Effect of manure application on crop yield and soil chemical properties in a long-term field trial of semi-arid Kenya

The sustainability of cereal/legume intercropping was assessed by monitoring trends in grain yield, soil organic C (SOC) and soil extractable P (Olsen method) measured over 13 years at a long-term field trial on a P-deficient soil in semi-arid Kenya. Goat manure was applied annually for 13 years at 0, 5 and 10 t ha(-1) and trends in grain yield were not identifiable because of season-to-season variations. SOC and Olsen P increased for the first seven years of manure application and then remained constant. The residual effect of manure applied for four years only lasted another seven to eight years when assessed by yield, SOC and Olsen P. Mineral fertilizers provided the same annual rates of N and P as in 5 t ha(-1) manure and initially ,gave the same yield as manure, declining after nine years to about 80%. Therefore, manure applications could be made intermittently and nutrient requirements topped-up with fertilizers. Grain yields for sorghum with continuous manure were described well by correlations with rainfall and manure input only, if data were excluded for seasons with over 500 mm rainfall. A comprehensive simulation model should correctly describe crop losses caused by excess water.

Distribution of nutrients in the root zone affects yield, quality and blossom end rot of tomato fruits

Tomato plants (Lycopersicon esculentum Mill. 'DRK') were grown hydroponically in two experiments to determine the effects of nutrient concentration and distribution in the root zone on yield, quality and blossom end rot (BER). The plants were grown in rockwool with their root systems divided into two portions. Each portion was irrigated with nutrient solutions with either the same or different electrical conductivity (EC) in the range 0 to 6 dS m(-1). In both experiments, fruit yields decreased as EC increased from moderate to high when solutions of equal concentration were applied to both portions of the root system. However, higher yields were obtained when a solution with high EC was applied to one portion of the root system and a solution of low EC to the other portion. For example, the fresh weight of mature fruits in the 6/6 treatment was only 20% that of the 3/3 treatment but the 6/0 treatment had a yield that was 40% higher. The reduction in yield in the high EC treatments was due to an increase in the number of fruits with BER and smaller fruit size. BER increased from 12% to 88% of total fruits as EC increased from 6/0 to 6/6 and fruit length decreased from 67 mm to 52 mm. Fruit quality (expressed as titratable acidity and soluble solids) increased as EC increased. In summary, high yields of high quality tomatoes with minimal incidence of BER were obtained when one portion of the root system was supplied with a solution of high EC and the other portion with a solution of moderate or zero EC.

Distribution of salinity in the root zone affects the yield, quality of tomato fruit

Tomato plants (Lycopersicon esculentum Mill. var. DRK) were grown with a split root system to determine the effect of an unequal distribution of salinity in the root zone on yield and quality. The roots of the plant were divided into two portions and each portion was irrigated with nutrient solutions differing in EC levels achieved by adding Na or K. The maximum yield was observed in treatments with unequal EC when one portion of the roots received only water and the lowest in the high EC treatments. The reduced yield in the high EC treatment was due to the incidence of blossom-end rot and reduced fruit size. Fruit size in the treatments receiving solutions of unequal EC was up to 12% greater than that in the control. No significant differences were found in soluble solids and acidity between control and all other unequal EC treatments. Ca concentration was significantly higher in the treatments where one portion of the root system received water. It was concluded that high salinity had positive effects on yield and quality provided that one portion of the root system were placed in low EC or only water.

Remote estimation of thermal inertia and soil heat flux for bare soil

A method is presented which allows thermal inertia (the soil heat capacity times the square root of the soil thermal diffusivity, C(h)rootD(h)), to be estimated remotely from micrometeorological observations. The method uses the drop in surface temperature, T-s, between sunset and sunrise, and the average night-time net radiation during that period, for clear, still nights. A Fourier series analysis was applied to analyse the time series of T-s . The Fourier series constants, together with the remote estimate of thermal inertia, were used in an analytical expression to calculate diurnal estimates of the soil heat flux, G. These remote estimates of C(h)rootD(h) and G compared well with values derived from in situ sensors. The remote and in situ estimates of C(h)rootD(h) both correlated well with topsoil moisture content. This method potentially allows area-average estimates of thermal inertia and soil heat flux to be derived from remote sensing, e.g. METEOSAT Second Generation, where the area is determined by the sensor's height and viewing angle. (C) 2003 Elsevier B.V. All rights reserved.

Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

Parameter estimation using a particle method: inferring mixing coefficients from sea level observations

This paper presents a first attempt to estimate mixing parameters from sea level observations using a particle method based on importance sampling. The method is applied to an ensemble of 128 members of model simulations with a global ocean general circulation model of high complexity. Idealized twin experiments demonstrate that the method is able to accurately reconstruct mixing parameters from an observed mean sea level field when mixing is assumed to be spatially homogeneous. An experiment with inhomogeneous eddy coefficients fails because of the limited ensemble size. This is overcome by the introduction of local weighting, which is able to capture spatial variations in mixing qualitatively. As the sensitivity of sea level for variations in mixing is higher for low values of mixing coefficients, the method works relatively well in regions of low eddy activity.