Nondestructive Methods to Estimate Leaf Area in Vitis vinifera L.

For two growing seasons (2005 and 2006), leaves of grapevine cv. Cabernet-Sauvignon were collected at three growth stages (bunch closure, veraison, and ripeness) from 10-year-old vines grafted on 1103 Paulsen and SO4 rootstocks and subjected to three watering regimes in a commercial vineyard in central Greece. Leaf shape parameters (leaf area − LA, perimeter − Per, maximum midvein length − L, maximum width − W, and average radial − AR) were determined using an image analysis system. Leaf morphology was affected by sampling time but not by year, rootstock, or irrigation treatment. The rootstock×irrigation×sampling time interaction was significant for all the leaf shape parameters (LA, Per, L, W, and AR) and the means of the interaction were used to establish relationships between them. A highly significant linear function between L and LA could be used as a non-destructive LA prediction model for Cabernet-Sauvignon. Eleven models proposed for the non-destructive LA estimation in various grapevine cultivars were evaluated for their accuracy in predicting LA in this cultivar. For all the models, highly significant linear functions were found between calculated and measured LA. Based on r 2 and the mean square deviation (MSD), the model proposed for LA estimation in cv. Cencibel [LA = 0.587(L×W)] was the most appropriate.Additional key words: leaf length; leaf width; non-destructive methods; Vitis vinifera.

Section: Resultsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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

Tsialtas

Koundouras²,

Zioziou³

2008

“…This method usually saves time and is non-destructive. Various combinations of measurements and various equations relating leaf L and W to leaf area have been used in, for example, tomato (Schwarz and Kläring 2001), cucumber (Robbins andPharr 1987), pepper (De Swart et al 2004), zucchini (Rouphael et al 2006), maize (Stewart and Dwyer 1999), sugar beet (Tsialtas and Maslaris 2005), taro (Lu et al 2004), grape (Montero et al 2000), and chestnut (Serdar and Demirsoy 2006).…”

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confidence: 99%

“…Our shape coefficient (0.68) agreed closely with those calculated for other crops. Values of 0.69 have been reported for pepper (De Swart et al 2004), 0.63 for zucchini (Rouphael et al 2006), 0.59 for Vitis vinifera L. (Montero et al 2000), 0.62 for soybean (Wiersma and Bailey 1975), and 0.73 for corn (McKee 1964). Except for Eq.…”

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confidence: 99%

Leaf area estimation of sunflower leaves from simple linear measurements

Rouphael¹,

Colla²,

Fanasca³

et al. 2007

Simple, accurate, and non-destructive methods for determining leaf area (LA) of plants are important for many experimental comparisons. Determining the individual LA of sunflower (Helianthus annuus L.) involves measurements of leaf parameters such as length (L) and width (W), or some combinations of these parameters. Two field experiments were carried out during 2003 and 2004 to compare predictive equations of sunflower LAs using simple linear measurements. Regression analyses of LA vs. L and W revealed several equations that could be used for estimating the area of individual sunflower leaves. A linear equation having W 2 as the independent variable provided the most accurate estimate (r 2 = 0.98, MSE = 985) of sunflower LA. Validation of the equation having W 2 of leaves measured in the 2004 experiment showed that the correlation between calculated and measured areas was very high.Additional key words: Helianthus annuus L.; leaf parameters; non-destructive methods.--Leaf area (LA) is associated with many agronomic and physiological processes including growth, photosynthesis, transpiration, photon interception, and energy balance (Goudriaan and Van Laar 1994). The equation which can predict LA without causing harm to the plant can provide researchers with many advantages in physiological experiments. Moreover, the equations enable researchers to measure LA on the same plants during the plant growth period and may reduce variability in experiments (Serdar and Demirsoy 2006).Despite various techniques used to estimate leaf area (Lu et al. 2004), the most common approach is to develop ratios and regression estimators by using easily measured leaf parameters such as length (L) and width (W; Kvĕt and Marshall 1971). This method usually saves time and is non-destructive. Various combinations of measurements and various equations relating leaf L and W to leaf area have been used in, for example, tomato (Schwarz and We needed a good equation for non-destructive LA estimation for use in physiological and agronomical studies on the vegetative growth phase of sunflower. Therefore, the aims of this study were (1) to compare existing predictive LA equations for sunflower leaves using non-destructive measurements; and (2) to assess the accuracy of the optimum equation selected using an independent dataset. Sunflower (Helianthus annuus L., cv. Melody) leaves used for all measurements and estimations were from two field experiments conducted during 2003 (May-September) and 2004 (May-October) at Tal Amara Research Station in the Bekaa Valley of Lebanon (33°51'44''N, 35°59'32''E, 905 m a.s.l.). The plants were grown in a completely randomized block design with 4 replications. The size of each plot was 3×10 m. Row spacing (four rows) was 0.80 m and the distance between plants in the row was 0.20 m providing a sowing density of 6 plants per m 2 . In both experiments, fertilizer was applied before seeding at a rate of 300 kg ha -1 of NPK (15-15-15). Additionally, 150 kg ha -1 of ammonium nitrate (34N) and 50 kg ha -1 of potassium n...

“…Lu et al (2004) proposed that simple and especially linear relationships between LA and leaf dimensions (length, L and width, W) could be useful for non-destructive estimation of LA. Till now, non-destructive models for LA determination have been established for many species such as maize (Stewart and Dwyer 1999), bean (Bhatt and Chanda 2003), taro (Lu et al 2004), white clover (Gamper 2005), sugar beet Maslaris 2005, 2008), sunflower (Květ andMarshall 1971, Rouphael et al 2007), radish (Salerno et al 2005), zucchini (Rouphael et al 2006), strawberry (Demirsoy et al 2005), grapevines (Manivel and Weaver 1974, Montero et al 2000, Williams and Martinson 2003, kiwi , chestnut (Serdar and Demirsoy 2006), and hazelnut .…”

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confidence: 99%

Evaluation of a leaf area prediction model proposed for sunflower

Tsialtas¹,

Maslaris²

2008

Six leaf samplings were conducted in two sunflower (Helianthus annuus L.) hybrids during the 2006 growing season in order to evaluate a simple model proposed for leaf area (LA) estimation. A total of 144 leaves were processed using an image analysis system and LA, maximum leaf width (W) [cm], and midvein length (L) [cm] were measured. Also, LA was estimated using the model proposed by Rouphael et al. (2007). Measured LA was exponentially related with L and W, and the W-LA relationships showed higher r 2 . Estimated LA was strongly and exponentially related with L. Strong, linear relationships with high r 2 between estimated and measured LA confirmed the high predictability of the proposed model.Additional key words: Helianthus annuus; leaf length; leaf width; non-destructive methods.