Predicting on-farm soybean yields in the pampas using CROPGRO-soybean

By J. Mercau, J. Dardanelli, D. Collino, J. Andriani, A. Irigoyen, E. Satorre. 2007

76 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Plant Science

View Paper: https://www.semanticscholar.org/paper/3574784cc3050c6c8bee94ae8ecd47273673c74f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology, Evolution, Behavior and Systematics

1. James R. Hunt
2. Zvi Hochman
3. Kenneth J. Boote
4. J. Kirkegaard

In Plant Science

1. Gerrit Hoogenboom
2. Kenneth J. Boote
3. James R. Hunt
4. Zvi Hochman
5. A. Patanothai
6. S. Jogloy
7. James W. Jones

Citations in the corpus

• Re-inventing model-based decision support with Australian dryland farmers. 3. Relevance of APSIM to commercial crops. (2009, methodology): “In similar tests in Argentina, Mercau et al. (2007) found that a locally calibrated CROPGROSoybean model explained only 41% of the measured variation in yields of soybean grown on commercial farms.”
• A sequential approach for determining the cultivar coefficients of peanut lines using end-of-season data of crop performance trials (2008, background): “, 2008), forecasting crop yield before harvest (Duchon, 1986; Bannayan et al., 2003; Yun, 2003; Nain et al., 2004; Mercau et al., 2007; Soler et al., 2007) and evaluating improved management options (Ruiz-Nogueira et al.”