DEVELOPING GENETIC COEFFICIENTS FOR CROP SIMULATION MODELS WITH DATA FROM CROP PERFORMANCE TRIALS

By T. Mavromatis, Kenneth J. Boote, James W. Jones, A. Irmak, D. Shinde, Gerrit Hoogenboom. 2001

155 citations recorded by the source corpus.

Subfields: Plant Science

View Paper: https://www.semanticscholar.org/paper/d1fbdb06956ba56b523e25a865a34bd6175762f8

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In Plant Science

1. Kenneth J. Boote
2. James W. Jones
3. Gerrit Hoogenboom
4. Cheryl H. Porter
5. J. Ritchie

Citations in the corpus

• Crop modeling, QTL mapping, and their complementary role in plant breeding (2003, unknown): “and explain genotype environment interactions To map quantitative traits, supplementary informa(G E) (Mavromatis et al., 2001) tion from recognizable single-gene loci is required.”
• Determining optimum planting dates for pearl millet for two contrasting environments using a modelling approach (2008, result): “Other studies have shown that models can be rather useful for planting date analysis, compared to resource intensive experimental studies (Mavromatis et al. 2001; Saseendran et al. 2005).”
• The DSSAT cropping system model (2003, methodology): “For additional information on phenology in CROPGRO see papers by Boote et al. (1998a,b), Grimm et al. (1993) (1994), Piper et al. (1996a,b), Mavromatis et al. (2001).”
• Predicting on-farm soybean yields in the pampas using CROPGRO-soybean (2007, methodology): “, 1996a) and yield (Colson et al., 1995; Mavromatis et al., 2001; Calviño et al., 2003).”