This PDF file contains the front matter associated with SPIE Proceedings Volume 8881, including the Title Page, Copyright Information, Table of Contents, and the Conference Committee listing.

The plant growth based on the scanning laser beam is newly developed. Three semiconductor lasers with three primary colors, i.e., blue, green and red are used. Here, the laser scanned position is restricted only to the plant leaves, where the light illumination is needed. The feedback system based on the perspective projection is developed. The system consists of the automatic position correction from the camera image. The automatic image extraction of the leaf parts is also introduced. The electric power needed for this system is as small as 6.25% compared with the traditional white fluorescent lamp. Furthermore, experimental results show that the red-color laser light is particularly efficient for the growth of the radish sprouts.

Plants of Ipomoea quamoclit L. were exposed to an 8-hour photoperiod under natural daylight, which was supplemented with 60 W incandescent lamps to give an 8- to 24-hour day. Under photoperiods of 12 hours or less, flower buds were initiated, while the period from bud formation to flowering was shortened in plants grown under a 12-hour photoperiod. Photoperiods of 12 hours or less had no effect on plant height and number of nodes. The present results suggest that Ipomoea quamoclit L. is a short-day plant.

Plant factory has been attracting attention as a new system of food production, and there are approximately 130 commercially operated facilities in March 2012 in Japan. Currently, leafy vegetables are mainly produced in plant factory. However, not only year-round and agricultural chemical free production but new researches focused on high value-added vegetable production and raw material production for pharmaceutical compounds have been studied. This report outlines the recent trends in research on high-value-added plants using light environments.

Precision agriculture addresses the variability in crop growth and its underlying causes to achieve the optimal plant behavior or yield (quantity as well as quality). The physiological processes to be monitored can be at different scales like the subcellular level, the leaf, the whole plant, a field or a region. Reflectance spectroscopy and fluorescence spectroscopy are the main techniques used for monitoring crop conditions. Imaging at different scales avoids that some spatially distributed phenomena are not observed. Hyperspectral or multi-spectral imaging and fluorescence imaging or a combination thereof yield vast amounts of data that require advanced analysis tools to yield usable information. The observations are frequently used in inverse modeling to identify underlying processes of growth, stress or infection.

We examine the effect of different wavelength spectra in the performance of our optical penetration-based silkworm pupa sex identification system. With available low-cost light emitting diodes (LEDs), each emitting different wavelength spectra at 468 nm, 565 nm, 639 nm, 940 nm, and broad white light, we find that the body of the silkworm pupa can block blue and near infrared light while allowing green and red light pass through. In particular, the red light can clearly highlight an important organ called “chitin gland” of the female, leading to high accuracy of silkworm gender identification. In our experiment with 120 silkworm pupae, measured high average 92.8% and lower average 87.5% accuracies in identifying silkworm gender are obtained under red and white light LEDs, respectively.

Over the past few decades, scientists have understood the needs for the exploitation of optical means particularly Vis-NIR spectroscopy to measure agriculture soil properties in real-time. The objective of this study is therefore to investigate the potential of Vis-NIR spectroscopy for mapping of multiple (19) soil properties using the optical-based real-time soil sensor (RTSS). For this purpose, Vis-NIR soil reflectance spectra (from 310 to 1700nm) were acquired using a tractor-mounted RTSS at 2 fields of a commercial farm in Hokkaido, Japan. The RTSS consists of a halogen lamp, fiber optics, two spectrophotometers, computer, DGPS receiver, and CCD camera. A total of 262 soil samples were collected subsequently for laboratory chemical analysis. PLSR coupled with full-cross validation was used to establish the relationship between the pre-treated Vis-NIR spectra with the value of soil properties obtained by chemical analysis. From this analysis, it was found that the accuracy of the calibration models ranged from R_val² of 0.65 to 0.86 and RPD from 1.7 to 2.7, meaning that the accuracy some of the models were excellent and others were almost good. Moreover, the predicted maps of 19 soil properties were comparable with the measured map. This shows that the RTSS by means of Vis-NIR spectroscopy can be used for mapping the 19 soil properties.

The problem of vibration measurement has assumed increasing importance in recent years for different aspects. In the first phase of this study an analysis of vibrations by means of contact accelerometers was carried out to study a tree shaking machine used in the mechanical harvesting of olives. Then a kinematic analysis of motion with a contactless method was carried out on a belt transmission system equipped with three pulleys: a high speed camera was used, able to capture up to 500 frames per second thus to follow the position of any moving point of the mechanical system under investigation. Vibrations were acquired detecting the positions during time of a marker fixed on the belt. The proposed method made it possible to analyse the mechanism and verify both known behaviours and neglected aspects in the usual kinematic analysis carried out using acceleration measurements.

We propose the use of “Optical Farming,” which is the leading application of all types of optical technologies, in agriculture and agriculture-related industries. This paper focuses on the optical sensing instruments named “Agriserver,” “Agrigadget” and “LIFS Monitor” developed in our laboratory. They are considered major factors in utilizing Optical Farming. Agriserver is a sensor network system that uses the Internet to collect information on agricultural products growing in fields. Agrigadget contains several optical devices, such as a smartphone-based spectroscopic device and a hand framing camera. LIFS Monitor is an advanced monitoring instrument that makes it possible to obtain physiological information of living plants. They are strongly associated with information communication technology. Their field and data usage performance in agricultural industries are reported.

Spectroscopic methods have been proposed to predict sugarcane quality in the field. There are different sample forms could be used to predict sugar content using spectroscopic methods; raw juice (RJ), clear juice (CJ), fibrated samples (FS), stalk cross sectional surface (SCS) and stalk skin (SS). Thus, this study was conducted to identify the optimum sample form for predicting quality using a low-cost and portable spectrometer. A total of 100 samples from each sample form were scanned using a visible-shortwave near infrared (Vis/SWNIR) spectrometer. The experiment was conducted under the same experimental setup and all data were treated using the same statistical methods. All spectral data were calibrated against brix value. The coefficient of determination (R²) for SCS, FS, CJ, SS and RJ were 0.88, 0.86, 0.84, 0.84, 0.81 and 0.80, respectively. The study found that a Vis/SWNIR spectrometer could be used to predict sugar content from all sample forms. The stalk samples scanned on cross sectional surface was found to be the optimum sample form for quality prediction using a Vis/SWNIR spectrometer.

Construction of large-scale 3D virtual environment is important in many fields such as robotic navigation, urban planning, transportation, and remote sensing, etc. Laser scanning approach is the most common method used in constructing 3D models. This paper proposes an automatic method to fuse image and laser-scanning data in a large-scale 3D virtual environment. The system comprises a laser-scanning device installed on a robot platform and the software for data fusion and visualization. The algorithms of data fusion and scene integration are presented. Experiments were performed for the reconstruction of outdoor scenes to test and demonstrate the functionality of the system. We also discuss the efficacy of the system and technical problems involved in this proposed method.

In this paper, a new approach to field monitoring has been presented. The concept of this method is based on low altitude aerial remote sensing and ground measurements, conducted by a mobile spectrometer. The presented idea of field monitoring is dedicated mainly for precision farming or experimental stations. We assume that non-metric aerial photos obtained from a low altitude are combined with high precision ground measurements from light reflected from the canopies and passing through the plants layer. Firstly, the data that has been obtained from remote sensing is processed by a geographical information system, which results in the generation spatial variation maps. After this step, a mobile spectrometer is taken manually at specific zones for the determination of the real vegetation state. This approach is effective for a study into the state of developing vegetation in regions where there is a large variability in the soil. In this case, the soil-mosaic has a significant influence on the plants conditions as well as its final yield. Another possibility of the applied presented method is by improving remote sensing of plant diseases and the need of fertilisation during the vegetation season.

Realizing that a current smart-mobile device such as a cell phone and a tablet can be considered as a pocket-size computer embedded with a built-in digital camera, this paper reviews and demonstrates on how a mobile device can be specifically functioned as a portable optical instrument for agricultural applications. The paper highlights several mobile device-based optical instruments designed for searching small pests, measuring illumination level, analyzing spectrum of light, identifying nitrogen status in the rice field, estimating chlorine in water, and determining ripeness level of the fruit. They are suitable for individual use as well as for small and medium enterprises.

Accurate monitoring of leaves and plants is a necessity for research on plant physiology. To aid this biological research, we propose a new active contour method to track individual leaves in chlorophyll fluorescence time laps sequences. The proposed active contour algorithm is developed such that it can handle sequences with low temporal resolution. This paper proposes a novel optimization method which incorporates prior knowledge about the plant shape. Tests show that the proposed framework outperforms state of the art tracking methods.

Carbohydrate contents have been demonstrated as indicators for flowering quality of Phalaenopsis plants. In this study, near infrared reflectance (NIR) spectroscopy was employed for quantitative analysis of carbohydrate contents like fructose, glucose, sucrose, and starch in Phalaenopsis. The modified partial least squares regression (MPLSR) method was adopted for spectra analyses of 176 grown plant samples (88 shoots and 88 roots), over the full wavelength range (FWR, 400 to 2498 nm). For fructose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.210% DW, SEV = 0.324% DW) in the wavelength ranges of 1400-1600, 1800-2000, and 2200-2300 nm. For glucose concentrations, the smoothing 1st derivative model can produce the best effect (R_c = 0.975, SEC = 0.196% DW, SEV = 0.264% DW) in the wavelength range of 1400-1600, 1800-2000, and 2100-2400 nm. For sucrose concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.961, SEC = 0.237% DW, SEV = 0.322% DW) in the wavelength range of 1300-1400, 1500-1800, 2000-2100, and 2200-2300 nm. For starch concentrations, the smoothing 1st derivative model can produce the best effect (Rc = 0.873, SEC = 0.697% DW, SEV = 0.774% DW) in the wavelength ranges of 500-700, 1200-1300, 1700-1800, and 2200-2300 nm. This study successfully developed the calibration models for inspecting concentrations of carbohydrates to predict the flowering quality in different cultivation environments of Phalaenopsis. The specific wavelengths can be used to predict the quality of Phalaenopsis flowers and thus to adjust cultivation managements.

Fecal contamination of produce is a food safety issue associated with pathogens such as Escherichia coli that can easily pollute agricultural products via animal and human fecal matters. Outbreaks of foodborne illnesses associated with consuming raw fruits and vegetables have occurred more frequently in recent years in the United States. Among fruits, strawberry is one high-potential vector of fecal contamination and foodborne illnesses since the fruit is often consumed raw and with minimal processing. In the present study, line-scan LED-induced fluorescence imaging techniques were applied for inspection of fecal material on strawberries, and the spectral characteristics and specific wavebands of strawberries were determined by detection algorithms. The results would improve the safety and quality of produce consumed by the public.

In this study, Optical Coherence Tomography (OCT) was used to investigate the effect of short term ozone exposure on both front and back surfaces of the leaves of Allium tuberosum plant. Plant leaves were subjected to treat with 240ppb level of ozone, and imaging data were acquired from back and front surfaces of the leaves. Variations of the biological activations were monitored based on the biospeckles. Standard deviations (SD) of OCT temporal signal at each point were calculated and used to visualize the effect of ozone exposure. Leaf back surface showed higher SDs in biospeckle OCT signal in comparison to these of the front surface. These observations prove that the short term ozone stress on plant can be investigated successively with biospeckle OCT imaging technique.

To evaluate the functional pigments in the tomato fruits nondestructively, we propose a method based on the multispectral diffuse reflectance images estimated by the Wiener estimation for a digital RGB image. Each pixel of the multispectral image is converted to the absorbance spectrum and then analyzed by the multiple regression analysis to visualize the contents of chlorophyll a, lycopene and β-carotene. The result confirms the feasibility of the method for in situ imaging of chlorophyll a, β-carotene and lycopene in the tomato fruits.

Faster and reliable testing technique to count and identify nematode species resided in plant roots is therefore essential for export control and certification. This work proposes utilizing a multichannel microfluidic chip with an integrated flow-through microfilter to retain the nematodes in a trapping chamber. When trapped, it is rather simple and convenient to capture images of the nematodes and later identify their species by a trained technician. Multiple samples can be tested in parallel using the proposed microfluidic chip therefore increasing number of samples tested per day.

A hyperspectral laser scatter imaging (HLSI) system based on a supercontinuum laser in combination with a monochromator has been developed for contactless and non-destructive measuring the ripeness of Braeburn apples. Reflectance images were obtained by a CCD camera at 91 different wavelengths ranging from 550 nm to 1000 nm and transformed into reflectance profiles. A linear function was fitted to the logarithm (log₁₀) of the extracted profiles, resulting in an intercept and a slope. These two parameters were then correlated with apple ripeness parameters such as firmness and soluble solids content (SSC) measured by the reference, destructive methods. Preliminary results showed the potential of slope and intercept to be used as a ripeness indicator. Moreover, during fruit ripening, the new HLSI measurement technique clearly showed the degradation of chlorophyll over time.

A contact spatially resolved spectroscopy (SRS) setup based on a fiber-optics probe in the Vis/NIR range (400-1000 nm) was developed, calibrated, and validated for its measurements and optical properties estimation by means of a metamodeling method on a set of liquid optical phantoms. Thirty Braeburn apples cultivated in sub-fertilization condition were harvested and measured before and after shelf-life storage (2 weeks at 18 °C) by the setup and were analyzed for quality attributes (firmness and soluble solids contents (SSC)) by destructive reference methods. Estimated optical properties (absorption and reduced scattering coefficients) acquired from SRS measurements at the beginning and the end of the shelf-life indicated changes in chemical composition of the apples. Partial Least Squares Regression (PLSR) was employed to construct calibration models relating the estimated optical properties to the reference quality attributes. The constructed PLS models based on the absorption coefficient spectra gave good prediction performance for the quality attributes of the apples in the validation set with correlation coefficients r of 0.901 and r of 0.844, respectively for SSC and firmness. The obtained results clearly show the potential of the SRS measurements for nondestructive quality evaluation of apples.