34 research outputs found

    Evaluation of FAO-56 Penman-Monteith and Temperature Based Models in Estimating Reference Evapotranspiration Using Complete and Limited Data, Application to Nigeria

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    Accurate determination of reference evapotranspiration is very essential for precise computation of crop water use. Several models have been used in computing reference evapotranspiration and they require local calibration in order to validate their usage. Climatic data used in computing reference evapotranspiration (ETo) for Abeokuta, Ijebu-Ode and Itoikin were obtained from Nigerian Meteorological Station (NIMET), Lagos Nigeria. For Abeokuta, complete climatic data were used in the computation of the ETo while limited climatic data were used in computing ETo for Ijebu-Ode and Itoikin using FAO-56 Penman-Monteith (FAO-56 PM), Jensen-Haise and Hargreaves models. In Abeokuta, the average coefficients of determination R2 obtained when ETo computed using Jensen-Haise and Hargreaves models were compared with FAO-56 PM model were 0.7914 and 0.5158 respectively. The average Root Mean Square Errors (RMSEs) obtained between Jensen-Haise, Hargreaves and FAO-56 PM models were 1.03 and 1.79 mmd-1 respectively. The index of agreement between pan evaporation and FAO-56 PM, Jensen-Haise and Hargreaves models were 0.56, 0.71 and 0.52 respectively. The average R2 of the ETo computed using  and temperature for FAO-56 PM and Jensen-Haise were 0.6784 and 0.8488 respectively. For Ijebu-Ode, the average R2 when Jensen-Haise, Hargreaves were compared with FAO-56 PM model were 0.9908, 0.9907 respectively. The average RMSEs between FAO-56 PM, Jensen-Haise and Hargreaves were 2.51 and 0.87 mmd-1 respectively while the index of agreement between FAO-56 PM, Jensen-Haise and Hargreaves models were 0.49, 0.88 and 0.54 respectively. Similarly for Itoikin, the average R2 obtained when Jensen-Haise and Hargreaves model were compared with FAO-56 PM were 0.9754 and 0.9557 respectively. The average RMSEs obtained between FAO-56 PM and Jensen-Haise and Hargreaves models were 2.50 and 0.89 mmd-1 respectively while the index of agreement between pan evaporation and FAO-56PM, Jensen-Haise and Hargreaves models were 0.28, 0.61 and 0.34 respectively. It is hereby recommended that beside FAO-56PM model, Jensen-Haise model is also recommended for the computation of ETo in situations where only maximum and minimum temperatures are available in Ogun-Osun River basin

    Estimating Soil Hydraulic Properties from Infrared Measurements of Soil Surface Temperatures and TDR Data

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    The spatiotemporal development of soil surface temperatures (SST) depends on water availability in the near-surface soil layer. Because the soil loses latent heat during evaporation and water available for evaporation depends on soil hydraulic properties (SHP), the temporal variability of SST should contain information about the near-surface SHP. The objective of this study was to investigate the uncertainties of SHP derived from SST. The HYDRUS-1D code coupled with a global optimizer (DREAM) was used to inversely estimate van Genuchten-Mualem parameters from infrared-measured SST and time domain reflectometry (TDR)-measured water contents. This approach was tested using synthetic and real data, collected during September 2008 from a harrowed silty loam field plot in Selhausen, Germany. The synthetic data illustrated that SHP can be derived from SST and that additional soil water content measurements reduce the uncertainty of the estimated SHP. Unlike for the synthetic experiment with a vertically homogeneous soil profile, a layered soil profile had to be assumed to derive SHP from the real data. Therefore, the uncertainty of SHP derived from real data was considerably larger. Water retention curves of undisturbed soil cores were similar to those estimated from SST and TDR data for the deeper undisturbed soil. The retention curves derived from SST and TDR data for the harrowed topsoil layer were typical for a coarse-textured soil and deviated considerably from the retention curves of soil cores, which were typical for a fine-textured soil and similar to those from the subsoil

    Adaptation of a Brush Cutter for Kenaf (Hibiscus cannabinus) Harvesting

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    The adaptation of some existing technologies such as sugarcane-type harvester, jute/reed-type harvesters and forage harvesters for kenaf harvesting has not been successful. These machines apart from being expensive cut kenaf stems into too short fragments. Information regarding machines for kenaf harvesting is rarely found in the literature. In this work, an existing 1.65 kW brush cutter was modified and adapted for kenaf harvesting with the view to developing a low-cost machine for kenaf harvesting. The modifications made include incorporating a suitable metal guard based on the physical properties of kenaf stem and selection of an appropriate serrated blade cutting mechanism. The machine was tested on an experimental field of 3 and 4 months old kenaf plantation, and its performance was evaluated considering the effective field capacity, theoretical field capacity, field efficiency and fuel consumption. The results showed that the field efficiency of the machine ranged from 69.15 – 81.21%. The theoretical field capacity and fuel consumption were 0.14 ha/hr, and 46.91 L/ha, respectively. Furthermore, it was found that kenaf variety had a significant effect (p<0.05) on the theoretical field capacity. The field efficiency was significantly affected (p<0.05), by the maturity of the kenaf plant and harvester blade type. However, blade type and kenaf varieties do not have a significant effect on fuel consumed by the harvester. The kenaf harvesting machine was able to harvest the two kenaf varieties considered in this study when fitted with the 3-tooth and 40-tooth brush cutter blades.  A machine of this nature is a positive development in kenaf harvesting, which hitherto has been an arduous task for kenaf farmers

    Seasonal changes in soil physical properties under long-term no-tillage

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    There is no consensus regarding seasonal changes in soil physical properties within and between rows in long-term no-till (NT) crop production systems. We hypothesized that soil physical properties in a Rhodic Ferralsol under long-term NT differed within and between rows and that these changes are influenced by wetting and drying cycles (WDC). Undisturbed samples were taken within and between crop rows from layers of 0 to 0.10 and 0.10 to 0.20 m depth in September 2010, 2011 and 2012 and March 2012 and 2013. At the first sampling, 40 soil samples were collected within the maize (Zea mays L.) row (R), at interrow (IR) sampling positions, and at an intermediate position (IP) between R and IR. Coordinates for each sampling point were identified so that subsequent samples could be collected from the same location. Soil bulk density (Db), soil water retention curve (WRC), S index, air-entry pressure and pore size distribution were determined. The results confirmed that furrow opening causes significant positive changes in soil physical properties within the crop row and plant growth can be affected by the “confinement” of roots within the R position within long-term NT sites. With each successive sampling, Db decreased and was significantly influenced by recent WDC. The pore size distribution showed larger pores with each successive sampling, providing a higher S index, air-entry pressure, and improved soil physical quality over time. The steady state of soil structural conditions achieved at long term NT can be affected by short term influences related to the crops and weather conditions. However, soil physical properties indicated that a new equilibrium was achieved and that soil under long-term NT may remain physically functional. Our results confirm that soil physical properties under NT are highly dynamic and strongly influenced by (i) soil disturbance caused by furrow opening, (ii) wetting and drying cycles, and (iii) sampling depth. Therefore, we recommend that for quantifying soil physical quality within no-till fields, measurements should be taken within and between crop rows
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