| dc.creator | Fascella,Giancarlo | |
| dc.creator | Darwich,Salem | |
| dc.creator | Rouphael,Youssef | |
| dc.date | 2013-03-01 | |
| dc.date.accessioned | 2019-04-24T21:19:37Z | |
| dc.date.available | 2019-04-24T21:19:37Z | |
| dc.identifier | https://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0718-58392013000100011 | |
| dc.identifier.uri | http://revistaschilenas.uchile.cl/handle/2250/55758 | |
| dc.description | Leaf area (LA) is a valuable key for evaluating plant growth, therefore accurate, simple, and nondestructive methods for LA determination are important for physiological and agronomic studies. A LA prediction model based on leaf length (L) and width (W) and developed under greenhouse on 14 cultivars of rose (Rosa hybr.*) was validated on a different cultivar of R. hybrida ’Red France’ and on a wild rose species (Rosa sempervirens L.) grown under open-field conditions with two light environments: ambient and 50% shade. Comparisons between measured vs. calculated LA using the following model: LA (cm²) = 0.56 + 0.717 LW, showed a high degree of correlation (R² > 0.95) and provided quantitative evidence of the validity of the LA prediction model. Calculated LA values were very close to the measured values, giving an underestimation of 3.5%, 4.2%, 1.1%, and an overestimation of 1.3% in the prediction for R. hybrida ambient light, R. hybrida 50% shade, R. sempervirens ambient light, R. sempervirens 50% shade, respectively. This model can provide accurate estimations of rose LA independently of the genetic materials and the growing conditions and can be adopted in many experimental comparisons without the use of any expensive instruments. | |
| dc.format | text/html | |
| dc.language | en | |
| dc.publisher | Instituto de Investigaciones Agropecuarias, INIA | |
| dc.relation | 10.4067/S0718-58392013000100011 | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.source | Chilean journal of agricultural research v.73 n.1 2013 | |
| dc.subject | Leaf length | |
| dc.subject | leaf width | |
| dc.subject | Rosa hybr | |
| dc.subject | Rosa sempervirens | |
| dc.subject | light environments | |
| dc.subject | regression analysis | |
| dc.subject | model validation | |
| dc.title | Validation of a leaf area prediction model proposed for rose | |
