Browsing by Author "Raja, Azeem"
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ThesisItem Open Access Phenological studies and Forage quality assessment of selected Herbaceous species at Benhama, Kashmir(SKUAST-K, 2017) Raja, Azeem; Geelani, S.N. ZaffarThe present study entitled “Phenological Studies and Forage Quality Assessment of Selected Herbaceous Species at Benhama, Kashmir” was carried out at Faculty of Forestry, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Benhama, Ganderbal, Jammu and Kashmir, during the year 2016-2017. The study was done to determine the phenophases of herbaceous species present at the study site along with their Nutrient analysis. Nine species i.e., Capsella bursapastoris, Convolvulus arvensis, Cynodon dactylon, Lolium perenne, Oxalis corniculata, Plantago lanceolata, Poa annua, Trifolium repens, and Trifolium pratense were selected and analysed. All the species were found to be present in 3 seasons i.e., Spring, Summer and Autumn while as only 6 species were reported in Winter season. Also, the species were distributed along all the three altitudes i.e., lower, middle and upper altitude and the delay in phenology was seen as we moved from lower to upper altitude. Vegetative phase of most of the species peaked in April of Spring season. Whereas, flowering phase of most of the species was at its peak from May-June i.e., Spring to Summer season. Seeding phase from July-August i.e., Summer to Autumn season. The effect of growth phases on the nutritional parameters of the herbaceous species was found to be significant (P≤ 0.05) i.e., the overall dry matter content, crude fibre content, total organic matter content and total carbohydrates content increased while as crude protein content, ether extract content, total ash content, acid insoluble ash content and nitrogen free-extract content decreased as the plant matures. Similiarly, the effect of species was also found to be significant on the nutritional parameters for all growth phases. Overall values of Dry matter content, Crude protein content, Ether extract content, Crude fibre content, Total ash content, Acid insoluble ash content, Nitrogen free-extract content, Total organic matter content and Total carbohydrates was significantly maximum (P≤0.05) in Capsella bursapastoris (39.99%), Trifolium pratense (20.55%), Capsella bursapastoris (2.22%), Lolium perenne (31.00%), Capsella bursapastoris (11.72%), Poa annua (2.39%), Convolvulus arvensis (56.10%), Trifolium pratense (91.45%), and Lolium perenne (75.61%) respectively; while as minimum values for the same was found to be present in Oxalis corniculata (16.21%), Lolium perenne (12.21%), Cynodon dactylon (1.33%), Convolvulus arvensis (17.14%), Trifolium pratense (8.54%), Trifolium pratense (0.89%), Capsella bursapastoris (39.14%), Capsella bursapastoris (88.27%) and Trifolium repens (64.13%).ThesisItem Open Access Stand Characterization, Wood Production and Livelihood Contribution of Household Woodlots in Ganderbal District of Kashmir(SKUAST Kashmir, 2020) Raja, Azeem; M.A. IslamThe present study entitled “Stand Characterization, Wood Production and Livelihood Contribution of Household Woodlots in Ganderbal District of Kashmir” was carried out in the district Ganderbal, Jammu and Kashmir, during the year 2018-2021. The study investigated the land-use and land-holding pattern, woodlot types, stand characteristics, wood production, livelihood contribution and determinant socio-economic and biophysical factors affecting woodlot farming strategies. Multistage random sampling technique was employed to select 155 farm woodlots from 12 sample villages. Secondary sources were used to collect village level data on land-use and land-holding pattern. Primary data concerning the trees were collected through farm woodlot inventories, structured interview, non-participant observation and market assessment. The data were analyzed using simple descriptive statistics, multiple regression analysis, Gini co-efficient and Lorenz curve. Results revealed that four types of woodlots were established as monoculture woodlot plantations which included Populus deltoides, P. nigra, Salix alba, S. triandra and Robinia pseudoacacia or the polyculture plantations which included cultivation of mixed species of Morus alba, Ulmus villosa, Aesculus indica and Ailanthus altissima. The total area under woodlots in the sample villages were 27.35 ha and the average land allocation of woodlots was 0.155 ha per household. The proportion of woodlot of poplar was highest i.e. 15.12 ha (55.28%), followed by willow 7.31 ha (26.73%), Robinia 3.38 ha (12.36%) and mixed 1.54 ha (5.63%). The results indicated that the average no. of poplar trees was 98.10 having average tree diameter of 24.80 cm, average tree height of 18.10 m, mean basal area of 22.55 m2 and volume of 204.05 m3/ha in the sample woodlots. Similarly, the willow woodlots possessed average no. of trees 94.97 having average tree diameter of 23.30 cm, average tree height of 16.10 m, mean basal area of 23.82 m2 and volume of 101.75 m3/ha. The average no. of Robinia trees was 78.79 having average tree diameter of 19.23 cm, average tree height of 12.45 m, mean basal area of 17.59 m2/ha and volume of 109.50 m3/ha in the sample woodlots. The mixed woodlots had average no. trees 68.32 having average tree diameter of 15.50 cm, average tree height of 10.64 m, mean basal area of 11.71 m2/ha and volume of 62.32 m3/ha. The aspect, elevation and mean slope of woodlots found in the sample households of the locality was ranging from south-west to west, 1655 m to 1880 m and 2 to 8%. The average household production (p) and consumption (c) of woodlot resources were; Populus timber (p=7.44 m3/year, c=0.51 m3/year), Salix timber (p=2.0 m3/year, c=0.20 m3/year), wicker (p=0.006 t/year, c=0.00 t/year), Populus and Salix fuel wood (p=0.87 t/year, c=0.65 t/year), Robinia and other fuel wood (p=1.04 t/year, c=0.63 t/year), tree browse (p=0.76 t/year, c=0.76 t/year) and leaf litter (p=0.51 t/year, c=0.51 t/year). Thus, the total household extractions of the woodlot resources were recorded to be timber (1454.87 m3), fuel wood (141.65 t/year), tree browse (117.8 t/year), wicker (0.94 t/year) and leaf litter (79.05 t/year). The average household subsistence consumptions of the woodlot tree resources were found to be fuel wood (99.95 t/year), tree browse (117.8 t/year), timber (109.01 m3/year), wicker (0.00 t/year) and leaf litter (79.05 t/year). Household woodlot resources secured a total income of ` 4622194.00/year including both subsistence (`1492562.00/year) and cash income (` 3129632.00/year) @ ` 29820.60/household/annum. Of the total household woodlot income, Poplar woodlot contributed highest share (59.86%), followed Salix woodlot (24.29%), Robinia woodlot (9.80%) and mixed woodlot (6.05%). Among the resources, Populus timber contributed maximum share (72.13%) in woodlot cash income followed by Salix timber (15.58%), Populus and Salix fuel wood (4.85%), wicker (4.00%), Robinia and other fuel wood (3.50%), tree browse (0.00%) and leaf litter (0.00%). The structure of household total gross annual income consisted of all off-farm and on-farm sources among the surveyed population was ₹132283.58/hh/year which was differentiated as agriculture (27.2%), horticulture (20.79%), livestock (16.55%), woodlots (15.26%), business (9.20%), service (6.97%), wage earning (2.55%) and others (0.76%). Hence, woodlot resources are the 4th major constituent of household economy. In terms of employment, the composition of household average gross annual employment was 712 man-days which was made up of agriculture (22.57%), horticulture (19.90%), livestock rearing (12.48%), business (14.78%), others (11.51%), wage earning (9.81%), woodlots (5.89%) and service (3.06%). Thus, the woodlots constituted the 7th major constituent in terms of household employment. The Kruskal Wallis was indicated that the impact of income sources across quartile 1 (poorer) to quartile 4 (richer) on household livelihoods varied significantly. The values of chi-square test for the income sources at 5% level of significance was on-farm (χ2 = 16.41, p = 0.004), off-farm (χ2 = 81.51, p = 0.000) woodlots (χ2 = 15.74, p = 0.002) and total income (χ2 = 63.44, p = 0.000). The Gini co-efficients with woodlot income and without woodlot income across households was 0.4728 and 0.5341 respectively. The household survey indicated that most of the respondents were middle aged (50.97%), educated up to primary level (50.97%), having large family size (80.00%) with 2 working members as family labor (53.55%). The size of land holding among most of the respondents (55.48 %) were marginal, engaged mainly in farm occupation (46.45%), having herd size upto 5 livestock (77.42%), medium income (59.35%) and medium wealth status (59.35%). Majority of the respondents (70.32%) were having proximity upto 10 km to the forests who visited the forests frequently (36.12%) and access the forest plantation most often (54.84%). Out of the 15 household variables, eight attributes viz., education, family composition, size of land holding, social participation, livestock possession, family labor, wealth status and gross annual income was found to have a significant positive correlation with the woodlot associated land allocation while as main occupation, frequency of forest visits, proximity to the forests, forest resource possession, urban closeness and access to alternative forest resources was found to have significant negative correlation with the woodlot land allocation and on the contrary age was found to have non-significant association. The co-efficient of determination (R2) signified that all the explanatory variables altogether had contributed to 81.00% variation in livelihood induced woodlot land allocation. The F value (39.984) showed that all the fifteen variables contributed significantly in the variation of the household woodlot income. The social, economic and biophysical variables together explained 81.20% of the variation (F-value = 39.984, p = <0.0001) in the proportion of land allocation for woodlot farming. Of the three matrices, biophysical attributes explained the greatest amount (60.80%, p = <0.0001) of unique variation on woodlot land allocation followed by social (56.10%, p = <0.0001) and economic (50.80%, p = <0.0001) variables. The percentage of the variance in principal component analysis of the sixteen components making up socio-economic and biophysical variables was made and we realized that the first three components including woodlot land allocation contribute 88.331% of the variance of the principal component and the last thirteen components contribute only 11.669%. Eigen values were greater than 1 varying from 1.138 (factor III) to 11.158 (factor I). The individual percentages of the variances of the three components making up the woodlot land allocation strategy displayed the Factor I contributed maximum (69.735%) variance followed by Factor II (11.484%) and Factor III (7.112%) of the principal component. The loading of socio-economic and biophysical variables on PC I varied from -0.936 to 0.953 whereas the variables weights were -0.714 to 0.704 in PC II and -0.716 to 0.558 in PC III. The corresponding percentage variances of socio-economic and biophysical variables on PC I was from 2.13% to 8.14% whereas the percentage variances were 0.01% to 27.76% in PC II and 0.03% to 45.01% in PC III. All variables included in the PCA had positive factor scores, and therefore were associated with higher socioeconomic and biophysical status. Thus, the woodlot farming is the key alternative for forest resource production, livelihood resilience and socioeconomic improvement; hence, policy must be implicated towards the promotion of woodlot farming by re-orienting the land use through farmer’s motivation and technical, financial and farming input assistance.