Current Issue : October - December Volume : 2019 Issue Number : 4 Articles : 6 Articles
Before the introduction of positioning technologies in agriculture practices such as global\nnavigation satellite systems (GNSS), data collection and management were time-consuming and\nlabor-intensive tasks. Today, due to the introduction of advanced technologies, precise information\non the performance of agricultural machines, and smaller autonomous vehicles such as robot\nmowers, can be collected in a relatively short time. The aim of this work was to track the\nperformance of a robot mower in various turfgrass areas of an equal number of square meters but\nwith four different shapes by using real-time kinematic (RTK)-GNSS devices, and to easily extract\ndata by a custom built software capable of calculating the distance travelled by the robot mower,\nthe forward speed, the cutting area, and the number of intersections of the trajectories. These data\nwere then analyzed in order to provide useful functioning information for manufacturers,\nentrepreneurs, and practitioners. The path planning of the robot mower was random and the\nturfgrass area for each of the four shapes was 135 m2 without obstacles. The distance travelled by\nthe robot mower, the mean forward speed, and the intersections of the trajectories were affected by\nthe interaction between the time of cutting and the shape of the turfgrass. For all the different\nshapes, the whole turfgrass area was completely cut after two hours of mowing. The cutting\nefficiency decreased by increasing the time, as a consequence of the increase in overlaps. After 75\nminutes of cutting, the efficiency was about 35% in all the turfgrass areas shapes, thus indicating a\nhigh level of overlapping....
Low efficiency of conventional fertilizer (quick release fertilizer) application in agricultural sectors has caused environmental\npollution and health problems. A method to overcome the drawback of the conventional fertilizer is by controlled release fertilizer\n(CRF) preparation. CRF is expected to be able to fulfil the nutrient demand of targeted plants. The objective of this research is to\nprepare CRF by coating NPK fertilizer with multilayer chitosan-polyanion using alginate, pectin, and sodium tripolyphosphate\n(TPP). In addition, the effect of the layer arrangement modification of material on the rate of nitrogen release was also studied. The\nmechanical strength of coated fertilizer was analysed by compressive stress test and the properties of the fertilizer coating was\nobserved by scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The nitrogen release study\nshows that multilayer of chitosan-alginate (CA)5, chitosan-pectin (CP)5, and chitosan-TPP (CT)5 as coating material was able to\nincrease the compressive stress and decrease the nitrogen release of coated fertilizer. These results are supported by the FTIR\nanalysis which exhibits the formation of ionic interaction between amine group of chitosan and carboxyl group of alginate in\nchitosan-alginate (CA)5 layer, carboxyl group of pectin in chitosan-pectin (CP)5 layer, and phosphate of TPP in chitosan-TPP\n(CT)5 layer. On the other hand, the modification of the arrangement of chitosan-alginate layers showed that the fertilizer with the\nalternating layer arrangement (CA)5 was able to optimally increase the compressive strength. The mathematical model for the\nnitrogen release of coated fertilizer is also prepared and simulated with the MATLAB software. The simulation results showed that\nthe nitrogen release of coated fertilizer followed the proposed diffusion mechanism....
Crops are highly susceptible to drought in sloping land. Due to its good adaptability\nto complex terrain, sprinkler irrigation is one of the commonly used methods for sloping land.\nTo improve water application uniformity for sprinkler irrigation on sloping land, an experiment was\nconducted on an artificial slope to determine the effects of pulsating versus constant pressure on\nsprinkler flow rate, radius of throw, water distribution pattern, and water application uniformity.\nCompared with sprinkler flow rate and water distribution uniformity at constant pressure, sprinkler\nflow rate was not reduced, but water distribution uniformity for a single sprinkler was improved\ndue to the decreased uphill throw, downhill throw and the ratio of downhill throw to uphill throw\nat pulsating pressure. The Christiansen Uniformity Coefficient (CU) value of water distribution\nfor a single sprinkler at pulsating pressure was about 10% higher than that of constant pressure.\nWhen water distribution of single sprinkler overlapped with rectangular arrangement, CU values\nfor pulsating pressure were on average 4.06% higher than those for constant pressure with different\nsprinkler spacings. Thus, pulsating pressure is recommended for use in sprinkler irrigation on sloping\nland to improve water application uniformity....
Accurate digital mapping of soil organic carbon (SOC) is important in understanding the\nglobal carbon cycle and its implications in mitigating climate change. Visible and near-infrared\nhyperspectral imaging technology provides an alternative for mapping SOC efficiently and accurately,\nespecially at regional and global scales. However, there is a lack of understanding of the impacts\nof spatial resolution of hyperspectral images and spatial autocorrelation of spectral information on\nthe accuracy of SOC retrievals. In this study, the hyperspectral images (380-1700 nm) with a spatial\nresolution of 1 m were acquired by Headwall Micro-Hyperspec airborne sensors. Then, hyperspectral\nimages were resampled into three dierent spatial resolutions of 10 m, 30 m, and 60mby near neighbor\n(NN), bilinear interpolation (BI), and cubic convolution (CC) resampling methods. The geographically\nweighted regression (GWR) model was used to explore the role of spatial autocorrelation in predicting\nSOC contrast with the partial least squares regression (PLSR) model. Results showed that (1) the\nhyperspectral images can be used to predict SOC and the spatial autocorrelation can improve the\nprediction accuracy, as the ratio of performance to interquartile range (RPIQ) values of PLSR and\nGWR were 1.957 and 2.003; (2) The SOC prediction accuracy decreased with the degradation of spatial\nresolution, and the RPIQ values of PLSR were from 1.957 to 1.134, and of GWR were from 2.003 to\n1.136; (3) Three resampling methods had a much weaker influence than spatial resolution on SOC\npredictions because the differences of RPIQ values of NN, BI, and CC resampling methods were 0.146,\n0.175, and 0.025 in the spatial resolutions of 10 m, 30 m, and 60 m, respectively; (4) Finally, the Global\nMoranâ??s I and the Anselin Local Moranâ??s I proved the existence of the spatial autocorrelation in SOC\nmaps. We hope that this study can offer valuable information for digital soil mapping by satellite\nhyperspectral images in the near future....
Crop production in the Fanteakwa District is predominantly rain fed, exposing this major livelihood activity to the variability or\nchange in rainfall pattern.The net potential effect of severe changes in rainfall pattern is the disruption in crop production leading to\nfood insecurity, joblessness, and poverty. As a major concern to food production in Ghana, this study seeks to show the relationship\nbetween the production of major crops and rainfall distribution pattern in the Worobong Agroecological Area (WAA) relative to\nfood security in the face of climate change. The study analysed the variability in local rainfall data, examining the inter seasonal\n(main and minor) rainfall distribution using the precipitation concentration index (PCI), and determined the pattern, availability\nof water, and the strength of correlation with crop production in the WAA. Data from the Ghana Meteorological Agency (GMet)\nspanning a 30-year period and grouped into 3 decades of 10 years each was used. Selected crop data for 1993-2014 was also obtained\nfrom the Ministry of Food and Agricultureâ??s District office and analyzed for trends in crop yield over the period and established\nrelationship between the crop data and the rainfall data. Part of the result revealed that rainfall variability within the major seasons\nin the 3 groups was lower than the minor seasons. It further showed that yields of three crops have declined over the period.\nAmong the strategies to sustain crop production is to make the findings serve as useful reference to inform discussions and policy\non adaptive agricultural production methodologies for the area in the face of changing climate....
The contribution of rain-fed farming to national food production in Indonesia has yet to be optimal. The major constraint has been\nlimited water supply, where it relies exclusively on the rainfall, and hence its planting index (PI) is still low, on average only 1.05.\nThe establishment of water management system to support rain-fed fields with the introduction of suitable cultivation techniques\n(gogo rancah, walik jerami, super jarwo, and ratoon paddy) is known to be effective in rain-fed farming. Further, the use of droughttolerant\npaddy variety and changing cropping pattern to focus on paddy, maize, and soybean would potentially improve the food\nproduction capacity in Indonesia. This study has shown these interventions, when applied to the existing 4 million ha rain-fed\nfields, are estimated to increase annual rice production by 16.7 million tons.The production of maize and soybean is also expected\nto increase by 3.7 million tons and 0.98 million tons per year, respectively. It is beyond the scope of this study, however, to consider\nthe actual benefit felt by rain-fed smallholder farmers. Future research with farmers as its focus and the capacity of Indonesian\ninstitutions toward rain-fed farming thus will contribute further to the rain-fed farming development in Indonesia. This article\nshares a strategy in maximising the contribution of the currently available 4 million hectares of rain-fed land to the national food\nproduction, and hence sustainable food self-sufficiency in Indonesia....
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