This study was conducted to assess variability among linear body measurements (LBMs), deduce components that describe these traits, and investigate the inter-relationship among them. For this purpose, seventeen LBM traits namely heart girth, body-length, wither-height, ear-length, forelimb-length, hindlimb-length, barrel-girth, face-length, hip-width, chest-width, chest-depth, tail-length, neck-length, hump-length, hump-circumference, forehoof-circumference and hindhoof-circumference were measured on 300 (51 males and 249 females) camels. PC factor analysis was used to describe the variation in LBM traits where extracted factors were varimax rotated to enhance interpretability. Pearson’s correlation coefficients among the traits were positive and very highly significant. From the factor analysis, two principal components (PCs) were extracted, which accounted for 63.2% of the total variance. PC1 accounted for 57.0% of the total observed variance and was loaded by EL, BL, FL, HL, FLL, WH, CD, NL, and HC; while PC2 contributed 6.1% of the total observed variance and had its loading on HG, BG, and HW. The results obtained from this study could be useful in designing appropriate husbandry, selection, and breeding programs for utilization of camel genetic resources.

Land use could impact soil properties and processes in varying degrees. Therefore, the impact of different land use systems on soil water status and its relationship with some physiochemical properties was studied at the Teaching and Research Farm, Ekiti State University, Ado Ekiti, Nigeria. The land use types included native forest (NF); Paddock (P); Oil palm plantation (OP); Teak (TK); new yam plot (NY) and yam plot under fallow (YF). Structure and disturbed surface soils (0 - 15 cm) samples were taken at three (3) locations in each land use type. Soil water content (SWC) significantly varied among the different land use types, with oil palm plantation storing the highest amount of water. The results also showed significant differences in soil bulk density, organic carbon, porosity, texture and hydraulic conductivity among the land use types. SWC associated positively and significantly with organic matter, silt content and silt + clay. The association between SWC and pH and silt/clay were positive but weak while particle density, bulk density and sand content showed negative and significant association. The principal component regression (PCR) showed a highly significant, positive relationship between SWC and the principal components of other physicochemical properties. Cluster analysis showed that SWC is highly related and linked to OM, Bd, Pd, Pt and silt/clay. The results implied that conversion to paddock and continuous cultivation led to depletion in soil water, physical and chemical properties, whereas cultivation of tree crops conserved these soil properties better. Therefore, establishment of tree crop and conservative soil management practices are suggested to prevent agricultural lands from degradation in areas with soils under similar conditions.

Land use could impact soil properties and processes in varying degrees. Therefore, the impact of different land use systems on soil water status and its relationship with some physiochemical properties was studied at the Teaching and Research Farm, Ekiti State University, Ado Ekiti, Nigeria. The land use types included native forest (NF); Paddock (P); Oil palm plantation (OP); Teak (TK); new yam plot (NY) and yam plot under fallow (YF). Structure and disturbed surface soils (0 - 15 cm) samples were taken at three (3) locations in each land use type. Soil water content (SWC) significantly varied among the different land use types, with oil palm plantation storing the highest amount of water. The results also showed significant differences in soil bulk density, organic carbon, porosity, texture and hydraulic conductivity among the land use types. SWC associated positively and significantly with organic matter, silt content and silt + clay. The association between SWC and pH and silt/clay were positive but weak while particle density, bulk density and sand content showed negative and significant association. The principal component regression (PCR) showed a highly significant, positive relationship between SWC and the principal components of other physicochemical properties. Cluster analysis showed that SWC is highly related and linked to OM, Bd, Pd, Pt and silt/clay. The results implied that conversion to paddock and continuous cultivation led to depletion in soil water, physical and chemical properties, whereas cultivation of tree crops conserved these soil properties better. Therefore, establishment of tree crop and conservative soil management practices are suggested to prevent agricultural lands from degradation in areas with soils under similar conditions.

Thirty five genotypes of coriander (Coriandrum sativum L.) were tested in four artificially created environments to judge their stability in performance of seed yield. The differences among genotypes and environments were significant for seed yield. Stability parameters varied considerably among the tested genotypes in all the methods used. The variation in result in different methods was due to non-fulfillment of assumption of different models. However, AMMI analysis provides the information on main effects as well as interaction effects and depiction of PCA score gives better understanding of the pattern of genotype – environment interaction. The sum of squares due to PCAs was also used for the computation of AMMI stability values for better understanding of the adaptability behavior of genotypes hence, additive main effects and multiplicative interaction (AMMI) model was most appropriate for the analysis of G x E interactions for seed yield in coriander. Genotypes RVC 15, RVC 19, RVC 22, RVC 25 and Panipat local showed wider adaptability while, Simpo S 33 exhibited specific adaptability to favourable conditions of high fertility. These genotypes could be utilized in breeding programmers to transfer the adaptability genes into high yielding genetic back ground of coriander.

Twenty five land races from Madhya Pradesh and ten germplasm of coriander were evaluated in four environments to assess umbel per plant using multivariate analysis. Mean sum of squares due to genotypes, environments and GEI were highly significant for umbels per plant. Variation in GEI was mainly due to heterogeneity. ). PCA 1 and PCA 2 captures the 99.42% of interaction sum of squares hence, these two principal component axes were the best predictive. The potential environment the potential environments E3 (high fertility, 2009-10) bearing lowest interaction effect while, least potential environments E2 (low fertility, 2008-09) exhibited high PCA scores. The biplot of genotype, environment and IPCA 1 showed three groups. One group exhibited the similar main effects (mean umbels per plant) to the grand mean. The second group showed high interaction effect varied in direction while third group bear the low interaction effect. AMMI Stability Values (ASV), ranging from from 7.444 to 31.099 was lowest in RVC 8 followed by RVC 4, RVC 11, RVC 21, RVC 9 and RVC 3 whereas, it was noted maximum in RVC 19 followed by Moroccan, CS 193, Simpo S 33 and G 5363. The genotypes exhibiting low IPCA scores and ASV namely, RVC 8, RVC 4, RVC 11, RVC 21, RVC 19 and RVC 25 showed wider adaptability for umbels per plant while, RVC 19, Moroccan, CS 193, Simpo S 33 and G 5363 exhibiting specific adaptability towards environmental conditions. These genotypes can be utilized in breeding programmes to transfer the adaptability genes for umbel per plant into high yielding genetic back ground in coriander.

Thirty five genotypes of coriander (Coriandrum sativum L.) were tested in four artificially created environments to judge their stability in performance of seed yield. The differences among genotypes and environments were significant for seed yield. Stability parameters varied considerably among the tested genotypes in all the methods used. The variation in result in different methods was due to non-fulfillment of assumption of different models. However, AMMI analysis provides the information on main effects as well as interaction effects and depiction of PCA score gives better understanding of the pattern of genotype – environment interaction. The sum of squares due to PCAs was also used for the computation of AMMI stability values for better understanding of the adaptability behavior of genotypes hence, additive main effects and multiplicative interaction (AMMI) model was most appropriate for the analysis of G x E interactions for seed yield in coriander. Genotypes RVC 15, RVC 19, RVC 22, RVC 25 and Panipat local showed wider adaptability while, Simpo S 33 exhibited specific adaptability to favourable conditions of high fertility. These genotypes could be utilized in breeding programmers to transfer the adaptability genes into high yielding genetic back ground of coriander.

Twenty five land races from Madhya Pradesh and ten germplasm of coriander were evaluated in four environments to assess umbel per plant using multivariate analysis. Mean sum of squares due to genotypes, environments and GEI were highly significant for umbels per plant. Variation in GEI was mainly due to heterogeneity. ). PCA 1 and PCA 2 captures the 99.42% of interaction sum of squares hence, these two principal component axes were the best predictive. The potential environment the potential environments E3 (high fertility, 2009-10) bearing lowest interaction effect while, least potential environments E2 (low fertility, 2008-09) exhibited high PCA scores. The biplot of genotype, environment and IPCA 1 showed three groups. One group exhibited the similar main effects (mean umbels per plant) to the grand mean. The second group showed high interaction effect varied in direction while third group bear the low interaction effect. AMMI Stability Values (ASV), ranging from from 7.444 to 31.099 was lowest in RVC 8 followed by RVC 4, RVC 11, RVC 21, RVC 9 and RVC 3 whereas, it was noted maximum in RVC 19 followed by Moroccan, CS 193, Simpo S 33 and G 5363. The genotypes exhibiting low IPCA scores and ASV namely, RVC 8, RVC 4, RVC 11, RVC 21, RVC 19 and RVC 25 showed wider adaptability for umbels per plant while, RVC 19, Moroccan, CS 193, Simpo S 33 and G 5363 exhibiting specific adaptability towards environmental conditions. These genotypes can be utilized in breeding programmes to transfer the adaptability genes for umbel per plant into high yielding genetic back ground in coriander.