Tropical Ecology 51(1): 41-54, 2010 ISSN 0564-3295 © International Society for Tropical Ecology www.tropecol.com

A GIS-based land use suitability assessment in Seoni district, Madhya Pradesh, India

S.V. BOBADE, B.P. BHASKAR*, M.S. GAIKWAD, P. RAJA, S.S. GAIKWAD, S.G. ANANTWAR, S.V. PATIL, S.R. SINGH & A.K. MAJI

National Bureau of Soil Survey and Land Use Planning, Nagpur 440 010, India

Abstract: A land evaluation for agricultural planning in Seoni district was carried out based on soil survey data within a geographical information system. The soil-based GIS data was compiled and interpreted for land use suitability and fertility assessment. Maps of fertility and land use suitability were generated from interpretative records. A suitability map for each agricultural land use was developed by combining the climatic and soil site factors for each crop. The land use suitability analysis indicated that 44% of land was non-arable and was found to be suitable for silvipasture and wildlife conservation and 56% of land was arable, of which, 24% was found to be suitable for sorghum-soybean and 15% for sorghum-cotton systems that can be productive despite a deficiency of potassium and zinc. The remaining 18% area was recommended for rice, citrus, maize, sunflower and vegetables. The mapping exercise was carried out to identify land units with suitable crops and to suggest alternative practices, where the current land use is suboptimal.

Resumen: Se llevó a cabo una evaluación del suelo para la planeación agrícola en el distrito

Seoni con base en datos de una investigación de suelos en un sistema de información geográfica. Se compilaron los datos de suelo basados en el SIG y se interpretó su aptitud de uso de suelo y la evaluación de su fertilidad. Se produjeron mapas de fertilidad y aptitud del uso del suelo a partir de registros interpretativos. Se elaboró un mapa de aptitud para cada uso agrícola del suelo por medio de la combinación de los factores de sitio climáticos y edáficos para cada cultivo. El análisis de la aptitud del uso del suelo indicó que 44% de la tierra no tenía aptitud agrícola sino que era adecuada para la silvicultura y el pastoreo, y para la conservación de la vida silvestre, y que 56% de la tierra era cultivable, de la cual 24% era adecuada para el cultivo de sorgo y soya, y 15% para sistemas de sorgo-algodón que pueden ser productivos a pesar de una deficiencia de potasio y zinc. Para el 18% restante del área se recomendó el cultivo de arroz, cítricos, maíz, girasol y verduras. Este ejercicio cartográfico tuvo por objeto identificar las unidades terrestres con sus cultivos más adecuados y sugerir prácticas alternativas para aquellos sitios donde el uso actual del suelo es subóptimo.

Resumo: Uma avaliação do solo para o planeamento da agricultura no distrito de Seoni foi

efectuada com base nos dados do inventário com um sistema de informação geográfico. Os dados do solo baseados no SIG foram compilados e interpretados para a capacidade de uso do solo e avaliação da fertilidade. Os mapas de fertilidade e de capacidade de uso foram gerados a partir de registos interpretativos. Um mapa para cada uso adequado de solo agrícola foi desenvolvido pela combinação dos factores de clima e solo para cada cultura. A análise da capacidade de uso do solo indicou que 44% do solo não era arável mas era satisfatório para a silvo-pastorícia e conservação do bravio e 56% era arável , dos quais 24% eram bons para sorgo-soja e 15% para sistemas sorgo-algodão e que podem ser produtivos não obstante uma deficiência em potássio e zinco. Os restantes 18% eram recomendáveis para arroz, citrinos, milho, girassol e hortícolas. O exercício de mapeamento foi levado a feito para identificar as unidades de solo para a melhor

* Corresponding Author; e-mail: bhaskar_phaneedra@yahoo.co.in

42 LAND USE SUITABILITY ASSESSMENT

afectação de culturas e para sugerir praticas alternativas, onde o uso do solo se encontrava sub-optimizado.

Key words: Conservation planning, fertility, GIS, land use suitability, soil mapping unit.

Introduction

The land use planning involves making knowledgeable decisions about land use and the environment. Soil information is a vital component in the planning process, reflecting directly upon land-use suitability (Coleman & Galbraith 2000). The utility of soil–land resource information for proper agricultural land use was proposed by Dumanski et al. (1987). The land evaluation system of FAO (1983) was based on land qualities as related to individual crops that was used to develop the crop requirements based on experi-ences in tropical areas (Sys et al. 1993). This land evaluation system for land use was earlier adopted to derive land suitability map in western parts of Maharashtra (Bhattacharyya et al. 1992) and in Nera watershed of Himachal Pradesh (Murthy et al. 1984). Advanced techniques have been made recently towards extraordinary digital systems for utilization in land-use planning. Computer program, that includes decision support systems (models) and Geographic Information Systems (GIS) have contributed to the speed and efficiency of overall planning process.

Quick and efficient access to large amount of information was enabled by GIS, exhibiting relationships, patterns, and trends (ESRI 1999) that are useful in combining soil survey information to monitor land use changes (Stout & Lee 2004; Wu et al. 2001). Application of GIS in Land Use Planning was well documented (Kushwaha et al. 1996; Maji et al. 1998, 2001, Salem et al. 2008). Soil survey database could be used to estimate soil characteristics based on known relationship to other soil physical and chemical properties (Brubaker et al. 1993) and also to improve fertilizer recommendations on the basis of soil test values (Seok et al. 1999). Of late, advanced land evaluation techniques have been found useful in addressing soil fertility constraints and management problems in the areas of low productivity (Hong & Park 1999). In some of such

areas, that are inhabited by tribal farming communities, crop failures were experienced frequently due to traditional agricultural practices. These areas should be given priorities for improved crop planning and agricultural development. Therefore, the study is aimed at using GIS for the integration of soil survey data to assess land use suitability to enhance land allocation processes for agricultural usage in Seoni, a tribal district of Madhya Pradesh.

Materials and methods

Study area Seoni district is one of the southern districts of

Madhya Pradesh and spread over 8,752 km2 area. About 90% of total population of 1,166,608 (as per 2001 census) is tribal. The district (21° 35' - 22° 58' N and 79o 12' - 81° 18' E) is bordered by Jabalpur, Narsinghpur and Mandla districts in the north, Balaghat in the east, Chhindwara in the west and Nagpur district of Maharashtra in the south (Fig. 1). The geology of the district comprises of Tirodi Biotite Gneiss (TBG), Quartzite, Mica Schist of Supracrustal Sausar Group - (SSG), Calc Silicate rocks of Lohangi series, Muscovite-Biotite schist of Mansaur series, Quartzite, Quartz-Muscovite schist of Charbaoli series and Crystalline Limestone and Dolomite of Bichua series (GSI 2002) in the southeastern parts, whereas, remaining part of the district was covered by Deccan Traps with sporadic occurrence of lameta, intertrappean beds, laterite cappings and Meso-Proterozoic to recent alluvium. The area forms part of the Narmada river system, that occupies about 25% of the area in the north of the district and the Wainganga river system occupying about 75% of the area in the south. The area experiences a tropical monsoon climate with ustic soil moisture and hyperthermic soil temperature regime. The mean annual rainfall (MAR) recorded was 1385 mm, of which about 85% was received during June to September. A detailed note on soils, landforms, land capability, cropping

BOBADE et al. 43

systems and degradation status at state level was reported by Tamgadge et al. (1999) and Tamgadge et al. (1999a, b & c). About 75% of the area in the district is covered by forest of teak and bamboo. The major forest belt runs from east to west along the Satpura hill ranges and north to south along the foot hills near the Seoni town. The district has a net sown area of 364,502 ha, of which 281,255 ha was under kharif (wet season) and 179,215 ha was under rabi (dry season). About 95,968 ha area was double cropped with irrigation potential of 35% (District Statistical Report 2003).

Methods A geo-pedological approach (Zinck 1988) was

applied for the local physiographic analysis. This approach was used to cover large areas rapidly by establishing relationships between landforms and soils. The landform map was generated as per standard procedures (USDA 1995), that has

fourteen landforms over basaltic and granitic landscapes of the district on 1:50,000 scale covering twenty-one topographical maps of Survey of India. The soil profiles were morphometrically examined and soils were classified up to subgroup level described by USDA (1998). Soil series were described and used mainly for practical purposes (Sohan Lal et al. 1994). The approach for the correlation of soil series in the field was done as described by Reddy (2006). The paradigm of the study is illustrated in Fig. 2. The soil information system constituted a set of files in GIS under a relational database management system. The spatial soil data were generated by digitizing 1:50,000 scale Survey of India topographical maps using ARC/INFO. The topology of each polygon was built and all spatial datasets had polyconic projection. The land use plan was prepared from thematic maps with the land capability classification (Klingebiel & Montgomery 1961), land suitability (FAO 1976; Sys et al. 1991) and

Fig. 1. Location of Seoni district.

44 LAND USE SUITABILITY ASSESSMENT

Fig. 2. Approach of this study.

the fertility capability classification (Sanchez et al. 1982).

A system approach was used to classify and map the landscapes by studying the expressions of landscape structures and anthropogenic activities. The survey and mapping of landscapes has four important aspects such as determination of landscape potentialities, determination of suitability of landscapes for different land uses and the conflicts of demands in time and space, characterization of current natural and anthropo-genic stresses and their capacity to resist the stress, spatial and temporal availability of land for use as limited by natural conditions, their spatial structures and existing land use pattern (Hasse 1989). The district was divided into five physiographic units viz., Lakhnadon plateau, upper Wainganga valley, the Sagar and Hirvi river valley, the lower Wainganga valley and the Southern lowland.

Results and discussion Landforms

The total area and the basic structure of landforms were defined by general normative elements (Table 1). The fourteen landforms were delineated (Fig. 3) and the area under each landform was estimated as (i) structural plateaus (26,968 ha), (ii) middle level plateaus (71,595 ha), (iii) narrow inter-hill basin (81,458 ha), (iv) structural hills and ridges (152,668 ha), (v) undulating plateaus (60,022 ha), (vi) rolling pediplains (58,547 ha), (vii & viii) upper and lower denudational plateaus (325,962 ha), (ix) steeply sloping denudational escarpments (17,973 ha), (x, xi, xiii and xiv) valleys, broad inter-hill basins, gently sloping plains and ridges (79,535 ha) and (xii) isolated hillocks (1,074 ha). Similar types of land forms were reported in basaltic terrain of central India by Reddy et al. (2004) and used

Agricultural Information Theory, Crop Calendar, Cropping Intensity, Current Land Use, Irrigation/Water Sources, Agricultural Population

& Forestry-Wildlife Criteria

Physiography-Soil Database

Forestry, Silvipasture & Wildlife Conservation

Arable Non-Arable Fertility Capability

Spatial Data Integration in GIS

Rice-wheat, Soybean-Sorghum & Wheat-Sorghum

Soil Survey

Land Suitability

BOBADE et al. 45

Table 1. Types and extent of landforms in Seoni district.

Types of Landforms Area (ha) Structural plateaus: High drainage density and severely eroded steep land with slopes of 3 to 8%. This is widely occurring in Lakhanadon plateau at an elevation of 700m and above.

26968 (3.1)

Middle level plateaus: This unit is moderately eroded, moderately sloping lands (8-15%) between 500 and 700m and cultivated for wheat, rice, sugar cane, mustard but at few places, vegetables are grown.

71595 (8.2)

Narrow inter-hill basins: mostly occurs in Ghansur, Kahani, and Hiran sub-basins of the Sher and Hiren rivers.

81458 (9.3)

Structural hills and ridges: Linear continuous features with rock outcrops, steep stony lands, sparse forest cover and the ridges running east-west wards with rock sheets.

152668 (17.4)

Undulating plateaus: Located in western part at an elevation of 300 to 400 m, severely eroded, highly dissected, 30% of surface area covered by stones.

60022 (6.9)

Rolling pediplains: Mostly occurs between 600 and 700m elevation towards Mohgaon to Barjhkar, moderate erosion with gentle slopes running east-west, has mostly 2nd order streams.

58547 (6.7)

Upper denudational plateaus: Isolated hillocks, erosional pediment surfaces, dissected 1st order streams on flat plateau tops with 50% surface stones, thin forest cover, concentrated in south-west, cultivation in patches between 500 and 600 m.

170451 (19.5)

Lower denudational plateaus: Barren rocky surface covered with open thin forest cover, cultivation in patches, highly dissected and moderately eroded.

155511 (17.8)

Steeply sloping denudational escarpments: Steeply sloping escarpments (30-50% slopes), severely eroded, highly dissected, surface stoniness is >50%.

17973 (2.1)

Valleys: Flat, gently sloping (3-8%), strongly associated with river systems of Wainganga of upper and lower reaches, mostly under double cropping (rice, wheat and soybean).

14675 (1.3)

Broad inter-hill basins: On plateaus with gentle slopes, slight erosion, intensively cultivated, occurs in small areas.

2526 (0.3)

Isolated hillocks: Granitic landscapes, mostly covered with stones and rock outcrops, thinly vegetated, mainly used for stone quarrying.

1074 (1.2)

Gently sloping flood plains: Common in southern lowlands with slopes of 3 to 8%, mostly under cultivation of wheat, red gram and soybean.

60822 (7.0)

Ridges: Continuous, residual forms of hills with linear feature, covered mostly with stones and rocks used for quarrying stones.

1512 (0.2)

(Values in parenthesis indicate the percentage)

for land evaluation schemes. Different strategies could be formulated in land use planning based on the different landscape elements described.

Soil map The spatial distribution of soils was presented

(Fig. 4) and the soil mapping units were designed as soil series association with their symbols. The soil mapping units in the northern plateaus are of Parasia (Pc)-Pipariya (Pr)-Khamariya (Ky) soil series association in Lakhnadon plateau occupied 11.6% of total geographical area (TGA). The soils of these series are very shallow, well drained, sandy clay loam texture and were cultivated for sorghum and redgram. About 10.4% of TGA was covered by Sagar (Sa)–Paddikona (Pd)–Khamariya (Ky)–Parasia (Pc) series, that are mostly under lower denudational plateaus. The soils of these series are moderately deep to very deep, clay in texture and were cultivated for paddy and soybean. The dominant soil mapping units in

southern lowlands of hills and ridges were Sukla (Sk)-Jamunola (Jm)-Rukhad (Rk) covering 7.5% of TGA with loamy sand to sandy loam textured soils, mostly covered by teak forest. These land units are frequently covered with thick forest vegetation and support the tiger habitat in the Pench reserve forest area.

About 4.8% of the TGA was covered by Parasia (Pc), Paddikona (Pd) and Khamariya (Ky) mapping units, that are shallow to very shallow clay soil associations, concentrated in the northern plateaus of Seoni district, and are mostly covered with pastures and only scanty area was cultivated for millets. About 16.4% of the TGA was on lower denudation plateaus and interhill basins, that are concentrated on northern and central part of the district, consisting of mapping units such as Arandiya (Ar), Kharsaru (Kh), Bhimgarh (Bg), Nadora (Nd), Silghat (Si), Atari (At) and Chuui (Cu), Dhenka (Dk), Paddikona (Pd), Sagar (Sa), Jamunpani(Jp), Chunamati (Ch) and Parasia (Pa),

46 LAND USE SUITABILITY ASSESSMENT

Khamariya (Ky), Gorakhpur (Go) and Lakhnadon (Lk). The soils of these associations were mostly clayey, deep to very deep and poorly to moderately well-drained.

Soils over structural hills, escarpments and severely eroded plateau tops are very shallow (<10 cm) to shallow (25-50 cm), somewhat excessively drained, sandy clay loam to clay loam texture and are mainly cultivated for millets and kondon kutki (a staple food in the form of pej). The mapping units are Khamariya (Ky), Atari (At), Parasia (Pc), Nadora (Nd), Sagar (Sa), Dhora (Dh) and Lakhnadon (Lk), Pipariya (Pr), that covers 16.9% of area, mostly concentrated in central Wainganga, Sagar and Hirvi valley. The soil

associations in southern lowlands under forest have sandy clay loam to clay texture, well drained, and shallow to deep soils covering 14.7% of the area. The mapping units are Kanera (Kn), Bisapur (Bs) and Jamuntola (Jm), Khawasa (Kw), Sukla (Sk), Tarali (Ta), Lungsa (Lu) and Lakhnadon (Lk) and Dhora (Dh)-Sukla (Sk), Prattappur (Pt).

Fertility characteristics Eight units of fertility capability (Fig. 5) were

derived and were defined in the combinations of type, substrata type and modifiers (Sanchez et al. 1982). The fertility capability classification (FCC) of basaltic soils have showed that these soils has clay surface texture with low infiltration, good

Fig. 3. Landform map of Seoni district.

BOBADE et al. 47

Fig. 4. Soil map of Seoni district.

Source : Tamgadage et al. (2008)

48 LAND USE SUITABILITY ASSESSMENT

Fig. 5. Fertility capability classification of soil units.

BOBADE et al. 49

water holding capacity, high shrink-swell potential and were highly productive. The FCC class for these soils was defined as CCvdb. Certain characteristics were particularly important in determining capabilities of various soil series

(Table 2). The modifiers and symbols that were used such as root-restricting hard substrata (R), low K reserves (k) and high P fixation in Khamariya series, r+ for 15-35% gravel by volume in Dhora series, v for severe topsoil swelling and shrinking in Gorakhpur series. The FCC unit of loamy textured surface soils in granitic landforms (Kanera, Arandiya, Jamuntola and Pipariya series) with root restricting hard substrata, that was defined as LRd, whereas, in Bisapur and Rukhad series with sandy top soil, with low water

holding capacity, low K supply and 15-35% gravels were defined as SSr+bk. The spatial distribution of units were in the ascending order viz., LRdik (6.1%) > CCvdik (7.3%) > CCRdv (9.7%) > LLdk (16.6%) > CCvdb (38.7%).

The availability of NPK Soils were grouped into three fertility classes

based on level of acceptance of critical limits (Benton Jones 2001). Group 1 soils (Gondatola series) have low N, P, K and Zn status. Group 2 soils (Prattappur & Chunamati series) have medium K status and lower amount of N, P, Fe and Zn. The Group 3 Aradiya series have high K and low in N, P and Zn status. The NPK status in the soils (Table 2 & Fig. 6) have showed that 40.3% of soils in northern Lakhnadon plateau have

Table 2. Soil mapping units based on NPK status.

Rating N P K

Soil Mapping Unit Area (ha) (%)

Low Low Low Sukla (Sk)-Jamuntola-Bisapur(Bs)(20) 50489 5.8 Low

Low

Medium

Parasia (Pc)-Paddikona (Pd)-Khamariya (Ky)(1),Parasia-Pipariya(Pr)-Khamariya (2),Sagar-Paddikona-Khamariya(3),Khamariya-Atari-Parasia (5), Silghat(Si)-Atari-Chhui(Cu)(12),Kharsaru-Gorakhpur- Lakhnadon(17) and Sagar-Atari-Lungsa(19)

352620 40.3

Low Low Low-medium

Parasia-Masanbarra (Ma)-Khamariya(18), Khawasa-Sukla-Tarali(27)

78110 8.9

Low

Low Medium-High

Atari-Parasia-Bhimgarh (4),Pipariya-Sagar-Jamunpani (8), Atari(At)-Lungsa-Kharsaru(11), Dhenka-Paddikona-Kharsaru(13), Sagar-Bhimgarh (Bg)-Dhenka (Dk)(14), Kharsaru-Jamunpani (Jp)-Chunamati (Ch)-Parasia (15), Bhimgarh-Khamariya-Atari (16)

110708 12.6

Low Low-Medium

Low-Medium

Lakhnadon-Pipariya-Sagar (7), Khawasa-Lungsa (Lu)-Lakhnadon(Lk) (29), Dhora-Sukla-Prattappur (30)

90160 10.3

Low Low-High Medium-High

Gorakhpur (GO)-Sagar-Paddikona (9), Sukla-Jamuntola-Rukhad (25)

67506 7.7

Low-Medium

Low-Medium

Low-High Prattappur (Pt)-Gondatola-Khawasa-Rukhad (24) 13303 1.5

Low-Medium

Low Low-High Nadora (Nd)-Sagar (Sa)—Dhora (Dh)(6), Kodajhiri (Ko)- Khawasa (Kw)-Sukla (Sk) (21), Dhenka-Sukla-Khawasa-Nadora (22), Tarali (Ta)-Kodajhiri-Jamuntola (Jm)(28)

83772 9.6

Low Medium Medium Jamuntola (Jm)-Gondatola (Gl)-Kharsaru (Kh)-Rukhad (Rk)(23),Kanera (Kn)-Bisapur (Bs)-Jamuntola (26)

28674 3.3

Low Low-High Low-High Arandiya (Ar)-Kharsaru (Kh)-Bhimgarh-Nadora (10) 345 0.04 * Available N (kg/ha) : Low = < 275; Medium= 275-550; High= > 550. Available P2O5 (kg/ha) : Low = < 34; Medium= 34-61; High= > 61 . Available K2O (kg/ha) : Low = < 137; Medium= 137-275; High= > 275. (Sehgal 1986)

50 LAND USE SUITABILITY ASSESSMENT

low available nitrogen (< 275 kg ha-1), low phosphorus (< 34 kg ha-1) and medium available potassium (138-275 kg ha-1), whereas, soils in southern lowlands have low nitrogen, low or high (> 61 kg ha-1) phosphorus and medium to high (> 275 kg ha-1) available potassium contents. The soils in upper Wainganga valley have low nitrogen, phosphorus and medium to high available potassium contents (Sehgal 1986).

Land use alternatives

Land capability classes were generally used for land use assessment, determine erodible areas and to review land use potentials. The land capability analysis showed that district has 44% non-arable and 56% (TGA) arable land, respectively. The non-arable lands were identified as having steep slopes, very shallow and strongly stony soils that

Fig. 6. NPK status of soil.

BOBADE et al. 51

make cultivation impossible. The non-arable portion concentrated in upper ridges of Lakhnadon plateau (45%) was evaluated for forestry and wildlife conservation as per the criteria of land capability classification (Klingebiel & Montgomery 1961). Thirty-eight percent of land was suitable for silvipasture and remaining 7% of TGA was suitable for wildlife conservation. The spatial distribution and details of 11 land use units are depicted in Fig. 7 and Table 3.

About 41% of the TGA was covered by the class III,

arable classes with erosion and depth limitations, which make this land moderately cultivable that requires careful selection of crops adapted to soil depth, slope and stoniness. About 15% (TGA) of the area was covered by the class IV soils, which are fairly suitable for occasional or limited cultivation. The soil-site suitability analysis of the arable land has indicated that 12% of TGA was suitable for rice - wheat cropping system, 24% for sorghum-soybean, 15.3% for sorghum-cotton and 24% of TGA was suitable for citrus. The soil-site

Fig. 7. Proposed land use plan.

52 LAND USE SUITABILITY ASSESSMENT

Table 3. Land use plan based on soil-site suitability and land capability.

Soil Mapping Units Land Suitablity Area (ha) % Sk-Jm-Rk(25), Kw-Sk-Ta(27), Ta-Ko-Jm(28) Soybean-Sorghum-Cotton-Maize-

Vegetables 129347 4.8

Sa-Pd-Ky-Pc(3) Rice-Wheat-Soybean-Sunflower-Sorghum 93841 10.7 Go-Sa-Pd(9), Bg-Ky-At(16), Sa-At-Lu(19) Rice-Wheat-Soybean-Citrus-Maize-

Sunflower 10090 1.2

Dk-Pd-Kh(13), Kh-Jp-Ch-Pc(15), Kh-Go-Lk(17) Sorghum-Cotton 83953 9.6 At-Pc-Bg(4), At-Lu-Kh(11), Kw-Lu-Lk(29) Sorghum-Cotton-Citrus-Maize 79885 9.1 Na-Sa-Dh(6), Pr-Sa-Jb(8), Si-At-Cu(12), Jm-Gl-Kh-Rk(23)

Wheat-Soybean-Sorghum-Cotton-Citrus-Maize

38013 4.3

Sa-Bg-Dh(14) Soybean-Sorghum 13213 1.5 Ar-Kh-Bg-Nd(10), Ko-Kw-Sk(21), Pt-Gl-Kw-Rk(24)

Soybean-Sorghum-Cotton-Citrus-Maize 39447 4.5

Pc-Pd-Ky(1), Pc-Pr-Ky(2), Ky-At-Pc-Roc(5), Kn-Bs-Jm-Roc(26)

Silvipasture 234961 26.8

Lk-Pr-Sa-Lu(7), Pc-Ma-Ky-Roc(18), Sk-Jm-Bs-(20) Fairly well-suited for silvipasture 98042 11.2

Dh-Sk-Kw-Nd(20), Dh-Sk-Pt(30) Suitable for wildlife conservation 59656 6.8 characteristics such as climate, slope, erosion, flooding, drainage, texture/structure, coarse fragments, depth, calcium carbonate/gypsum content, apparent cation exchange capacity, base saturation, sum of basic cations, pH, organic carbon content, and exchangeable sodium percentage, that were used in the land evaluation of different crops by Sys et al. (1991).

The agro-climate of Seoni is characterized by hot moist sub-humid with an annual rainfall of 1100 to 1500 mm and mean annual temperature of 24 to 25 °C. The length of growing period (LGP) is 180 to 210 days with three months of humid period (July-August-September) and had residual soil moisture that was used by crops until January (Velayutham et al. 1999). The suitability of soils to crops was evaluated and described. Moderately deep, moderately well drained, sandy loam to sandy clay loam textured, slightly acid with low available N and K soils are suitable for sorghum and moderately suitable for wheat, soybean and citrus. These soils are mostly concentrated in southern lowlands of the district with soil series of Arandiya (Ar), Bisapur (Bs), Chunamati (Ch), Dhenka (Dh) and Gondatola (Go), Jamunpani (Jm) Prattappur (Pr) and Khawasa (Kw).

Very shallow, clay textured, stony soils with root restricting hard layers, slightly acid and low NPK status were classified as non-arable lands

and occur mostly on escarpments and plateau tops in the district. The soil, of Dhora, Kanera, Lakhnadon, Parasia and Pipariya series have shallow, slightly acid to slightly alkaline, clayey surface texture and were evaluated as moderately suitable for soybean, citrus and maize. They are arable lands with severe limitations of steep slopes and stoniness. These soils (Gorakhpur, Khamariya and Kharsaru series) were mostly associated with moderately deep, well drained Masanbarra and Kodajhiri series which were not suitable for cultivation. The Nadora and Paddikona series occurring on valleys and inter-hill basins were moderately well drained, moderately deep, clay textured, high shrink-swell potentials and slightly alkaline in reaction. These soils were suitable for the cultivation of wheat, soybean, cotton and sorghum.

The current land use in the district is sub-optimal with a net sown area of 374,000 ha, wherein, food crops account for 84% of the total cropped area. The acreage under the principal food crops are rice (87,700 ha), wheat (86,700 ha), jowar (14,700 ha), maize (6,700 ha), kodon kutki (53,700 ha), Bengal gram (27,600 ha), black gram (21,900) and pigeon pea (6,200 ha). The productivity of these crops in kg/ha was 1,242 for rice, 449 for wheat, 623 for jowar, 984 for maize, 183 for kodon kutki, 596 for Bengal gram, 239 for black gram and 1,260 for pigeon pea (District Statistical

BOBADE et al. 53

Report 2003). These average productivities of crops were below the national average yield. Therefore, the plan was proposed, based on land resource data that minimizes the expansion of area on marginal lands under paddy and replacing the areas cultivated for kodon kutki (a non-remunerative food crop) by diversified crops like soybean, cotton, wheat and maize. There is a vast scope to replace the area cultivated for sun hemp (31,000 ha), sesamum (8,200 ha) and kodon kutki (53,700 ha) in the district (Guru 1989).

Conclusions

The land resource data, that have been generated, could be integrated through GIS techniques for efficient crop planning at district level. The land units that were under citrus and soybean have been identified as a potential area for crop diversification in the Seoni district. The fertility capability classification (FCC) units and available NPK status zones that were delineated could be used for linking crop response studies with integrated nutrient management for various cropping systems in the district for land evaluation programmes.

Acknowledgements

The authors express their gratitude to Dr. S.P.S. Kushwaha, Head, Forestry and Ecology Division, IIRS, Dehradun and Dr. Skip J. Van Bloem, Department of Agro-Environmental Scien-ces, University of Puerto Rico, Mayagüez, USA, for critical reviews and for many useful suggestions. Authors thank Mrs. Ujwala Tijare, NBSS & LUP, Nagpur, for map data processing in GIS.

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