Luigi Bodria

OPTICAL TECHNIQUES TO ESTIMATE THE RIPENESS OF RED-PIGMENTED FRUITS

During fruit ripening, chlorophyll degradation is responsible for the degreening of the ground color, which is a well-established ripeness indicator for several species. In completely red-pigmented cultivars of fruits such as apples and peaches, this process is not visible, being masked by anthocyanins in the skin. Two different optical systems were developed to non-destructively assess the chlorophyll content in these fruits, to estimate ripeness, and to optimize harvesting and postharvest management. A fluorescence imaging system equipped with a UV-blue actinic light was used to obtain fluorescence images of fruit in which the gray level of pixels correlated (R2 = 0.81) with the firmness of fresh apples (Malus domestica cv. Red Delicious). With this technique it was possible to estimate changes in the firmness and soluble solids sugar content of stored Red Delicious apples undergoing no detectable hue change in the skin. Using the same system with a red actinic light, fluorescence correlated fairly well with firmness for fresh peaches and nectarines (Prunus persica cv. Elegant Lady, Summer Rich, and Morsiani 90), even though the detected fluorescence signal was low in intensity. A laser-diode based, dual-band reflectance probe was developed and tested on fresh peaches (cv. Summer Rich) and stored apples (cv. Royal Gala). The R/IR index, defined as the ratio of the signal measured in red and near-infrared bands, was found to correlate with the chlorophyll content of the fruits (R2 = 0.66), regardless of fruit species and anthocyanin presence. The R/IR index was used to track the postharvest ripening process for fresh peaches harvested at different maturity stages.

Chlorophyll fluorescence sensing for early detection of crop’s diseases symptoms

A chlorophyll fluorescence imaging system based on a filtered xenon lamp, providing actinic light in UV and violet bands, and on a high resolution camera equipped with a 690nm (FWHM=10nm) passband filter, for single band measurements, and with a four bands beam splitter with pass-band filters (450nm, 550nm, 690nm, 740nm, all with a FWHM=10nm), for multispectral measurements, was implemented and applied on wheat plants inoculated with different fungal infections, with the aim of investigating the potential of such a technique for detecting plants disease symptoms. In steady state fluorescence images of attached leaves acquired at 690nm in laboratory conditions, the symptoms appear as highly emitting spots at sub-millimetric or millimetric scale which, with the progress of the disease, develop in larger, low emitting lesions surrounded by high intensity halo. Even if the changes in emission pattern are limited to the neighborhoods of the infection point; this technique allowed to detect disease presence before visible symptoms appear. Kinetic fluorescence imaging performed by acquiring a sequence of images at 690nm during an actinic illumination period of several minutes, allowed to find differences between diseased and healthy areas, even at very early stages, both in terms of intensity and time-dependence of emission. Nevertheless, the excitation/sensing period of several minutes on which this technique is based, limits practical field applications on moving vehicles. Multispectral fluorescence imaging in field conditions resulted unsuccessful during day-time measurements due to plants saturation by long-exposure to direct sunlight and to the interference of the diffuse environmental illumination. On the contrary, night-time imaging confirmed the high potential of this technique for disease detection and quantifications. In particular, an image analysis algorithm based on the ratio of fluorescence images at 550nm and 690nm was implemented, allowing to discriminate plants lesions and to map the disease severity in experimental plots in agreement with visual inspection made by a pathologist.

Detection of foliar disease in the field by the fusion of measurements made by optical sensors

The objective of this research was to detect and recognize plant stress caused by disease in field conditions by combining hyperspectral reflection information between 450 and 900nm and fluorescence imaging. The aim is to develop a tractor mounted cost-effective optical device for site-specific pesticide application in order to reduce and optimize pesticide use. The work reported here used yellow rust (Puccinia striiformis) disease of winter wheat as a model system. In the field hyperspectral reflection images of healthy and infected plants were taken with an imaging spectrograph mounted at spray boom height. Leaf recognition and spectral normalization procedures to account for differences in canopy architecture and spectral illumination were used. A model, based on quadratic discrimination, was built, using a selected group of wavebands to differentiate diseased from healthy plants. The model could discriminate diseased from healthy crop with an error of about 10% using measurements from only three wavebands. Multispectral fluorescence images were taken on the same plants using UV-blue excitation. Through comparison of the 550 and 690 nm fluorescence images, it was possible to clearly detect disease presence. The fraction of pixels in one image, recognized as diseased, was set as final fluorescence disease variable called the lesion index LI). The lesion index was added to the pool of normalized selected reflection wavebands. This pool of observations was used in a quadratic discrimination model. This model was further refined using a neural network approach. The combined model improved disease discrimination compared to either the spectral model or fluorescent model and had a classification error of between 1 and 2 %. The results suggest that there is potential for developing detection systems based on multisensor measurements that can be used to in precision disease control systems for use in arable crops.

Optical Techniques for Assessing the Fruit Maturity Stage

Among the several changes that a fruit undergoes during ripening, chlorophyll degradation is responsible for degreening of ground color, that is a well established maturity indicator for several species. In red pigmented cultivars of apples and peaches, of high interest for the European market, this process is not visible, being masked by a uniform layer of anthocyanins. Two different systems were developed to evaluate non-destructively the chlorophyll content in these fruits, basing on their optical properties, in order to assess their maturity stage allowing for an optimal, quality oriented harvest and post-harvest management. A fluorescence imaging system equipped with a blue actinic light, allowed to obtain fruits fluorescence images in which the gray level of pixels resulted well correlated with firmness of fresh apples (R2=0.81) and permitted to follow the post-harvest evolution of firmness and sugar content of stored apples, even in absence of significant skin colour changes. The system equipped with a red actinic light provided results fairly good correlated with firmness of fresh peaches and nectarines, even though the fluorescence signal resulted quite low due to the low chlorophyll content in the considered cultivars. A dual-band, laser-diode based, punctual reflectance probe was developed and tested on fresh peaches and stored apples. The index R/IR, defined as the ratio of the signal measured in red and near-infrared band, was found to correlate the chlorophyll content of the fruits with R2=0.66, regardless the differences due to the species. Moreover, R/IR resulted a fairly good estimator of conventional quality indices (correlations R2=0.4-0.5 with sugars and firmness), and allowed to track the post-harvest ripening process, showing different evolution patterns for fresh peaches at different maturity stages.