The relation between yield indices of maize plant and soil physicochemical characteristics
The aim of this study was to set regression models based on correlation between yield parameters of maize plant (height, thousand seed weight and yield) and physical and chemical characteristics of soils and to determine applicability of obtained models in estimation of plant yield grown in soils of...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Federation of Eurasian Soil Science Societies
2020-01-01
|
| Series: | Eurasian Journal of Soil Science |
| Subjects: | |
| Online Access: | http://ejss.fesss.org/10.18393/ejss.644038 |
| Summary: | The aim of this study was to set regression models based on correlation between yield parameters of maize plant (height, thousand seed weight and yield) and physical and chemical characteristics of soils and to determine applicability of obtained models in estimation of plant yield grown in soils of Çarşamba Plain. Regression coefficient (R), root mean square error (RMSE), index of agreement , model efficiency (ME) were evaluated to determine the validity of regression models between the yield components and physical and chemical characteristics of 40 soil samples taken from root zone of cultivated farms. Model associated with the relation between (i) plant height and bulk density (BD), field capacity (FC), clay and sand content wasn’t statistical significant (R= 0.53, p>0.05); (ii) thousand seed weight and soil electrical conductivity (EC), organic matter (OM), lime (CaCO3), nitrogen (N), phosphorus (P), potassium (K), Ca + Mg was characterized with a moderate R (R=0.79, p < 0.05), and (iii) seed yield and OM, N, P, K, copper (Cu), cation exchange capacity (CEC), CaCO3 indices has the highest R (R = 0.87; p <0.01). In general, statistical parameters were within the validity limits. The established regression models can be applied for the predicting of yield parameters of maize plant grown in the farmed areas of the region. |
|---|---|
| ISSN: | 2147-4249 2147-4249 |