Constantino Valero

Nondestructive quantification of chemical and physical properties of fruits by time-resolved reflectance spectroscopy in the wavelength range 650–1000 nm

Time-resolved reflectance spectroscopy can be used to assess nondestructively the bulk (rather than the superficial) optical properties of highly diffusive media. A fully automated system for time-resolved reflectance spectroscopy was used to evaluate the absorption and the transport scattering spectra of fruits in the red and the near-infrared regions. In particular, data were collected in the range 650-1000 nm from three varieties of apples and from peaches, kiwifruits, and tomatoes. The absorption spectra were usually dominated by the water peak near 970 nm, whereas chlorophyll was detected at 675 nm. For all species the scattering decreased progressively with increasing wavelength. A best fit to water and chlorophyll absorption line shapes and to Mie theory permitted the estimation of water and chlorophyll content and the average size of scattering centers in the bulk of intact fruits.

Time-Resolved Reflectance Spectroscopy Applied to the Nondestructive Monitoring of the Internal Optical Properties in Apples

Time-resolved reflectance has been used for the nondestructive measurement of optical properties in apples. The technique is based on the detection of the temporal dispersion of a short laser pulse injected into the probed medium. The time distribution of re-emitted photons interpreted with a solution of the diffusion equation yields the mean values of the absorption and reduced scattering coefficients of the medium. The proposed technique proved useful for the measurement of the absorption and scattering spectra of different varieties of apples, revealing the spectral shape of chlorophyll. No major variations were observed in the experimental data when the fruit was peeled, showing that the optical properties measured were those of the pulp. With this technique the change in chlorophyll absorption during storage and ripening could be followed. Finally, a compact prototype working at few selected wavelengths was designed and constructed, demonstrating potentialities of the technique for industrial applications.

Grapevine Yield and Leaf Area Estimation Using Supervised Classification Methodology on RGB Images Taken under Field Conditions

The aim of this research was to implement a methodology through the generation of a supervised classifier based on the Mahalanobis distance to characterize the grapevine canopy and assess leaf area and yield using RGB images. The method automatically processes sets of images, and calculates the areas (number of pixels) corresponding to seven different classes (Grapes, Wood, Background, and four classes of Leaf, of increasing leaf age). Each one is initialized by the user, who selects a set of representative pixels for every class in order to induce the clustering around them. The proposed methodology was evaluated with 70 grapevine (V. vinifera L. cv. Tempranillo) images, acquired in a commercial vineyard located in La Rioja (Spain), after several defoliation and de-fruiting events on 10 vines, with a conventional RGB camera and no artificial illumination. The segmentation results showed a performance of 92% for leaves and 98% for clusters, and allowed to assess the grapevine’s leaf area and yield with R2 values of 0.81 (p < 0.001) and 0.73 (p = 0.002), respectively. This methodology, which operates with a simple image acquisition setup and guarantees the right number and kind of pixel classes, has shown to be suitable and robust enough to provide valuable information for vineyard management.

Detection of internal quality in kiwi with time-domain diffuse reflectance spectroscopy

Time-domain diffuse reflectance spectroscopy (TRS), a medical sensing technique, was used to evaluate internal kiwi fruit quality. The application of this pulsed laser spectroscopic technique was studied as a new, possible non-destructive, method to detect optically different quality parameters: firmness, sugar content, and acidity. The main difference with other spectroscopic techniques is that TRS estimates separately and at the same time absorbed light and scattering inside the sample, at each wavelength, allowing simultaneous estimations of firmness and chemical contents. Standard tests (flesh puncture, compression with ball, .Brix, total acidity, skin color) have been used as references to build estimative models, using a multivariate statistical approach. Classification functions of the fruits into three groups achieved a performance of 75% correctly classified fruits for firmness, 60% for sugar content, and 97% for acidity. Results demonstrate good potential for this technique to be used in the development of new sensors for non-destructive quality assessment.

Fleets of robots for environmentally-safe pest control in agriculture

Abstract Feeding the growing global population requires an annual increase in food production. This requirement suggests an increase in the use of pesticides, which represents an unsustainable chemical load for the environment. To reduce pesticide input and preserve the environment while maintaining the necessary level of food production, the efficiency of relevant processes must be drastically improved. Within this context, this research strived to design, develop, test and assess a new generation of automatic and robotic systems for effective weed and pest control aimed at diminishing the use of agricultural chemical inputs, increasing crop quality and improving the health and safety of production operators. To achieve this overall objective, a fleet of heterogeneous ground and aerial robots was developed and equipped with innovative sensors, enhanced end-effectors and improved decision control algorithms to cover a large variety of agricultural situations. This article describes the scientific and technical objectives, challenges and outcomes achieved in three common crops.

Nondestructive measurements of the optical properties of fruits by means of time-resolved reflectance

The non-destructive assessment of the quality of fruits is getting a crucial task. As a possible first step toward the noninvasive evaluation of quality, we propose the measurement of the internal optical properties of fruits and vegetables by means of time-resolved reflectance spectroscopy. Mode-locked dye and Titanium:Sapphire lasers are used as the illumination source. The reflectance signal is processed by an electronic chain for time-correlated single-photon counting. The time-dispersion of re-emitted photons is fitted to the solution of the diffusion equation, with absorption and transport scattering as free parameters. The whole instrumentation is computer-controlled and allows one to perform measurements from 610 to 1000 nm. Absorption and scattering spectra of several species of fruits were acquired, and particular attention was devoted to the optical characterization of apples.

Predicting Pitting Damage During Processing in Californian Clingstone Peaches Using Color and Firmness Measurements

Nondestructive and destructive measures of color and firmness were studied to determine the feasibility of predicting the level of damage to clingstone peaches during mechanical pitting. Nondestructive and destructive measures of firmness were equally variable when measuring the firmness at three equatorial cheek locations (coefficient of variation of about 17%), both had inverse relationships with the level of pitting damage (r2 ranged from 0.70 to 0.83), and could classify peaches into two categories (those subject to and those not subject to pitting damage) with classification accuracies of 75.2% and 81.7%, respectively. Destructive firmness was not a good predictor of nondestructive firmness in clingstone peaches. Skin color was not a good predictor of flesh color in clingstone peaches, and flesh color was not a good predictor of potential for damage to clingstone peaches during mechanical pitting.

Feature extraction on vineyard by Gustafson Kessel FCM and K-means

Image segmentation is a process by which an image is partitioned into regions with similar features. Many approaches have been proposed for color images segmentation, but Fuzzy C-Means has been widely used, because it has a good performance in a wide class of images. However, it is not adequate for noisy images and it takes longer runtimes, as compared to other method like K-means. For this reason, several methods have been proposed to improve these weaknesses. Methods like Fuzzy C-Means with Gustafson-Kessel algorithm (FCM-GK), which improve its performance against the noise, but increase significantly the runtime. In this paper we propose to use the centroids generated by GK-FCM algorithms as seeding for K-means algorithm in order to accelerate the runtime and improve the performance of K-means with random seeding. These segmentation techniques were applied to feature extraction on vineyard images. Segmented images were evaluated using several quality parameters such as the rate of correctly classified area and runtime.

Analysis of the mechanical aggressiveness of three orange packing systems: packing table, box filler and net filler

Three different types of orange packing systems (packing table, box filler, and net filler) were analysed using an instrumented sphere IS 100 (7 cm . ) in four orange packing lines in the region of Levante (Spain). Four packing tables, three box fillers, and three net fillers were tested by analysing impacts inflicted to fruit at the entrance and outlet transfer points of the machine. In general, entrance transfer points were more aggressive than outlet transfer points. Box filler was the least aggressive machine.

A partial study of vertical distribution of conventional no-till seeders and spatial variability of seed depth placement of maize in the Alentejo region, Portugal

Abstract The requirements for a good stand in a no-till field are the same as those for conventional planting as well as added field and machinery management. Among the various factors that contribute towards producing a successful maize crop, seed depth placement is a key determinant. Although most no-till planters on the market work well under good soil and residue conditions, adjustments and even modifications are frequently needed when working with compacted or wet soils or with heavy residues. The main objective of this study, carried out in 2010, 2011 and 2012, was to evaluate the vertical distribution and spatial variability of seed depth placement in a maize crop under no-till conditions, using precision farming technologies and conventional no-till seeders. The results obtained indicate that the seed depth placement was affected by soil moisture content and forward speed. The seed depth placement was negatively correlated with soil resistance and seeding depth had a significant impact on mean emergence time and the percentage of emerged plants. Shallow average depth values and high coefficients of variation suggest a need for improvements in controlling the seeders’ sowing depth mechanism or more accurate calibration by operators in the field.