Author
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Jaradat, Abdullah |
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Submitted to: Communications in Biometry and Crop Science (CBCS)
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 11/28/2007 Publication Date: 12/21/2007 Citation: Jaradat, A.A. 2007. Predictive Grain Yield Models Based on Canopy Structure and Structural Plasticity. Communications in Biometry and Crop Science. 2(2):74-89. Interpretive Summary: Two-year field experiments were conducted to study the impact of several management strategies, including conventional and organic cropping systems, moldboard and strip tillage and 2- and 4-yr crop rotations on the ability of a soybean genotype to produce different phenotypes. Plants grown under five management strategies differed as to their fractal dimension of plant skeletal images, leaf physical dimensions, light interception and midday differential canopy temperature. Plants grown under conventional system, moldboard tillage and 4-yr crop rotation developed complex plant architecture, maintained the largest midday differential canopy temperature, intercepted more light and produced the largest grain yield per plant, unlike plants grown under organic system, strip tillage and 4-yr crop rotation. It was possible to predict grain yield per plant at several reproductive growth stages with high probability using midday differential canopy temperature and light interception measurements as predictors. This information is of potential value to agronomists and farmers in developing and using simple periodic measurements to predict crop growth and yield under different management strategies. Technical Abstract: Structural dimensions, digitally measured on stems and leaves of soybean plants during the first six reproductive growth stages (R1-R6), were used to assess the impact of five management strategies including cropping systems (conventional (C) vs. organic, (O)), tillage (conventional moldboard (C) vs. strip tillage (S)), the recommended fertilizer rate (Y) and crop rotations (2-yr vs. 4-yr) on grain yield per plant. Leaf physical dimensions, light interception [Log (I/Io)], fractal dimension of plant skeletal images (Do) and midday differential canopy temperature (dC) explained 84.0% of variation among plant samples grown under the five management strategies with 75-100% correct classification. Management strategies, growth stages and their interaction accounted for a total of 24-79% of variation in different structural dimensions, and for 97, 97 and 94% of variation in Do, dC and Log(I/Io), respectively. Structural dimensions of plants grown under CCY4 and OSY4 accounted for the largest (98%) and smallest (72%) variation in dC, respectively; largest (91%) and smallest (81%) variation accounted for in Do were found for plants grown under CCY2 and CSY4, respectively, whereas largest (97%) and smallest (73%) variation accounted for in Log(I/Io) were found for plants grown under OSY4 and CSY4, respectively. Grain yield per plant can be predicted at R3, R4, R5 and R6, with increasing probability (R2= 52, 64, 69 and 72%, respectively) and decreasing root mean square error of prediction (from 3.2 at R3 to 2.1 g plant-1 at R6) using dC and Log(I/Io) as predictors. |
