Geo-spatial sensing of physical properties a leeway to agricultural soil assessment

Abstract

The demand for economical means of evaluating soil nutrients’ unpredictability triggered the use of physical factors against the costlier, laborious, and time-consuming chemical approach. This drive led to resolving its capability in evaluating intricate soil properties as a productivity checker. This study aimed at assessing the physical parameters as a useful alternative to the conventional chemical examination of nutrient inconsistency. A petrographic examination was conducted on four rock samples for their classifications. Apparent Electrical Conductivity (ECa) measurements were seasonally executed in the wet (912-station) and dry (906-station). Ten cored soil samples were subjected to a permeability test. Twenty soil samples were examined for pH, Electrical Conductivity (EC), available phosphorus, acidity, Na, Mg, K, and Ca using standard soil science procedures. The mineralogical composition of six samples was determined with X-ray diffraction. The rock is biotite granite gneiss containing plagioclase (22%), microcline (24%), orthoclase (4%), quartz (25%), biotite (7%), and others (18%). The soils ECa were 10-344 µS/cm; categorised as low (1-49 µS/cm), moderate (50-99 µS/cm), and high (>100 µS/cm). The ECa distribution varied from moderate (61%) to high (64%) suggesting a heterogeneous pattern of soil attributes. The infiltration rate was slow in high ECa (5.56x10-5-1.67x10-4 cm/s) signifying good retention capability whereas the low and moderate ECa (moderate-moderately rapid) sections promote nutrient leaching. The cation exchangeable capacity was low (2.99 cmol/kg) in the low ECa and moderate (3.30-4.85 cmol/kg) in the moderate and high ECa; with varying basic cation saturation in the high (81.38%), moderate (73.34%) and low (71.89%) ECa regions and high ECa had higher fertility status. The high ECa had low quartz (41.3%) and microcline (15.7%), but high kaolinite (31.1%) had an affinity to ads orb more cations compared to other ECa regions. ECa variability is practicable in predicting the spatial distribution of soil properties and delineating the management zones. Key words: Granite gneiss, electrical conductivity, permeability, soil composition, mineral assemblages