2009, Kumar 2009, Zhou and Shoko 2009, Kumar and Sharma 2010, Olfati et al 2010. As an alternative for LA measurement, this indirect, nondestructive method can provide accurate LA estimates and help the in situ LA estimation, which is also necessary for the successive measurements on the same leaf (Beerling and Fry 1990).…”

“…old leaves of eucalypts are much narrower than new ones. Many studies concerned about the effects of different genotypes on LA estimation (e.g., Mendoza-de Gyves et al 2008, Tsialtas andMaslaris 2008), but to our knowledge, only a few concerned about leaf age effects on LA estimates by using leaf dimensions Maslaris 2005, Rouphael et al 2006). Since leaf size may vary with leaf age and leaf shape (L:W ratio) may change with leaf size in some species (Rouphael et al 2006), we do not know whether the varying size of LA alters the coefficients of models.…”

Evaluation of a leaf area prediction model proposed for sunflower

“…However, the highly significant, with a very high r 2 relationships reported in this work could also provide reliable LA estimations. The main advantage of the model proposed by Rouphael et al (2007) is its simplicity since it is a linear relationship (Lu et al 2004, Tsialtas andMaslaris 2008).…”