Study of land suitability for rubber and cashew in the derived savanna zone of Edo State, Nigeria

This study attempted to assess the soil suitability in the derived savanna zone of Edo State, Nigeria for the cultivation of some tree crops. The research specifically aimed to evaluate soil suitability for cashew and rubber supported by suitability maps for both crops. In terms of land suitability evaluation, mapping units 1 and 2, with an area coverage of 27.4 ha of the entire research area (100 ha) were found to be marginally suitable (S3) for rubber cultivation but moderately suitable (S2) for cashew. Mapping unit 3, with area coverage of 38 ha was found to be currently not suitable (N1) for rubber but marginally suitable (S3) for cashew cultivation. Mapping unit 4 representing area coverage of 34.7 ha was found to be permanently not suitable (N2) for rubber cultivation but marginally suitable (S3) for cashew. Thus, technically, rubber can only be cultivated in that land at marginal level with an expected productivity of 27.4 ha (27.4 %). Cashew can be cultivated at moderate and marginal levels with an expected yield of 27.4 ha (27.4 %) and 72.6 ha (72.6 %), respectively, of the total land area. Thus, the preferred crop for the studied is cashew. It is recommended that for any significant investment in cultivation of this crop, the priority is the moderate levels with an expected productivity of 27.4 ha or 27.4 % of total land area.

Optimized Land Use through Integrated Land Suitability and GIS Approach in West El-Minia Governorate, Upper Egypt

Land evaluation is imperative for its efficient use in agriculture. Therefore, this study aimed at assessing the suitability of a region in West El-Minia for cultivating some of the major crops using the geographical information system (GIS). The results focus on allocating space for cultivating sugar beet and utilizing the free period of sugar beet in other crops. This exploitation helps to maintain the quality of the land and increase its fertility by using crop rotation with integrated agricultural management. A machine learning technique was implemented using the random forest algorithm (RF) to predict soil suitability classes for sugar beet using geomorphology, terrain attribute and remote sensing data. Fifteen major crops were evaluated using a suitability multicriteria approach in GIS environment for crop rotation decisions. Soil parameters were determined (soil depth, pH, texture, CaCO3, drainage, ECe, and slope) to characterize the land units for soil suitability. Soils of the area were found to be Entisols; Typic Torrifluvents, Typic Torripsamments and Typic Torriorthents and Aridsols; Typic Haplocacids, Calcic Haplosalids and Sodic Haplocalcids. Overall, the studied area was classified into four suitability classes: high “S1”, moderate “S2”, marginal “S3”, and not suitable “N”. The area of each suitability class changed depending on the crop tested. The highest two crops that occupied S1 class were barley with 471.5 ha (representing 6.8% of the total study area) and alfalfa with 157.4 ha (2.3%). In addition, barley, sugar beet, and sorghum occupied the highest areas in S2 class with 6415.3 ha (92.5%), 6111.3 ha (88.11%) and 6111.3 ha (88.1%), respectively. Regarding the S3 class, three different crops (sesame, green pepper, and maize) were the most highly represented by 6151.8 ha (88.7%), 6126.3 ha (88.3%), and 6116.7 ha (88.2%), respectively. In the end, potato and beans occupied the highest areas in N class with 6916.9 ha (99.7%) and 6853.5 ha (98.8%), respectively. The results revealed that the integration of GIS and soil suitability system consists of an appropriate approach for the evaluation of suitable crop rotations for optimized land use planning and to prevent soil degradation. The study recommends using crop rotation, as it contributes to soil sustainability and the control of plant pests and diseases, where the succession of agricultural crops on a scientific basis aims at maintaining the balance of nutrients and fertilizers in the soil.

​Soil Suitability for Growing Pulses in Northern Dry Zone of Karnataka

Background: A soil suitability evaluation of Kanamadi South sub-watershed in the Northern Dry Zone of India was carried out during April 2019 to define the soil fitness for the production of pigeonpea, chickpea, greengram and cowpea the four major pulses that are widely grown in the area. Methods: A detailed soil survey of Kanamadi South sub-watershed was carried out using IRS P6 LISS-IV image and Vijayapura district toposheet. The soils of Kanamadi south sub watershed were grouped into 19 mapping units based on studied 50 profiles. The studied physical and chemical properties were evaluated using the FAO (1976) framework for land evaluation was followed in the evaluation of soil-site suitability for major crops grown in Kanamadi South sub-watershed. This classification recognized two orders of land suitability, order ‘S’ (suitable) and order ‘N’ (not suitable) which are further subdivided into land suitability classes. Result: The studied 19 mapping units were moderately (S2) to marginally suitable (S3) for pigeonpea and greengram having marginal to severe limitations of rainfall and soil physico-chemical properties and none to slight limitation of land form characteristics. The mapping units were moderately suitable (S2) to marginally suitable (S3) for chickpea and cowpea having moderate to severe limitation of temperature, rainfall, depth and pH and none to slight limitation of land form characteristics. The suitability of the study area for all the pulses were said to be moderately suitable (S2) for growing pulse crop for improving productivity and improving biological nitrogen fixation.

Delineation of Cumin (Cuminum Cyminum L.) Production Zone Beyond Boundaries in India Based on Climate Analogues, Soil Suitability and Rainfall Analysis

Here, we attempted to identify ideal ecological niche for cumin cultivation in India in the future climate scenario by adopting an integrated approach of climate analogues and soil suitability. This will help policy makers for area expansion to generate more revenue as cumin has huge export potential. Climate analogues tool, a web-based tool developed by the Research Programme on climate change, agriculture and food security (CCAFS) helps to identify, connect and map sites with statistically similar climates across space and time. Efficient cumin production zones in India were identified based on relative spread index and relative yield index which were used as the input/reference site for finding the analogues sites. Rainfall and temperature were the main climatic variables used in the study under SRES A1B emission scenario. The results showed a total of 453 analogues sites (districts) identified by 14 reference sites used in the study. The analogues sites identified by the tool were further corroborated with the soil suitability of the location and refined analogues sites which included soil suitability for cumin cultivation (337 analogues sites out of 453) were identified. Rainfall trend analysis from the rainfall data of past 110 years indicated that analogues sites are showing the rainfall trend suited for cumin cultivation. This is the first report on the use of climate analogues tool to identify analogues sites with soil suitability and rainfall trend analysis of the identified analogues sites.

Winter Wheat Cultivar Recommendation Based on Expected Environment Productivity

We used 5 years of data from multi-environmental trials conducted in Poland to assess average winter wheat yield based on selected environmental factors to recommend cultivars depending on their performance in environments of different productivity. Average expected yields in particular environments were calculated using a model based on analysis of covariance (ANCOVA), which describes the relationship between winter wheat yield and environmental factors of soil suitability and pH, drought length and Selyaninov’s Hydrothermal Coefficient (HTC) in 10-day periods. The cultivar performance was evaluated using linear regression. The cultivar yield estimated by the mixed model was considered the dependent variable, whereas the environmental mean yields, estimated by ANCOVA, were considered independent variables. The cultivars were ranked according to the estimated yield in environments of determined average wheat productivity. Higher yielding cultivars were divided into two groups: widely and narrowly adapted cultivars, which were then recommended. The novelty of this study stems from the consideration of the environmental productivity in the recommendation process, the indication of widely adapted cultivars to be grown in a broad range of productivity sites and the selection of cultivars with narrow adaptation, which may outperform cultivars of wide adaptation in homogeneous fields. This study confirmed the importance of soil suitability and HTC for winter wheat yield. Direct application of our results is possible in Poland and in other countries with similar conditions.

Soil Water Erosion Vulnerability and Suitability under Different Irrigation Systems Using Parametric Approach and GIS, Ismailia, Egypt

Preserving the sustainable agriculture concept requires identifying the plant response to the water regime and rationing the water for irrigation. This research compares different irrigation designs coupled with a parametric evaluation system on soil water erosion and soil suitability to assess the sites vulnerable to soil erosion based on a soil water erosion model (ImpelERO) in an area of 150.0 hectares, Ismailia Governorate, Egypt. Land suitability maps are prepared using the Geographic Information System (GIS), and the soil properties are analyzed and evaluated for the different surface, sprinkler, and drip irrigation methods. The results show that the sprinkler and drip irrigation strategies are more practical irrigation methods and additional environment friendly than surface irrigation for enhancing land productivity. Moreover, the principle acumen for creating use of the surface irrigation on this space is for lowering the soil salinity. Land capability index for surface irrigation ranges from 20.5 to 72.2% (permanently not suitable N2 to moderately suitable S2); and the max capability index (Ci) for drip irrigation was 81.3% (highly suitable-S1), while the mean capability index (Ci) was 42.87% (Currently not suitable-NI). The land suitability of the study area using sprinkler irrigation was ranked as highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and currently not suitable (N1). Thus, the obtained data indicated that applying drip irrigation (trickle irrigation) was the most efficient system compared to the sprinkle and surface irrigation systems. To identify the soil, water erosion vulnerability, and soil optimal management strategies for the agricultural parcel in that region, the ImpelERO model (soil erosion vulnerability/impact/management) was applied. Erosion risk classes ranged from V2 (small) to V3 (moderate), that that region categorized as small-sensitive to water erosion by alfalfa, to moderate-sensitive to water erosion by olive. The results of soil losses varied from 7.1 to 37.9 t ha−1 yr−1 with an average of 17.7 t ha−1 yr−1. Thus, guarantee efficient water use and soil suitability for food production in the future will require the use of an efficient irrigation system.