CORN productivity data is needed to sustain the farm production. …… This research was conducted to evaluate soil productivity of two different soil texture, clay loam (soil1)and loam (soil2) using three productivity index models (PI1, PI2 and PIM). Five soil properties were chosen to calculate the productivity index for the model PI1 namely, soil available water, soil bulk density, pH, EC, and root depth. Two more parameters, clay content and organic matter, were included in the original PI1 model to calculate PI2. The calculation of PIM index was depending on different irrigation treatments; i.e. 50%, 70%, 80% and 100% of available soil moisture and on crop evapotranspiration besides the soil properties used in the original PI1 model. Obtained results showed that the estimated values of PI1 were 0.57 and 0.52, whereas, for PI2 were 0.28 and 0.22 for soil1 and soil2, respectively. On the other hand, values of PIM increased as soil moisture increased. The highest PIM (0.46 and 0.45) were obtained with 80% irrigation treatment, whereas, the lowest PIM (0.34 and 0.33) were obtained with 50% irrigation treatment of soil1 and soil2, respectively. The results revealed that soil1 has higher productivity potential than soil2, where the calculated values of PI1, PI2 and PIM were higher for soil1 than for soil2. When comparing the calculated values of PI1, PI2 and PIM with the relative values of soil productivity, the PI1 values showed that both soils are very high productive soils. Whereas, PI2 showed that both soils have moderate productivity. In contrast, the PIM values under all irrigation treatments indicated that both soils have high soil productivity. The higher and lower corn yields corresponded to higher and lower productivity indices values, respectively in both soils. A highly significant correlation between seed yield and PIM (R2 = 0.97) was obtained. Whereas, the relationship between seed yield and actual evapotranspiration explained about 84% of the variation in corn yield (R2 =0.84). These results concluded that PI1 andPIM models were effective in quantifying soil productivity and seem to be good prediction models of corn yield.
(2015). Evaluation of the Productivity of Two Soils Using Productivity Index. Egyptian Journal of Soil Science, 55(2), 171-184. doi: 10.21608/ejss.2015.314
MLA
. "Evaluation of the Productivity of Two Soils Using Productivity Index". Egyptian Journal of Soil Science, 55, 2, 2015, 171-184. doi: 10.21608/ejss.2015.314
HARVARD
(2015). 'Evaluation of the Productivity of Two Soils Using Productivity Index', Egyptian Journal of Soil Science, 55(2), pp. 171-184. doi: 10.21608/ejss.2015.314
VANCOUVER
Evaluation of the Productivity of Two Soils Using Productivity Index. Egyptian Journal of Soil Science, 2015; 55(2): 171-184. doi: 10.21608/ejss.2015.314
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