**4.9 Analysis**

#### *4.9.1 Laboratory and statistical analysis*

The laboratory analysis of soil samples was done at the Soil Science Laboratory, University of Agriculture, Makurdi. Hydrometer method, as explained by Gee and Bauder [82], was used for determining the particle size. The pH meter with glass electrode was utilized for determining the pH of soil in water, 1:2 of soil:water ratio. Experimentation with flame photometer, as described by Udo et al. [83], was utilized to determine cation exchange, whereas potassium and sodium, calcium and magnesium were determined in the extract by ethylenediaminetetraacetic acid (EDTA) titration. The dichromate wet-oxidation method, as explained by Nelson and Sommers [84], was used for getting organic matter content. Phosphorus content was realized by the Bray-1 step, as described by the researcher Kuo [85]. The available nitrogen was obtained by the micro-Kjeldahl digestion and distillation system, as put forward by Bremmer [86]. Cation exchange capacity (CEC) was determined according to the method explained by Sumner and Miller [87]. The data obtained on growth and yield parameters of okra during the study were subjected to test and analysis using IBM SPSS Statistics Version 21 software. Among the determined components were correlation, regression and analysis of variance (ANOVA).

#### **4.10 Results and discussion**

#### *4.10.1 Soil properties of the experimental site*

**Table 1** shows the result of pretreatment of soil physical and chemical properties of the study site. Thus, textural class of soil is sandy loam having higher percentage of sand particles among all points below the soil surface taken, viz., 0–15, 16–30 and 31– 45 in centimeters and the presence of acidic content was noticed in the different depths. Soil within 0–15 cm depths showed more values of organic matter, followed by points 16–30 and 31–45 accordingly, confirming organic matter decreases with soil depth. The soil available N, P content, cation exchange capacity (CEC), Mg and organic matter were found to be minimal, indicating the inherent low fertility status of tropical soils, as reiterated by Ojeniyi [88].

#### *4.10.2 Soil properties as influenced by treatments, growth parameters and yield of okra*

Odey [25] further revealed that the structural properties of soil were affected during field experiment (see **Tables 2** and **3**). **Table 2** shows how the different soil manipulation methods influenced physiochemical properties of soil during growth stages of okra. The results indicated that the treatments have a very similar textural class, sandy loam soil, with a higher percentage of sand characteristics showing in the various treatments. Soil pH remained acidic in all the treatments. Organic matter was maximum at 0–15 cm depth in both conventional and conservative tillage than 16– 30 cm and 31–45 cm depths apart from zero tillage.

On the other hand, different tillage systems did not lead to rise in soil N, P content, cation exchange capacity (CEC), Mg, Ca and Na in the different depths under study. These results correspond with the findings of Brady and Weil [89], which revealed that soil contains minerals, organic matter, air and water; confirming the submission of Carter [90] who reported that soil textural class is made of clay, sand and silt.

Thus, conventional and conservative soil manipulation methods resulted in increased output of the crop than the output from no till method system. These findings concurred with the submission of Lal [91], which reiterated that various soil manipulation methods have effects on okra output.

#### *4.10.3 Analytical results for properties of soil, development and okra output*

According to Odey [25], the experimental results in **Table 4** revealed the analytical results for properties of soil, development and okra output. There is a strong positive


**Table 1.**

*Properties of soil at various depths before treatments of agricultural field.*

*Modeling Growth and Yield of Crops Using Different Tillage Systems DOI: http://dx.doi.org/10.5772/intechopen.113410*


**Table 2.**

 *Properties of soil as affected by field experiment.*

*Modeling Growth and Yield of Crops Using Different Tillage Systems DOI: http://dx.doi.org/10.5772/intechopen.113410*


#### **Table 3.**

*Average data for density of soil, voids, development and output of okra.*


#### **Table 4.**

*Analytical values of properties of soil, development and okra output.*

relationship between height, width and leaves of okra, showing the correlation between height and width of okra tending to 1 (1.0), and in agreement to that of leaves and width. The findings are related to the assertion of Ariyo and Akenova [92], which expressed a strong affiliation among the development criteria of crops. Hence, there is a strong positive correlation among okra development and output and soil voids. Thus, as densities of voids were 1.000, tallness, breadth, leaf count, flowering and okra output maintain their stand at 0.5248, 0.4904, 0.6115, 0.6825 and 0.6909 accordingly. Whereas, sturdy adverse correlation was displayed between densities of soil, development and okra output. When densities of soil were 1.000, soil voids were 1.000, while tallness, leaf count, flowering and okra output stood at 0.5249, 0.4904, 0.6115, 0.6825 and 0.6909, respectively.

#### *4.10.4 Regression of soil properties and growth parameters with yield of okra*

Odey [25] reported an analytical work carried out on properties of soil densification of soil and voids, development data and okra output, with the dependent variable as okra output (see results in **Tables 5** and **6**). Mathematical expression for okra output per hectare was determined from the analyzed results presented. Hence, predetermined model for okra output on agricultural field experiment conducted by different soil manipulations was inferred.

$$Y\_o = -84.64 + 12.23\_{\text{bd}} + 93.96\_{\text{p}} + 0.21\_{\text{H}} - 0.24\_{\text{NL}} + 0.20\_{\text{T}} \tag{5}$$

Where,

*Yo* = okra output Bd = soil bulk density P = soil porosity H = okra plant height N*L* = numbers of leaves of okra T = experimental treatment

The model eq. 5 above had a R2 value, 0.934. The distinctions among mean values of estimated and observed okra output at 95% confidence level were applied to infer when statistical tools were used. According to Odey [25], t-test results revealed—no important difference at (p > 0.05) between experimented and predicted output of okra recorded when various soil manipulation methods were carried out. It can be


#### **Table 5.**

*Regression coefficients.*


*aPredictors: (Constant),Treatment, No. of leaves, Bulk density, Height, Porosity.bDependent variable: Yield of okra Odey [25].*

**Table 6.** *Model summary.*

#### *Modeling Growth and Yield of Crops Using Different Tillage Systems DOI: http://dx.doi.org/10.5772/intechopen.113410*

inferred that the forecasted output expression has close relation to the actual okra output. Therefore, the model is utilized in forecasting the production of okra in advance for any given agricultural field, provided other data are known. These findings agreed with the assertion of Mulumba and Lal [93], which stated that tillage practice is a management input that influences soil physical characteristics, which in turn touches growth and yield of crops.

Odey [25] concluded that the field study conducted was aimed at modeling okra growth and yield using different tillage systems, with the intention of predicting the output of okra. Field data were obtained and analyzed using appropriate tools. Findings revealed the negative relationship among development data, okra output and soil densities. Whereas, porosity of soil showed positive relationship among development criteria and okra output. Okra output was more in conventional and conservative tillage than in no till system. Modeled equation with R squared, 0.934 on the okra output using different tillage practices was created from the regression analysis, showing forecasted output almost equaled observed okra yield. The output of okra is estimated during cultivation, provided soil physical properties and growth parameters of okra are identified as in Odey et al. [94]. Odey [25] recommended conventional and conservative tillage systems for enhancement in the production of okra on soil with sandy loam texture.
