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Tree Structural Diversity and Yield Prediction Models for Tree Species in Old Oyo National Park, Nigeria
Adesoji Akinwumi Adeyemi,
Hussainat Taiwo Taofeek
Issue:
Volume 5, Issue 2, June 2020
Pages:
11-20
Received:
14 April 2020
Accepted:
30 April 2020
Published:
9 June 2020
Abstract: Evaluation of structural and species distribution is essential for conservation work. Besides, reliable baseline information is crucial for a sustainable forest management. We assessed forest structure and formulated yield-prediction models for tree species in Old Oyo National Park (OONP). Systematic sampling technique was adopted for the study. Thirty transects of 1000 m-long were laid at 1 km intervals. Four 0.25ha-plots were then alternately laid at 250 m intervals along each transect, and 120 plots were used for the study. Structural parameters including diameters at the base, breast height, middle, merchantable top and tree heights were measured for trees with Dbh ≥10 cm to compute stand density and volume. Data were analysed using descriptive statistics and regression. Species diversity and richness indices were computed using Shannon-Wiener and Margalef’s Indices. Models were assessed using R2 and standard error of estimate (SEE), overall significance of each model was evaluated using F-test. Model validation was done using t-test and bias. Sixty-four tree species in 23 families were encountered with richness and diversity indices of 1.189 and 3.544, respectively. Only one endangered (Pterocarpus erinaceus) and three vulnerable (Afzelia africana, Vitellaria paradoxa and Maranthes agnesis) species were encountered. Burkea africana was the most locally-abundant in the area with a relative density and basal area of 9.3 and 3.058 m2/ha, respectively. Fabaceae was the most-represented family. The best yield-prediction model was of the form: V=27.53 + -21.41logDB + 0.023THT² having R2, SEE and bias values of 90.5%, 0.599 and 0.005, respectively. It is recommended for future predictions.
Abstract: Evaluation of structural and species distribution is essential for conservation work. Besides, reliable baseline information is crucial for a sustainable forest management. We assessed forest structure and formulated yield-prediction models for tree species in Old Oyo National Park (OONP). Systematic sampling technique was adopted for the study. Th...
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On Farm Demonstration of Management of Fusarium Wilt Disease of Chickpea Under Rainfed Conditions in Mid Hill Region of Jammu, Jammu & Kashimir, U.T., India
Shahid Ahamad,
Jag Paul Sharma,
Bimal Singh Jamwal
Issue:
Volume 5, Issue 2, June 2020
Pages:
21-24
Received:
30 September 2019
Accepted:
25 October 2019
Published:
20 June 2020
Abstract: Chickpea is one of the most vulnerable crop to attack of pests and diseases causing huge production losses. Among the diseases, chickpea wilt poses a severe problem in rainfed areas of Jammu region. It was observed that chickpea seeds treated with Trichoderma viride (soil application) recorded 21.50% wilt incidence followed by Trichoderma viride (seed application) 35.25%, neem seed cake 47.00%, Carbendazim 48.90%, Thiram 50.14% and Captan 56.50%. While Trichoderma viride (soil application) gave 78.50% (highest) wilt disease control, followed by Trichoderma viride (seed application) 64.75%, neem seed cake 53.00%, Carbendazim 51.10%, Thiram 49.86%, Captan 43.50% and least in check. Recommendations of the results were repeated in the 4 farmers field in Reasi district, disease incidence were 25.40% but after applying of Trichoderma viride (soil application) diseases incidence reduced to 7.95% only and it was reduced to 6.75% (Table 2). While yield of chick pea was enhanced from 5.25 to 9.20 q/ha and maximum 9.80 q/ha against least farmers’ practices i.e. 5.25% only.
Abstract: Chickpea is one of the most vulnerable crop to attack of pests and diseases causing huge production losses. Among the diseases, chickpea wilt poses a severe problem in rainfed areas of Jammu region. It was observed that chickpea seeds treated with Trichoderma viride (soil application) recorded 21.50% wilt incidence followed by Trichoderma viride (s...
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Physiochemical Responses and Cold Survival Mechanism of Rice Seedlings of Selected Cultivars in Northwest Bangladesh
Bikash Chandra Sarker,
Sumaiya Aktar,
Prodip Kumar Roy
Issue:
Volume 5, Issue 2, June 2020
Pages:
25-29
Received:
6 April 2020
Accepted:
29 April 2020
Published:
4 July 2020
Abstract: Cold stress at seedling stage is a serious concern to the sustainable rice production in some regions of the world. A field experiment was carried out to investigate the physiological parameters of seedlings of selected five rice cultivars, namely Binadhan-6, BR-26, BRRI dhan28, BRRI dhan29, and BRRI dhan50 (Banglamoti) for cold survival mechanism during low temperature in the Northwest Bangladesh. The field experiment was arranged following Randomized Complete Block Design (RCBD) with three replications. The physiological parameters such as leaf proline, chlorophyll, total carotenoid content, relative water content (RWC) and starch were determined. In this study, the rice cultivars showed significant variation of physiological activities at low temperature. BRRI dhan28 synthesized the highest amount of proline (1.25 mg g-1), chlorophyll-a (2.63 mg g-1), chlorophyll-b (0.85 mg g-1), relative water content (93.33%) and starch (28.21%) content. Significant variability was observed among the cultivars during the experiment time for their survivability. The sequence of survival potentiality was observed as BRRI dhan28> BRRI dhan29> BR-26> BINA dhan-6> BRRI dhan50. The present finding infers that BRRI dhan28 showed the best survival potentiality based on the synthesis of proline, chlorophyll and other physiological parameters.
Abstract: Cold stress at seedling stage is a serious concern to the sustainable rice production in some regions of the world. A field experiment was carried out to investigate the physiological parameters of seedlings of selected five rice cultivars, namely Binadhan-6, BR-26, BRRI dhan28, BRRI dhan29, and BRRI dhan50 (Banglamoti) for cold survival mechanism ...
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