Agriculture Reference
In-Depth Information
HAl
CEC
+
Acidity saturation
(%) =
× 100
Ca
CEC
Mg
CEC
K
CEC
SaturationofCaMgorK
,
,
(%)
=
×
100
,
×
100
,
or
×
100
Ca
Mg
Ca
K
Mg
K
Ca,Mg, or Kratios
= ,
,
or
Analysis of variance should be used for data analysis and the quadratic regression model and is
generally used to describe the yield and yield component responses to fertilizer or nutrient rates and
soil chemical properties or indices. The quadratic response function is the most common functional
form to evaluate the yield response to applied nutrient rates and soil chemical properties or indices.
The quadratic model is a second-order polynomial function written as
Y = a + bx + cx
2
where Y is the estimated yield, x is the application rate of the nutrients, and soil chemical proper-
ties or indices a, b, and c, are coefficients estimated by fitting the model to the data. The quadratic
function assumes that crop yield will increase at the decreasing rate as the nutrient application rate
increases until the maximum yield is achieved at
N(Y
max
) = b/2c
where N(Y
max
) is the level of applied nutrient that achieves maximum yield; past this point, the yield
decreases.
In addition to the above observations related to the greenhouse and field experiments, data
related to yield should be presented in metric units. Similarly, nutrient concentration in soil and
plants should be expressed in mol m
−3
or mmol.
3.7.2.2 Experimental Results
The author studied the response of lowland rice to N fertilization under field conditions. The sig-
nificance of F values derived from the analysis of variance showed significant responses of rice
grain yield and yield components to N rates and years of cultivation, but the year × nitrogen rate
(Y × N) interactions were significant only for grain yield (Fageria and Baligar, 2001) (Figure 3.38).
Therefore, the grain yield data for 3 years as well as the average values of 3 years are presented.
Grain yield increased with N fertilization and showed significant (P < 0.01) quadratic responses in
the 3 year experimentation (Figure 3.38). Based on the regression equations, in the first year, maxi-
mum grain yield (6937 kg ha
−1
) was obtained at 209 kg N ha
−1
; in the second year, maximum grain
yield (6958 kg ha
−1
) was obtained at 163 kg N ha
−1
; and in the third year, maximum grain yield of
5682 kg ha
−1
was obtained at 149 kg N ha
−1
.
The average data for three years showed that the maximum grain yield of 6465 kg ha
−1
was
obtained with the application of 171 N ha
−1
. Singh et al. (1998) reported that the maximum aver-
age grain yield of 7700 kg ha
−1
of 20 lowland rice genotypes was obtained at 150-200 kg N ha
−1
at the International Rice Research Institute in the Philippines. Our results fall more or less in the
same range. In our fertilizer experimentations, however, 90% of maximum yield is considered as
an economical rate (Fageria et al., 2011a); in the first year, it was 6298 kg kg
−1
achieved at 120 kg
N ha
−1
. In the second and third years, 90% of the maximum grain yields (6345 and 5203 kg ha
−1
)
was achieved at 90 and 78 kg N ha
−1
, respectively. The average of 3 year data showed that 90% of
