Multispectral images of peach related to firmness and maturity at harvest

wo multispectral maturity classifications for red soft-flesh peaches (‘Kingcrest’, ‘Rubyrich’ and ‘Richlady’ n = 260) are proposed and compared based on R (red) and R/IR (red divided by infrared) images obtained with a three CCD camera (800 nm, 675 nm and 450 nm). R/IR histograms were able to correct the effect of 3D shape on light reflectance and thus more Gaussian histograms were produced than R images. As fruits ripened, the R/IR histograms showed increasing levels of intensity. Reference measurements such as firmness and visible spectra also varied significantly as the fruit ripens, firmness decreased while reflectance at 680 nm increased (chlorophyll absorption peak)

Selection Models for the Internal Quality of Fruit, based on Time Domain Laser Reflectance Spectroscopy

Time domain laser reflectance spectroscopy (TRS) was applied for the first time to evaluate internal fruit quality. This technique, known in medicine-related knowledge areas, has not been used before in agricultural or food research. It allows the simultaneous measurement of two optical characteristics of the sample: light scattering inside the tissues and light absorption. Models to estimate non-destructively firmness, soluble solids and acid contents in tomato, apple, peach and nectarine were developed using sequential statistical techniques: principal component analysis, multiple stepwise linear regression, clustering and discriminant analysis. Consistent correlations were established between the two parameters measured with TRS, i.e. absorption and transport scattering coefficients, with chemical constituents (soluble solids and acids) and firmness, respectively. Classification models were created to sort fruits into three quality grades (‘low’, ‘medium’ and ‘high’), according to their firmness, soluble solids and acidity

Optical parameters in food and agricultural processing

The non-destructive feature of optical techniques has gained interests for quality assessment of various agricultural produce as well as in food processing technology. The principle and interaction of light with food and agricultural produce provide essential information for quality assessment which promotes non-destructive inspection methods. This review encompasses the determination of optical properties associated with the evaluation of the quality of agricultural produce. The understanding of how light interacts with turbid agricultural produce is also presented, including light characteristics such as absorption and scattering. A brief overview of the estimation and application of the optical parameters in food and agricultural processing are discussed. The problems and implementation of optical parameters as well as its future trend are also included

Prediction of the kiwifruit decline syndrome in diseased orchards by remote sensing

Eight years after the first record in Italy, Kiwifruit Decline (KD), a destructive disease causing root rot, has already affected more than 25% of the area under kiwifruit cultivation in Italy. Diseased plants are characterised by severe decay of the fine roots and sudden wilting of the canopy, which is only visible after the season's first period of heat (July-August). The swiftness of symptom appearance prevents correct timing and positioning for sampling of the disease, and is therefore a barrier to aetiological studies. The aim of this study is to test the feasibility of thermal and multispectral imaging for the detection of KD using an unsupervised classifier. Thus, RGB, multispectral and thermal data from a kiwifruit orchard, with healthy and diseased plants, were acquired simultaneously during two consecutive growing seasons (2017-2018) using an Unmanned Aerial Vehicle (UAV) platform. Data reduction was applied to the clipped areas of the multispectral and thermal data from the 2017 survey. Reduced data were then classified with two unsupervised algorithms, a K-means and a hierarchical method. The plant vigour (canopy size and presence/absence of wilted leaves) and the health shifts exhibited by asymptomatic plants between 2017 and 2018 were evaluated from RGB data via expert assessment and used as the ground truth for cluster interpretation. Multispectral data showed a high correlation with plant vigour, while temperature data demonstrated a good potential use in predicting health shifts, especially in highly vigorous plants that were asymptomatic in 2017 and became symptomatic in 2018. The accuracy of plant vigour assessment was above 73% when using multispectral data, while clustering of the temperature data allowed the prediction of disease outbreak one year in advance, with an accuracy of 71%. Based on our results, the unsupervised clustering of remote sensing data could be a reliable tool for the identification of sampling areas, and can greatly improve aetiological studies of this new disease in kiwifruit

Actuators and sensors for application in agricultural robots: A review

In recent years, with the rapid development of science and technology, agricultural robots have gradually begun to replace humans, to complete various agricultural operations, changing traditional agricultural production methods. Not only is the labor input reduced, but also the production efficiency can be improved, which invariably contributes to the development of smart agriculture. This paper reviews the core technologies used for agricultural robots in non-structural environments. In addition, we review the technological progress of drive systems, control strategies, end-effectors, robotic arms, environmental perception, and other related systems. This research shows that in a non-structured agricultural environment, using cameras and light detection and ranging (LiDAR), as well as ultrasonic and satellite navigation equipment, and by integrating sensing, transmission, control, and operation, different types of actuators can be innovatively designed and developed to drive the advance of agricultural robots, to meet the delicate and complex requirements of agricultural products as operational objects, such that better productivity and standardization of agriculture can be achieved. In summary, agricultural production is developing toward a data-driven, standardized, and unmanned approach, with smart agriculture supported by actuator-driven-based agricultural robots. This paper concludes with a summary of the main existing technologies and challenges in the development of actuators for applications in agricultural robots, and the outlook regarding the primary development directions of agricultural robots in the near future

Review: computer vision applied to the inspection and quality control of fruits and vegetables

This is a review of the current existing literature concerning the inspection of fruits and vegetables with the application of computer vision, where the techniques most used to estimate various properties related to quality are analyzed. The objectives of the typical applications of such systems include the classification, quality estimation according to the internal and external characteristics, supervision of fruit processes during storage or the evaluation of experimental treatments. In general, computer vision systems do not only replace manual inspection, but can also improve their skills. In conclusion, computer vision systems are powerful tools for the automatic inspection of fruits and vegetables. In addition, the development of such systems adapted to the food industry is fundamental to achieve competitive advantages

Sensors for product characterization and quality of specialty crops—A review

This review covers developments in non-invasive techniques for quality analysis and inspection of specialty crops, mainly fresh fruits and vegetables, over the past decade up to the year 2010. Presented and discussed in this review are advanced sensing technologies including computer vision, spectroscopy, X-rays, magnetic resonance, mechanical contact, chemical sensing, wireless sensor networks and radiofrequency identification sensors. The current status of different sensing systems is described in the context of commercial application. The review also discusses future research needs and potentials of these sensing technologies. Emphases are placed on those technologies that have been proven effective or have shown great potential for agro-food applications. Despite significant progress in the development of non-invasive techniques for quality assessment of fruits and vegetables, the pace for adoption of these technologies by the specialty crop industry has been slow

NIR technologies for high speed fruit grading

Today’s consumers seek information about food products so they can purchase with confidence, even if it translates to higher priced items. It is the aim of this thesis to improve the instruments available for the prediction of food quality, in particular, to advance the technology used for the rapid, low cost, non-destructive analysis of the internal quality of fruit. This thesis contains both experimental and theoretical work covering two main areas of research: the first deals with issues related to the practical grading of fruit, the second with the NIR light penetration and distribution within a fruit. A ‘rotary grader’ has been built to enable the rapid, non-destructive assessment of fruit. Up to twenty fruit can be placed on a rotating disk, which can be spun at a controlled speed or moved to fixed positions for stationary studies. A variety of optical arrangements can be mounted to enable the acquisition of spectra from individual fruit in different ‘modes’ of operation. A comparison between the different optical arrangements is presented. It was found that transmission mode (where the light passes right through the fruit) performs better than reflectance mode (where the detected light comes primarily from near the surface of the fruit). This result has been previously predicted and has now been demonstrated with the equipment used in this work. Different angles of transmission are compared as well as different fruit orientations for their influence on fruit quality predictions. It was found that 90° transmission (where the light is detected at right angles to the illumination of the fruit) might work best for randomly orientated kiwifruit; if they are hand placed then 180° or 150° may be more effective. A study of mandarins suggested that the acid content cannot be assessed directly, but it can be inferred from surface properties such as colour and chlorophyll content. This is contrary to several published reports and questions the ability of NIR spectroscopy to measure low concentrations of acid in fruit. A third experiment showed that soluble solids content (SSC) and dry matter (DM) can be assessed from moving apples with a prediction error of 0.54 ± 0.07 °Brix (R²ₚ = 0.65) and 0.66 ± 0.08 % (R²ₚ = 0.80) respectively. A unique perspective is presented showing where the useful information is attained from the continuously moving fruit. Transmission and reflectance spectra from apples moving at speeds of up to 3 fruit/s have been recorded, and the optimal spectra from the sequence were combined for improved predictions. To investigate the NIR light distribution and penetration in fruit a fibre optic probe was built to take direct measurements of the light levels inside fruit. This enabled, for the first time, the degree of light penetration to be assessed without altering the optical boundaries of the fruit (for example cutting away sections of the fruit). Corresponding simulations using Monte Carlo photon tracing, match the experimental measurements. It was found that fruit such as mandarin exhibit strong internal reflection from the skin, a result that has not previously been reported. The influence of the core and other features in the fruit on the light penetration and distribution is also studied showing perturbations in the internal light levels mapping out these features

Investigating Maturity State and Internal Properties of Fruits Using Non-destructive Techniques-a Review

The evaluation of internal condition of the fruit via destructive techniques mostly damaged the internal and external fruit structure. However, there are several non-destructive techniques available could be applied in the agricultural industry, specifically for observing internal fruit conditions. Different kinds of internal conditions of fruits are evaluated in terms of their quality and ripeness levels. These non-destructive techniques include fruit evaluation via ultrasonic measurement techniques, light spectroscopy, imaging via Magnetic Resonance Imaging (MRI) and X-Ray, computer vision, electric nose and also vibration. The capabilities and the effectiveness of these techniques towards fruit monitoring are thoroughly discussed. Besides, the drawback of these non-destructive technique has been analysed