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End date: 2024 × Start date: 2020 × DDC: 570 × search.filters.applied.f.series: Agriculture 10 (2020), Nr. 4 ×

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    Using SPOT-7 for Nitrogen Fertilizer Management in Oil Palm
    (Basel : MDPI AG, 2020) Yadegari, Mohammad; Shamshiri, Redmond R.; Shariff, Abdul Rashid Mohamed; Balasundram, Siva K.; Mahns, Benjamin
    Environmental concerns are growing about excessive applying nitrogen (N) fertilizers, especially in oil palm. Some conventional methods which are used to assess the amount of nutrient in oil palm are time-consuming, expensive, and involve frond destruction. Remote sensing as a non-destructive, affordable, and efficient method is widely used to detect the concentration of chlorophyll (Chl) from canopy plants using several vegetation indices (VIs) because there is an influential relation between the concentration of N in the leaves and canopy Chl content. The objectives of this research are to (i) evaluate and compare the performance of various vegetation indices (VIs) for measuring N status in oil palm canopy using SPOT-7 imagery (AIRBUS Defence & Space, Ottobrunn, Germany) to (ii) develop a regression formula that can predict the N content using satellite data to (iii) assess the regression formula performance on testing datasets by testing the coefficient of determination between the predicted and measured N contents. SPOT-7 was acquired in a 6-ha oil palm planted area in Pahang, Malaysia. To predict N content, 28 VIs based on the spectral range of SPOT-7 satellite images were evaluated. Several regression models were applied to determine the highest coefficient of determination between VIs and actual N content from leaf sampling. The modified soil-adjusted vegetation index (MSAVI) generated the highest coefficient of determination (R2 = 0.93). MTVI1 and triangular VI had the highest second and third coefficient of determination with N content (R2 = 0.926 and 0.923, respectively). The classification accuracy assessment of the developed model was evaluated using several statistical parameters such as the independent t-test, and p-value. The accuracy assessment of the developed model was more than 77%.
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    Influence of Tree Species, Harvesting Method and Storage on Energy Demand and Wood Chip Quality When Chipping Poplar, Willow and Black Locust
    (Basel : MDPI AG, 2020) Pecenka, Ralf; Lenz, Hannes; Jekayinfa, Simeon Olatayo; Hoffmann, Thomas
    The cultivation of fast-growing wood (e.g., poplar, willow or black locust) in short rotation coppices and agroforestry systems presents an opportunity for producing biomass sustainably in the agricultural sector. Cost-efficient agricultural wood production requires the availability of high-performance machinery and methods with which high-quality wood chips can be produced at low cost. It is known from harvesting short rotation coppices in practice that both the wood chip quality and the performance of the harvesting machinery depend on a variety of factors (e.g., harvesting method, weather conditions, tree species). That is why this study examines in detail the influence of the tree species (different varieties of poplar, willow, black locust) and the wood condition (fresh, stored or dried, frozen) on the specific energy demand for comminution in a stationary drum chipper and on the particle size distribution of the wood chips produced. For all the tree species examined, the chipping of dried as well as frozen stems was connected with a significant increase in the specific energy demand for comminution. An increase of 31% has been measured if poplar stems are chipped in frozen conditions (max. 6.31 kWh t−1). Drying led to an increase of 59% for dried willow stems (max. 6.67 kWh t−1). Drying and frost had also an influence on the size and quality of the wood chips, but no globally significant connection could be established for the examined tree varieties.