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.
Soil physicochemical properties plant height regression models seed yield
Birincil Dil | İngilizce |
---|---|
Bölüm | Articles |
Yazarlar | |
Yayımlanma Tarihi | 1 Ocak 2020 |
Yayımlandığı Sayı | Yıl 2020 Cilt: 9 Sayı: 1 |