Antihus Hernández Gómez

A new approach to predict n, p, k and OM content in a loamy mixed soil by using near infrared reflectance spectroscopy

Near Infrared Reflectance (NIR) spectroscopy technique was used to estimate N, P, K and OM content in a loamy mixed soil of Zhejiang, Hangzhou. A total of 165 soil samples were taken from the field, 135 samples spectra were used during the calibration and cross-validation stage. 30 samples spectra were used to predict N, P, K and OM concentration. NIR spectra and constituents were related using Partial Least Square Regression (PLSR) technique. The r between measured and predicted values of N and OM, were 0.925 and 0.933 respectively, demonstrated that NIR spectroscopy have potential to predict accurately this constituents in this soil, not being this way in the prediction of P and K with r, 0.469 and 0.688 respectively, demonstrated a poorly for P and a less successfully for K prediction. The result also shows that NIR could be a good tool to be combined with precision farming application.

Nondestructive Determination Method of Fruit Quantity Detection Based on Vis/NIR Spectroscopy Technique

The objective of this study was to establish the relationship between vis/NIR spectral and the major physiological properties of tomato-soluble solids content (SSC), acidity (pH) and fruit firmness. A total of 200 tomatoes were hand harvested and analyzed the spectra features using spectrophotometer. Principal component regression (PCR) and partial least squares (PLS) were used to develop the prediction models. The models for SSC (r= 0.90) of standard error of prediction (SEP) 0.19degBrix with three factors; pH (r- 0.83) of SEP 0.09 with four factors; compression force (r= 0.81) of SEP 16.017N with six factors, and puncture force (r= 0.83) of SEP 1.18N with three factors, showed the excellent prediction performance. The vis/NIR spectroscopy technique had significantly greater accuracy in determining SSC. It was concluded that it is possible to assess the quality characteristics of tomato

Estudio energético del sistema de bombeo en el Instituto de Ciencia Animal, Cuba

Con el objetivo de realizar un estudio energetico del sistema de bombeo del Instituto de Ciencia Animal (ICA), se procedio a la mapificacion y deteccion de salideros en la conductora principal, se midieron las fugas de agua en las redes interiores y se determino el porciento de este liquido que se pierde por derroche. Conjuntamente se analizo el consumo energetico de la bomba, se determino la potencia real consumida y la eficiencia del motor. Los resultados demostraron que existen perdidas de agua respecto al total que se bombea (1 400 m3), por mal uso (39,67%) y por mal estado tecnico de las redes (31,76%). El estudio energetico mostro que el consumo electrico anual de la institucion por cuestion de abasto de agua es de 310 034.49 kW, lo que representa 67,6 toneladas equivalentes de petroleo, para un gasto anual de la institucion de 71 962.38 USD. Se concluye que si se eliminan las perdidas de agua, se evitan 5 horarios de bombeo, lo que representa un ahorro de 51 405.31 USD al ano por dejar de importar 48,26 toneladas de petroleo, ademas se dejan de emitir a la atmosfera 131,75 t de CO2.

Spectral feature characterizing and nitrogen content prediction in a soil with different particle size and moisture content

Near-infrared reflectance (NIR) is a valuable fast and convenient technique able to quantify several soil properties. This research work was focused in to analyze the influence of moisture content, particle size, light source incidence angle and captator height on loamy mixed soil spectra. On the other hand, prediction models for Nitrogen (N) content at different moisture content and particle sizes were obtained, and the influence of these properties on N prediction was studied, as well as, the future applicability of NIR spectroscopy as a technique able to make prediction on site was analyzed. Captator height 100 mm and light source angle 45° were chosen as presenting sharpest spectra without apparent scatter effect above of the other heights and angles used. Moisture content and particle size were found to affect strongly the absorbance of the spectra and an accurate N prediction was obtained when the particle sizes vary from 0.5-1.0; 1.0-2.0 and 2.0-5 mm with r of 0.819; 0.815 and 0.818, respectively. Poor N prediction was obtained when the soil kept its natural moisture content with r of 0.575 and Standard Error of Prediction (SEP) of 3.275 on the contrary with the performance when it was dry with r of 0.815 and SEP of 2.425.