AGRICULTURAL PHYSICS, REMOTE SENSING AND GIS

5.5.1 Soil Physics

5.5.1.1 Development of soil quality indices for quantification of soil quality under cropping systems and tillage management

The assessment of soil quality for evaluating the sustainability of soil and crop management practices has become one of the important issues. Soil quality indices (SQI) were developed and evaluated for quantifying the changes in soil quality under two different cropping systems, viz., maize-wheat and rice-wheat, and two tillage practices in each cropping system. Twelve soil indicators consisting of five soil physical indicators, namely, bulk density, total porosity, mean weight diameter, available water capacity and saturated hydraulic conductivity, five soil chemical indicators, namely, pH, EC, soil nitrate-N, soil ammonium-N and organic carbon, and two soil biological indicators, namely, microbial biomass carbon and dehydrogenase activity, were measured which constituted the minimum data set for estimation of SQI. A total of eight indices were determined for all the treatments, which were Linear Simple Additive SQI (LSASQI), Linear Weighted Additive SQI (LWASQI), Linear Simple Multiplicative SQI (LSMSQI), Linear Weighted Multiplicative SQI (LWMSQI) (for linear approach) and Non-Linear Simple Additive SQI (NLSASQI), Non-Linear Weighted Additive SQI (NLWASQI), Non-Linear Simple Multiplicative SQI (NLSMSQI), and Non-Linear Weighted Multiplicative SQI (NLWMSQI) (for non-linear approach).

Among all the eight indices developed, the ‘Linear Weighted Additive Soil Quality Index (LWASQI)’ showed maximum sensitivity to represent soil quality changes due to cropping systems. LWASQI is also most responsive to soil quality changes due to tillage practices of conventional planting and bed planting in M-W and puddling and non- puddling in R-W cropping systems. The investigations with measured values indicate that the degree of sensitivity to reflect soil quality changes was higher in Linear than in Non- linear approach for all the treatments.

5.5.1.2 Mapping of soil physical properties for assessing cropping sequences by the use of crop simulation technique in GIS environment

Soil physical properties, namely, moisture content, bulk density (BD), hydraulic conductivity (HC) and available water capacity (AWC) were mapped on grid basis in the farmers’ fields of Shikohpur watershed. Bulk density, saturated hydraulic conductivity and moisture contents at 0.1 bar, 0.3 bar, 0.5 bar, 1 bar, 5 bar and 15 bar were determined for three depth layers (0-15 cm, 15-30 cm and 30-60 cm) for each of the 26 grids of the study area. It was found that the average value of BD of soil of Shikohpur watershed significantly varied from 1.54 Mg m^-3 to 1.60 Mg m^-3 between surface layer (0-15 cm) and lower layer (30-60 cm). A significant variation of 20 per cent was found in the HC of surface layer and lower layer, and for available water capacity, no difference was observed at different depths.

Spatially, all the properties varied significantly. Yields of crops grown in the watershed were simulated for each grid with these soil properties as inputs and yield maps were prepared for the study area. These yield maps were able to identify the areas producing low yields due to spatial variability in the soil physical properties.

5.5.1.3 Soil hydrothermal regimes and root growth under conventional, bed planted wheat and mustard A field study was conducted to monitor the soil hydrothermal environment under bed and conventionally

planted wheat and mustard crops. Temperatures at 0 cm, 5 cm, 10 cm, 15 cm and 20 cm depth were observed at hourly interval from 10 A.M. to 7 P.M. for variable soil water contents, aerial temperatures and relative humidity (RH) conditions. The results revealed that for similar frequency of irrigation, soil water content (SWC, w/w) of 0-20 cm of soil under bed was always lower by 2-3% after irrigation (SWC>10%) and temperatures were higher by 2-3 °C, but the differences in SWC and temperatures reduced to 0.5% and 1-2 °C, respectively, for drier soil (SWC<4%). Depending on atmospheric conditions, soil temperature peak arrived between 2 to 3 P.M. at surface, whereas the time of arrival of peaks at 5 cm, 10 cm and 15 cm depended on soil water status and varied between 3 and 4 P.M., 4.30 and 5.30 P.M.

and 5.30 and 6.30 P.M., respectively. For drier soils, the peak of soil temperature wave at bed surface was higher than aerial maximum by 1-2 °C. However, under high RH and high SWC, it became lower than aerial maximum by 2- 3 °C. Computation of thermal parameters of heat transport equation showed that most of the time, thermal diffusivity, thermal conductivity and heat capacity values were lower and hence damping depth was also less under bed than under conventional system.

Computed thermal parameters were used for simulating diurnal soil temperature fluctuations under both systems by solving heat transport equation by using the finite difference method. Simulated and observed data showed close agreement.

5.5.1.4 Pedotransfer functions for soil penetration resistance

Pedotransfer functions for soil penetration resistance were developed for soils belonging to soil orders, inceptisol and alfisol. Results suggested that at lower SWC, for most bulk densities, penetration resistance (PR) was higher under alfisol than under inceptisol but the trend was reversed at relatively higher SWC. The higher PR at lower SWC in alfisols was mainly due to hardsetting behaviour of red Chalka soils. For both soil types, value of SWCat 2MPa soil strength (lower limit of LLWR/water availability)at maturity (i.e., at higher compaction level) increased by 4-5% in comparison to its value at the initial stage with less compaction.

Comparison of eight indices for cropping systems

LSASQI LWASQI LSMSQI LWMSQI NLSASQI NLWASQI NLSMSQI NLWMSQI

M-W 60.19 3.36 36.42 91.83 64.13 11.47 38.04 91.68

R-W 49.69 0.98 28.40 82.77 51.80 8.8 29.16 82.35

CV 13.5 77.5 17.5 7.3 15.0 18.6 18.7 7.5

%

Change 17.4 70.8 22.0 9.9 19.2 23.3 23.4 10.2

Significant Significant Significant Significant Significant Significant Significant Significant

5.5.1.5 Effect of tillage and residue management on soil and plant in maize-mustard system

Field experiments were carried out on a sandy loam soil (Typic Haplustept) in semi-arid region of India to evaluate the effect of tillage (conventional and zero) and residue management (incorporation/retention/removal) on soil physical properties vis-à-vis plant growth in maize- mustard cropping system. Residue incorporation significantly (P=0.01) lowered the bulk density of surface (0-0.15 m) soil layer. Zero tillage with residue retention recorded significantly higher soil organic carbon (SOC) and microbial biomass carbon (MBC) and also significantly greater mean weight and geometric mean diameter of soil aggregates. Though a compact zone between 0.3 m and 0.4 m in the profile was observed in all the plots, residue incorporation reduced the soil resistance to penetration at surface (0-0.15 m). Zero tillage resulted in higher infiltration rates, both at initial and steady state. Emergence rates of seedlings were faster in zero tilled plots without residue for both maize and mustard crops, but the quick emergence could not be effectively transformed in producing more biomass or yield. However, increase in leaf area was faster under conventionally tilled plots with residue incorporation, and the peak leaf area index was also the maximum. Biomass at maturity differed significantly between conventional and zero tillage, but no difference was observed between residue management practices within same tillage system. Root weight density in maize was significantly higher in conventional tillage with residue incorporation, though at deeper depths, the differences were mostly insignificant. In mustard also, maximum root biomass was obtained under conventional tillage with residue incorporation. Although zero tillage optimized water use by both maize and mustard in comparison with conventional tillage, maximum water use efficiency was obtained in conventional tillage with residue incorporation, mainly because of maximum yield obtained under the treatment.

5.5.1.6 Effect of mulching on soil and plant water status, growth and yield in wheat (Triticum aestivum L.) in a semi-arid environment

Field experiments were conducted during winter seasons in a sandy loam soil to evaluate the soil and plant

water status in wheat under synthetic (transparent and black polyethylene) and organic (rice husk) mulches with limited irrigation practices as against adequate irrigation with no mulch (conventional practices by the farmers).

Though all the mulch treatments improved the soil moisture status, rice husk was found to be better in maintaining the optimum soil moisture condition for use by the crop. The residual soil moisture was also minimum, indicating effective utilization of moisture by the crop under rice husk. The plant water status, as evaluated by relative water content and water potential of the leaves was found to be more favourable under the rice husk mulch. Specific leaf weight, root length density and dry biomass were also higher with rice husk. Optimum soil and canopy thermal environment of wheat with limited fluctuations were observed under rice husk, even during dry periods. This also produced comparable yield with less water use, enhancing the water use efficiency. Therefore, under limited irrigation condition, rice husk mulching will be beneficial for wheat as it is able to maintain better soil and plant water status, leading to higher grain yield and enhanced water use efficiency.

5.5.1.7 Pedotransfer functions for predicting the hydraulic properties of Indian soils

Most of the data pertaining to Indian soils, is limited to only the major soil separates, viz., sand, silt and clay.

Therefore, an attempt was made to explore the possibilities of using these parameters to relate to the hydraulic characteristics of the soils of India. The final or steady state infiltration rate, which is mainly profile controlled, showed power function relationship with minimum and average clay content in the soil profile. The saturated hydraulic conductivity also showed similar relationship with silt+clay content. The soil water content at a given suction could be satisfactorily predicted using per cent of major soil separates, sand, silt and clay. The coefficients in the soil water function ψ(θ) were linearly related to the sand content of soil. Non-linear regression equations were developed to predict these coefficients using sand and clay per cent of soils. The equations prove to be quite satisfactory for a wide range of textures and provide reasonably accurate estimates of the soil water characteristic curve with a minimum of readily available data set.

5.5.1.8 Canopy hydro-thermal environment of wheat under long-term fertilization

A field experiment was conducted under long-term fertility trial in a sandy loam (Typic Halpustept) soil at IARI during rabi with wheat (cultivar HD 2329). Treatments were 50% NPK (T₁), 100% NPK (T₂), 150% NPK (T₃), 100% NPK + FYM @ 15 t ha^-1 yr^-1 (T₄), and control (T₅). Cumulative stress degree day (ΣSDD) was computed from canopy air temperature difference (CATD). Considerable higher transpiration rate was recorded with 100% NPK along with application of FYM @ 15 t ha^-1 yr^-1 compared to that of control, which also increased with crop growth. It increased from 4.5 µg cm^-2 sec^-1 to 13.6 µg cm^-2 sec^-1 in T₄ and 2.6 µg cm^-2 sec^-1 to 8.6 µg cm^-2 sec^-1 in control during growing season, leading to significant higher grain (5.48 t ha^-1) and straw ( 4.79 t ha^-1) yields in T₄ compared to those of control.

At flowering stage, significantly lower CATD (-6.5 °C) was observed in T₄ compared to that in other treatments, which might be due to that in higher transpirational cooling. A linear relationship was found between CATD and transpiration rate at different growth stages, which was poor at initial stages, but at fully developed canopy significantly higher inverse relationship (r = -0.82) was found. A negative correlation (r = -0.76) was found between ΣSDD and grain yield of wheat.

From this study, it can be concluded that remote sensing can be used as a potential tool for assessing leaf water status and yield of wheat.

5.5.2 Remote Sensing and GIS

5.5.2.1 Identifying potential zones for adoption of resource conserving technologies

Mau district of Uttar Pradesh and Patna district of Bihar were taken for identifying potential zones of RCTs. These districts, which have inherent problems of salinity, waterlogging and flood, were found to be the potential area for optimizing the agricultural land use through Resource Conserving Technologies. Time series multispectral remote sensing satellite data could be used to characterize the areas.

Late harvested rice followed by fallow or late sown crop in both the districts, saline areas in Mau district, and excessive moisture and flood in Patna district could be characterized through remote sensing data analysis, thereby identifying potential zones for adoption of different RCTs.

5.5.2.2 Land use cover change analysis with multi- temporal remote sensing data

In India, cities are usually surrounded by agricultural area, and changes, in particular, are harmful when urban expansion occurs against surrounding agricultural areas.

In the National Capital Territory of Delhi, urban expansion has been rapid at the cost of highly productive agricultural lands in its surroundings. Satellite remote sensing has been found to be a potential tool for quantification of such change in spatial-temporal scale. Land use cover change analysis of the NCR-Delhi was done using satellite data of 1977 and 2001, respectively, and different change detection techniques were evaluated. Spectral change detection techniques, except multi-date principal component (PC) can be used for identifying the temporal direction of changes. But they could not help find the type of land use change, for which post classification methods were found to be useful. Result of multi-date principal component analysis approach was comparable to that of direct multi-date classification approach. The major changing classes were built up area, vegetation (crop), and bare lands. There was 59.98% of growth in built-up area at the cost of vegetation (crop)/agriculture lands and bare lands.

5.5.3 Agricultural Meteorology

5.5.3.1 Modification in micro-meteorology of Brassica through de-branching and its effect on crop growth parameters

The de-branching in two Brassica varieties Pusa Jaikisan and Bio-169-96 facilitated higher radiation penetration to the ground which resulted in reducing the chances of occurrence of white rust and Alternaria blight diseases to a considerable extent. Apart from this beneficial effect, it was also observed that the radiation use efficiency, water use efficiency and heat use efficiency in the de- branched plots were relatively higher as compared to those of the control plots. The leaf area index in Bio-169-96 was observed to be higher than that of Pusa Jaikisan irrespective of the treatment. Moreover, the leaf area index in the de- branched plots was found to be marginally higher than that of the control plots.

5.5.3.2 Assessing the leaf area index and biomass production in mustard varieties by the use of thermal time

Based on the field experiments with two Brassica varieties (Pusa Jaikisan and Bio-169-96), thermal response curves were developed using thermal time as a base. The best-fit polynomial second order regression equations were developed taking LAI as a dependable variable with the thermal time, viz., growing degree days (GDD) as an independent variable. The growing degree days could explain 96% to 99% variation in LAI in different treatments in Pusa Jaikisan and Bio-169-96 in October 15 sowings and 95% to 98% in October 30 sowing. When the 2006-07 season data were pooled with the previous crop season data (two varieties and two seasons), the correlation coefficients were highly significant (at 1 per cent). Hence, the regression equations were developed which will be of immense use in assessing the leaf area index by the use of the thermal time, without destroying the plant samples. Similarly, by the use of thermal response curves of biomass production, regression equations were developed to assess the biomass production at different intervals of time, without destroying the plants. However, caution is required when the data over varieties are pooled, as they might lead to considerable errors. It would be worthwhile to develop equations, which are variety and location specific. These types of quantitative relationships would go a long way in dynamic crop simulation modeling studies.

Thermal response curves: (top) for leaf area index (LAI), and (bottom) for biomass in mustard under control(D0), and debranched at 50 DAS(D1) and at 60 DAS(D2)

Effect of debranching on ground shading inhibiting the radiation penetration to the ground level (left: control, right:debranched plots)