Annia García Pereira

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

A New Approach to Detect Soil Nutrient Content Based on NIR Spectroscopy Technique

The objective of this research was to evaluate the prediction ability of NIR to soil nutrient content. A total of 165 soil samples were obtained from the field and analyzed their spectra features. 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 0.92 and 0.93 respectively, demonstrated that NIRS have potential to predict accurately this constituents in this soil, not being this way in the prediction of P and K with r, 0.48 and 0.68 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

Indicadores de productividad del proceso de pelado y la fuente energética en plantas casaberas artesanales

En Venezuela la elaboracion del casabe se realiza de forma artesanal, se realiza en pequenas comunidades e industrias, la produccion casabera se ha visto afectada por la falta de fuerza de trabajo y bajos indices de productividad. Con la finalidad de mejorar y optimizar la elaboracion de este producto algunas empresas se han abocado en tiempo y recursos para el diseno de sistemas que rallen la yuca. El presente trabajo esta dirigido a evaluar la influencia del proceso de pelado y la fuente energetica en los indicadores de productividad de dos plantas casaberas artesanales del municipio “Simon Rodriguez”, Anzoategui, Venezuela. Para la realizacion de la misma se utiliza la NC 34-37:03 con modificaciones para el proceso y las maquinas en estudio, se determinan los principales indicadores de productividad entre los que se destacan, productividad por tiempo de trabajo limpio, productivo, operativo, entre otros. Los principales resultados que las productividades WL; Wop; WTpr y Wtexp, correspondientes al molino LY-259 supera en 36,3; 26,88; 29,02; 22,48%, al LS-228 y que los indicadores de tiempo que mas influyen en el proceso son: el Tiempo de paradas por lluvia y la falta de fluido electrico (T8) y el Tiempo explotativo (T07).

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.