Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uamuzi wa Tarehe ya Kupanda× | Uchunguzi wa Fenolojia× | |
|---|---|---|
| Nyanja | Agronomia | Agronomia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 2006 | 1974 |
| Mwanzilishi≠ | P. K. Aggarwal, N. Kalra, IARI India | Zadoks, Chang, Konzak (cereals); Fehr, Caviness (soybean) |
| Aina≠ | Decision support pipeline | Observational and classification pipeline |
| Chanzo asilia≠ | Aggarwal, P. K., Kalra, N., Chander, S., & Pathak, H. (2006). InfoCrop: A decision support system for crop planning and resource management at farm level. Agricultural Systems, 88(1), 56-77. link ↗ | Zadoks, J. C., Chang, T. T., & Konzak, C. F. (1974). A decimal code for the growth stages of cereals. Weed research, 14(6), 415-421. DOI ↗ |
| Majina mbadala | Planting date optimization, Sowing time selection, Phenological timing | Growth stage assessment, Phenological monitoring, Crop stage scale |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | Sowing Date Optimization is a decision support pipeline for determining optimal crop planting dates that align phenological development with favorable environmental windows, maximizing yield and reducing climate risk. Developed by crop modelers (Aggarwal, Semenov) in the 2000s, this method combines crop simulation, climate data, and risk analysis to identify safe, profitable sowing windows. | Phenological Observation is an observational and classification pipeline for systematically recording crop development stages from germination to maturity. Standardized through crop-specific scales (Zadoks for cereals, Fehr for soybean), this method enables precise communication of crop status, timing of management decisions (fungicide application, irrigation), and prediction of harvest readiness. |
| ScholarGateSeti ya data ↗ |
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