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Honeybees pollinate over 75% of the total food resources produced annually, and they produce valuable hive products, such as bee pollen, propolis, and royal jelly. However, species such as the Asian hornet (Vespa velutina) feed on more than 85% of honeybees, causing a decline in their population and considerable damage to beekeepers in Korea. To prevent damage to honeybees, a portable real-time monitoring system was developed that detects V. velutina individuals and notifies users of their presence. This system was designed with a focus on portability and ease of installation, as V. velutina can be found in various areas of apiary sites. To detect V. velutina, an improved convolutional neural network YOLOv5s was trained on 1960 high-resolution (3840×2160) image data. At the confidence threshold of ≥0.600 and intersection over the union of ≥0.500, the performance of the system in terms of detection accuracy, precision, recall, F1 score, and mean average precision was high. A distance-based performance comparison showed that the system was able to detect V. velutina individuals while monitoring three beehives. During a field test of monitoring three beehives, the system could detect 83.3% of V. velutina during their hunting activities and send alarms to registered mobile application users.

In this study, the discrete element method was used to optimize the bucket size for the metering device in a garlic planter for enhancing the productivity of garlic farming according to the garlic size. Statistical information concerning the actual shape of garlic cloves was incorporated, and the mechanical properties of garlic were determined using the bulk density, sliding test, and repose angle test for enhancing the fidelity of the simulation model. The optimal bucket size achieving the target plant rate of 97.5% was determined using the developed discrete element model for the three garlic size groups. The linear search method was used for optimization, and batch simulation was performed to validate the optimized results and confirm the performance index of the metering device. A Gaussian distribution based on statistical information accounted for the various garlic sizes in each group. Finally, a metering test verified the reliability of the optimization technique. The differences between the simulation and test results were within 10% for all performance indices, including missing plant rate, multi-plant rate, and planting rate, indicating the high reliability of the analysis model. Subsequently, the larger garlic groups (Groups 2 and 3) exhibited metering performance close to the target plant rate.

Hybridization and polyploidization are pivotal to plant evolution. Genetic crosses between distantly related species are rare in nature due to reproductive barriers but how such hurdles can be overcome is largely unknown. Here we report the hybrid genome structure of xBrassicoraphanus, a synthetic allotetraploid of Brassica rapa and Raphanus sativus. We performed cytogenetic analysis and de novo genome assembly to examine chromosome behaviors and genome integrity in the hybrid. Transcriptome analysis was conducted to investigate expression of duplicated genes in conjunction with epigenome analysis to address whether genome admixture entails epigenetic reconfiguration. Allotetraploid xBrassicoraphanus retains both parental chromosomes without genome rearrangement. Meiotic synapsis formation and chromosome exchange are avoided between nonhomologous progenitor chromosomes. Reconfiguration of transcription network occurs, and less divergent cis-elements of duplicated genes are associated with convergent expression. Genome-wide DNA methylation asymmetry between progenitors is largely maintained but, notably, B. rapa-originated transposable elements are transcriptionally silenced in xBrassicoraphanus through gain of DNA methylation. Our results demonstrate that hybrid genome stabilization and transcription compatibility necessitate epigenome landscape adjustment and rewiring of cis-trans interactions. Overall, this study suggests that a certain extent of genome divergence facilitates hybridization across species, which may explain the great diversification and expansion of angiosperms during evolution.

This study aims to develop a low-drift air induction (AI) nozzle that meets the requirements of agricultural control unmanned aerial vehicles (UAVs). An AI nozzle was designed and manufactured to satisfy the design goals. The performance of the developed AI nozzle was quantitatively evaluated in terms of injection flow rate, air-to-liquid ratio (ALR), spray angle, and droplet size. The average value of the injection flow rate and the variation over time were measured using a gear-type positive displacement precision flow meter. The spray structure and spray angle were obtained at very high temporal resolution using the single image acquisition function of a two-dimensional particle image velocimetry (PIV) system. The droplet size of the spray was measured using a laser diffraction technique. The injection flow rate of the AI nozzle changes with the pressure recovery characteristics inside the nozzle mixing chamber and affects the dynamic stability of the AI nozzle. The spray angle of the AI nozzle with a flat-fan nozzle tip increases linearly with the injection pressure, and if there is additional consideration for the two-phase flow effect, the prediction equation for the single-phase flow can be applied to estimate the spray angle. The generation of air bubble-containing droplets in AI nozzles is formed by large-diameter ligament disintegration caused by a rolled-up liquid sheet and is larger than that of single-phase flow nozzles. The droplet size (Dv0.5) of the developed AI nozzle was 384 μm, which was smaller than that of a similar commercial AI nozzle. AI nozzle design, manufacturing and performance evaluation technology that satisfies the requirements of agricultural control UAVs, was established through this study.

The downwash flow produced by agricultural drones has a great influence on the coverage ratio and the drift potential of pesticide spray droplets. Therefore, the configuration of the boom and the position of the nozzle of the pesticide injection system should be adjusted on the basis of the characteristics of the downwash flow. However, although many studies have been conducted, few studies have quantitatively investigated the characteristics of downwash flow. In this study, the average characteristics and turbulence of the downwash flow formed by a single blade were quantitatively evaluated. The single rotor blade used in the test had a radius of 370 mm, and this length was used to normalize the measurement positions. Downwash flow was measured at 400 mm × 400 mm at 10-mm intervals in the X-Y plane and for 6 measurement planes at 100-mm intervals along the Z-direction. The rotational speed of the blade was set to 2000, 2500, and 3000 rpm, and the corresponding blade tip velocities were 71.17 m/s, 88.97 m/s, and 106.76 m/s, respectively; these values were used to normalize the mean and turbulent velocity components. The velocity of downwash flow was measured using a constant temperature anemometer (CTA)-type hot-wire anemometry with an X-type probe, and data were collected at a sampling rate of 30 kHz for analysis of the turbulence characteristics. From this experimental study, the axial, radial, and tangential velocity components of the downwash flow, based on the maximum value, were 20%, 4.8%, and 5.9% of the blade tip velocity (VBtip), respectively. In addition, the turbulence intensity of the axial, radial, and tangential velocity components was 8.5%, 3.0%, and 4.5%, respectively, based on the maximum value, and the axial component was approximately twice as high as the other two velocity components. High turbulent intensity appeared near the shear flow region at high axial velocities. The downwash flow generated by a single rotor blade showed a steep velocity gradient with the blade length and axial distance, and the turbulent intensity was high in the shear layer region of the mean flow field.

Delivering pesticide droplets accurately to a target has always been a challenge for crop spraying. Pesticide spray that drifts or runs-off the crop are major sources of soil and groundwater pollution and encourage pesticide overuse. This study optimised an agricultural air-induction nozzle to overcome these difficulties. Various configurations were designed and manufactured to investigate the geometrical parameters. A range of experiments were designed and carried out to simulate field conditions and examine spray structure, stability, droplet size range, and the probability of microbubbles to determine correlations between droplet size and spray drift and droplet rebound potential with or without entrained microbubbles. The performance of the designed nozzle was compared to that of commercial nozzles. Optical diagnostic methods, including high-speed photography, laser diffraction-based droplet sizing, and microscopic flow visualisation, were employed to perform accurate investigations of droplet size range and microbubble presence potential. In addition, the spatial distribution of spray influenced by lateral wind was investigated in an open-type wind tunnel and measured using a 2-dimensional patternator and water-sensitive papers. The rebound potential of the droplets was investigated using high-speed photography for artificial leaves. The results demonstrate the significance of geometrical design factors on the performance of nozzles and the effectiveness of induced air on the reduction of drift and rebound potential. Droplets including microbubbles were found to distribute across the surface of the target leaves on impact and exhibit increased rebound resistance.

In this study, the atomization characteristics and drift potential of injection nozzles used in the pesticide injection system of agricultural drones currently used in Korea are evaluated. Furthermore, technical methods to reduce drift potential are determined. To this end, atomization characteristics were evaluated by selecting four representative nozzles commonly used in domestic agricultural drones. Additionally, an experimental device, consisting of a wind tunnel, was constructed to simulate the field situation. Moreover, drift potential was evaluated by using a water-sensitive paper under side wind conditions. The VMD and RSF of the nozzles used in the test were shown high in the order of TX–XR–TP, and the number density was low in in the order of TX–TP–XR. Thus, the evaluation of the droplet drift potential with respect to the side wind revealed that large amount of droplet drift occurs due to the side wind of 1 m/s, and the droplet drift of all nozzles used in the experiment, with the exception of the AI nozzle, was high. When the nozzle was installed obliquely, considering the flight speed and flight angle of the drone, it was confirmed that the tilt angle of the nozzle installation affects drift reduction. This applies even to nozzles that produce small droplets of less than 200 μm. Furthermore, as the speed of the side wind decreases, the drift reduction effect increases. Given that the drift potential of XR and TP nozzles, which are currently most commonly used in agricultural drones, are evaluated to be weak, auxiliary drift reduction methods, such as nozzle tilt angle, should be actively considered to reduce drift potential and minimize environmental damage.

This study aims to verify that the characteristics of the typical injection pumps and nozzles used in pesticide injection systems in current agricultural drones in Korea are consistent with those presented in the product specifications, and to provide experimental quantitative data for selecting the correct pump and nozzle. The performances of three types of pumps and 18 types of nozzles currently in use were evaluated in terms of the pressure-flow rate curve, injection flow rate, spray angle, and droplet size. For pesticide injection pumps, the maximum pressure and pressure-flow rate curve should include the nozzle’s injection pressure and flow rate range. Most of the 18 nozzles used in the test showed nearly the same results as the flow rates suggested from the manufacturer, but the spray angle showed a difference of up to 10%. The droplet size was slightly smaller than the value suggested by the manufacturer, and the relative span factor ranged from 0.2 to 1.2. The pressure-flow rate curves of the injection pumps and spray angles of the commercial nozzles used for agricultural control drones must be evaluated for official approval/assessment of such agricultural drones to ensure the performance of agricultural drone sprayers.

To expand the availability of intergeneric allopolyploids between Brassica rapa and Raphanus sativus beyond BB#1, a stable xBrassicoraphanus koranhort (baemoochae) cultivar (2n = 38, aAARR genome), we developed four intergeneric hybrids between different materials from B. rapa and R. sativus. These hybrids produced neither self-pollinated seeds nor embryos in microspore culture. The hybrids, however, did produce seeds (F1F1) via cross-pollination with existing baemoochae and mooyangchae, another xBrassicoraphanus line (2n = 36, rCCRR genome) generated from a cross between R. sativus and B. oleracea at Huazhong Agriculture University, China. The hybrid plants (F1F1) produced more seeds than the previous generation in both self- and cross-pollination and embryos, even in the presence of an induced microspore mutation. The self-sterile, cross-fertile properties of the newly synthesized allopolyploids suggest possible mechanisms for fertility restoration and provide valuable information for the development of intergeneric baemoochae cultivars.

Maize is the second-most produced crop in the Korean peninsula and has been continuously cultivated since the middle of the 16th century, when it was originally introduced from China. Even with this extensive cultivation history, the diversity and properties of Korean landraces have not been investigated at the nucleotide sequence level. We collected 12 landraces with various flowering times and performed RNA-seq in the early vegetative stage. The transcriptomes of 12 Korean landraces have been analyzed for their genetic variations in coding sequence and genetic relationships to other maize germplasm. The Korean landraces showed specific genetic characteristics and were closely related to a Chinese inbred line. Flowering-time related gene profiles pointed to multiple causes for the variation of flowering time within Korean landraces; the profiles revealed significant positive and negative correlations among genes, allowing us to infer possible mechanisms for flowering time variation in maize. Our results demonstrate the value of transcriptome-based genetic and gene expression profiles for information on possible breeding resources, which is particularly needed in Korean waxy landraces.

Hybridization and polyploidization are pivotal to plant evolution. Genetic crosses between distantly related species rarely occur in nature mainly due to reproductive barriers but how such hurdles can be overcome is largely unknown. xBrassicoraphanus is a fertile intergeneric allopolyploid synthesized between Brassica rapa and Raphanus sativus in the Brassicaceae family. Genomes of B. rapa and R. sativus are diverged enough to suppress synapsis formation between non-homologous progenitor chromosomes during meiosis, and we found that both genomes reside in the single nucleus of xBrassicoraphanus without genome loss or rearrangement. Expressions of syntenic orthologs identified in B. rapa and R. sativus were adjusted to a hybrid nuclear environment of xBrassicoraphanus, which necessitates reconfiguration of transcription network by rewiring cis-trans interactions. B. rapa coding sequences have a higher level of gene-body methylation than R. sativus, and such methylation asymmetry is maintained in xBrassicoraphanus. B. rapa-originated transposable elements were transcriptionally silenced in xBrassicoraphanus, rendered by gain of CHG methylation in trans via small RNAs derived from the same sequences of R. sativus subgenome. Our work proposes that not only transcription compatibility but also a certain extent of genome divergence supports hybrid genome stabilization, which may explain great diversification and expansion of angiosperms during evolution.

Background Hybridization and polyploidization events are important driving forces in plant evolution. Allopolyploids formed between different species can be naturally or artificially created but often suffer from genetic instability and infertility in successive generations. xBrassicoraphanus is an intergeneric allopolyploid obtained from a cross between Brassica rapa and Raphanus sativus, providing a useful resource for genetic and genomic study in hybrid species. Objective The current study aims to understand the cause of hybrid sterility and pollen abnormality in different lines of synthetic xBrassicoraphanus from the cytogenetic perspective. Methods Alexander staining was used to assess the pollen viability. Cytogenetic analysis was employed to monitor meiotic chromosome behaviors in pollen mother cells (PMCs). Origins of parental chromosomes in xBrassicoraphanus meiocytes were determined by genome in situ hybridization analysis. Results The xBrassicoraphanus lines BB#4 and BB#6 showed high rates of seed abortion and pollen deformation. Abnormal chromosome behaviors were observed in their PMCs, frequently forming univalents and inter-chromosomal bridges during meiosis. A positive correlation also exists between meiotic defects and the formation of micronuclei, which is conceivably responsible for unbalanced gamete production and pollen sterility. Conclusion These results suggest that unequal segregation of meiotic chromosomes, due in part to non-homologous interactions, is responsible for micronuclei and unbalanced gamete formation, eventually leading to pollen degeneration and inferior fertility in unstable xBrassicoraphanus lines.

Recently, agricultural drones have been widely used for precise agricultural control. In the case of drone control, improved coverage and reduced drift potential of chemical sprays are of major concern, and this is greatly influenced by the downwash flow characteristics formed by the rotor blades. In this study, the mean and turbulent flow characteristics of the downwash flow generated by a single blade of a four-sided agricultural control drone were quantitatively evaluated. The blade radius used to generate the downwash flow was 370 mm, and the measurement position was normalized using this length. In addition, the rotational speed of the blade was 3000 rpm, and the velocity components were dimensionlessly expressed using the blade tip velocity (VBtip) corresponding to this rotational speed. The velocity of downwash flow was measured using CTA-type hot-wire anemometry with an X-type probe, and data were collected at a sampling rate of 30 kHz for turbulence characteristics analysis. The mean velocity, vorticity distribution, turbulence intensity, and Reynolds stress of the fluctuation velocity were quantitatively measured. From extensive experimental works, it was revealed that a high axial velocity is formed at a specific position (r/Lb = 0.4–0.8) along the blade length. The radial velocity shows an asymmetric distribution in the plane close to the blade, and the tangential velocity is higher in the central part of the downwash flow than in the region of a high axial and negative radial velocity. An asymmetric spiral rotational flow with low axial velocity and low-pressure distribution exists inside the downwash flow due to the shear flow, and the influence of the driving motor almost disappears at the axial position (Z/Lb ∼ 1). The averaged mean value of the axial, radial, and tangential velocity components measured at six axial planes and normalized by blade tip velocity (VBtip) is composed of the ratio of the axial velocity component of 12.8%, the radial velocity component of 0.19%, and the tangential velocity component of 1.3%. The maximum values of the turbulence intensity of the axial, radial, and tangential velocity components were estimated as 6.8%, 3.0%, and 4.3%, respectively.

본 연구는 타인에 대한 조망수용 능력과 공감 능력을 활용한 배려증진 집단상담 프로그램이 초기 청소년의 배려심과 또래관계기술 향상에 효과가 있는지 검증하는 것을 목적으로 하였다. 이러한 연구 목적을 위하여 서울 소재 J초등학교 4학년 학생을 실험집단(22명)과 통제집단(22명)에 배정하였다. 실험 및 통제집단의 학생 모두에게 배려심, 또래관계기술 척도 검사를 사전, 사후로 실시하였으며, 실험집단에는 배려증진 집단상담 프로그램을 총 8회기 실시하였다. 본 연구의 결과는 다음과 같다. 첫째, 배려증진 집단상담 프로그램에 참여한 집단은 통제집단에 비해 배려심 척도의 하위 요인인 타인 심정 고려, 양보심, 염려 모두 향상되었다. 둘째, 배려증진 집단상담 프로그램에 참여한 학생은 통제집단에 비해 또래관계기술의 하위요인 중 협동과 공감에서 유의미한 향상이 나타났다. 본 연구는 조망수용 능력과 공감 능력을 바탕으로 배려심과 또래관계기술 함양이 매우 필요한 초기 청소년을 대상으로 배려증진을 위한 집단상담 프로그램을 실시하여 그 효과를 검증하였다는 점에서 의의가 있다. 또한 본 연구결과를 토대로 상담 실제를 위한 시사점과 후속연구에 대한 제언을 논의하였다.

Root skin color is one of the economically important traits in radish (Raphanus sativus), and the pigmentation in red skin varieties is largely attributable to anthocyanin accumulation. Pelargonidin was found as a major anthocyanin pigment accumulated in the sub-epidermal layer of red radish roots. In the 20 F2 population generated from the F1 with red root skins, root skins with red and white colors segregated in a 3:1 ratio. Additionally, a test cross between a red F3 individual and a white skin individual gave rise to 1:1 segregation of red and white, indicating that the root skin color of radish is determined by a single locus and red color is dominant over white. We performed association mapping for root skin color using SNPs obtained from RNA-seq analysis. Segregation analysis on the 152 F3 test-cross population revealed an RsMyb1 transcription factor as a candidate gene to determine root skin color. A PCR marker based on the polymorphism within 2 kb of RsMyb1 was developed and tested on 12 and 152 individuals from F2 and F3 test cross populations, respectively, and red and white root skin colors were completely distinguished corresponding to the genotypes. Expression levels of RsMyb1 in red or purple root cultivars were significantly higher than in white root cultivars. These findings suggest that RsMyb1 is a crucial determinant for anthocyanin biosynthesis in radish roots, and the molecular marker developed in this study will be useful for marker-assisted selection for red skin individuals at early seedling stages.

Path planning is an essential part for autonomous mower tractor to travel and mow. Objectives of the paper were to analyze operation patterns by a farmer, to extract and optimize waypoints, and to demonstrate generation of formatted planned path for autonomous mower tractors. An 18-kW mid-mower tractor was operated by a skilled farmer on grass fields. To measure tractor travel and operation characteristics, an RTK-GPS antenna with a 2-cm RMS error, an inertia motion sensing unit, a gyro compass, a wheel angle sensor, and a mower on/off sensor were mounted on the mower tractor, and all the data were collected at a 10-Hz rate. And all of sensor data were transferred through a program to show the status immediately on the notebook. From 3 grass field tests, total 53,412 data points (every 0.1s) were obtained, and amount the data 73% was straight steering, 22% was turning steering, and 5% was for others (e.g. artificial error, needless work). Field test data showed some overlap, especially in the turning areas. Based on the human operation patterns, path planning algorithm was suggested for autonomous mower tractor. Finally path generation was demonstrated in a formatted file and graphic display. Results of the study would be useful to implement and test autonomous mower tractor, but further research needs to be done to improve the performance.

Purpose: The net rind pattern and color of melon surface are important for a high market value of melon fruits. The development of the net and color are closely related to the changes in shape, size, and maturing. Therefore, the net and color characteristics can be used indicators for assessment of melon quality. The goal of this study was to investigate the possibility of estimating melon soluble solids content (SSC) and firmness by analyzing the net and color characteristics of fruit surface. Methods: The true color images of melon surface obtained at fruit equator were analyzed with 18 color features and 9 texture features. The partial least squares (PLS) method was used to estimate SSC and firmness in melons using their color and texture features. Results: In sensing melon SSC, the coefficients of determination of validation (Rv 2) of the prediction models using the color and texture features were 0.84 (root mean square error of validation, RMSEV: 1.92 °Brix) and 0.96 (RMSEV: 0.60 °Brix), respectively. The Rv 2 values of the models for predicting melon firmness using the color and texture features were 0.64 (RMSEV: 4.62 N) and 0.79 (RMSEV: 2.99 N), respectively. Conclusions: In general, the texture features were more useful for estimating melon internal quality than the color features. However, to strengthen the usefulness of the color and texture features of melon surface for estimation of melon quality, additional experiments with more fruit samples need to be conducted.

th , 2012; Revised: June 27 th , 2012; Accepted: June 29 th , 2012 Purpose: In near infrared spectroscopy, interactance configuration of a light source and a spectrometer probe can provide more information regarding fruit internal attributes, compared to reflectance and transmittance configuration. However, there is no through study on the parameters of interactance measurement setup. The objective of this study was to investigate the effect of the parameters on the estimation of soluble solids content (SSC) and firmness of muskmelons. Methods: Melon samples were taken from greenhouses at three different harvesting seasons. The prediction models were developed at three distances of 2, 5, and 8 cm between the light source and the spectrometer probe, three measurement points of 2, 3, and 6 evenly distributed on each sample, and different number of fruit samples for calibration models. The performance of the models was compared. Results: In the test at the three distances, the best results were foun d at a 5 cm distance. The coefficient of determination (Rcv 2 ) values of the cross-validation were 0.717 (standard error of prediction, SEP=1.16 °Brix) and 0.504 (SEP=4.31 N) for the estimation of SSC and firmness, respectively. The minimum measurement point required to fully represent the spectral characteristics of each fruit sample was 3. The highest Rcv 2 values were 0.736 (SEP=0.87 °Brix) and 0.644 (SEP=4.16 N) for the estimation of SSC and firmness, respectively. The performance of the models began to be saturated when 60 fruit samples were used for developing calibration models. The highest Rcv 2 of 0.713 (SEP=0.88 °Brix) and 0.750 (SEP=3.30 N) for the estimation of SSC and firmness, respectively, were achieved. Conclusions: The performance of the prediction models was quite different according to the condition of interactance measurement setup. In designing a fruit grading machine with interactance configuration, the parameters for interactance measurement setup should be chosen carefully.

th , 2012; Revised: June 27 th , 2012; Accepted: June 29 th , 2012 Purpose: This study was conducted to investigate the potential of interactance mode of NIR spectroscopy technology for the estimation of soluble solids content (SSC) and firmness of muskmelons. Methods: Melon samples were taken from local greenhouses in three different harvesting seasons (experiments 1, 2, and 3). The fruit attributes were measured at the 6 points on an equator of each sample where the spectral data were collected. The prediction models were developed using the original spectral data and the spectral data sets preproces sed by 20 methods. The performance of the models was compared. Results: In the prediction of SSC, the highest coefficient of determination (Rcv 2 ) values of the cross-validation was 0.755 (standard error of prediction, SEP=0.89°Brix) with the preprocessing of normalization with range in experiment 1. The highest coefficient of determination in the robustness tests, Rrt 2 =0.650 (SEP=1.03 °Brix), was found when the best model of experiment 3 was evaluated with the data set of experiment 2. The best Rcv 2 for the prediction of firmness was 0.715 (SEP=3.63 N) when no preprocessing was applied in experiment 1. The highest Rrt 2 was 0.404 (SEP=5.30 N) when the best model of experiment 3 was applied to the data set of experiment 1. Conclusions: From the test results, it can be concluded that the interactance mode of VIS/NIR spectroscopy te chnology has a great potential to measure SSC and firmness of thick-skinned muskmelons.

The overall goal of this study was to examine the feasibility of predicting firmness of pear fruit by analyzing laser-induced light backscattering images. Thirty-five image analysis characteristics extracted from the laser-induced light backscattering images were used to build partial least squares regression (PLSR) models for predicting firmness of pear fruit. Experiments were conducted with three sets of pear samples which were in same “Shingo” cultivar, harvested in a same season, but produced in different counties. In every experiments with fruit samples produced in a same county, the correlation coefficients of prediction (rp) and root mean square errors of prediction (RMSEP) of the models were 0.550~0.761 and 4.039~6.154 N, respectively. In an experiment with mixed fruit samples produced in different counties, the rp and RMSEP of the model were 0.669 and 5.02 N, respectively. The experiment results indicate that the analysis of laser-induced light backscattering images could be a useful tool for predicting firmness of pear fruit nondestructively.

Three modes of VIS/NIR spectroscopic measurement (interactance and two modes of transmission) were compared for their ability to estimate soluble solids content (SSC) of ‘Shingo’ pear non-destructively. The two transmission modes are named as full- and semi-transmission, where full-transmission stands for passing of light through abdomen of pear and semi-transmission is for transit of light mainly through flesh of pear. For comparison of the modes, prediction models developed from the collected spectroscopic data by the three modes were developed and tested for comparison of their performance. Partial least square regression (PSLR) was used to develop the models and various pre-processing methods were applied to develop models of high accuracy. The experiment was repeated three times with pears produced in different regions. The experiments resulted that selection of pre-processing is very important to attain accurate models, and multiplicative scatter correction (MSC) was selected as a pre-processor of high accuracy for the three modes of spectroscopic measurement in every experiment. Except for MSC, different group of pre-processing methods were selected for the three modes of measurement in every experiment without any tendency to the tested modes of measurement and pears of different produced region. Root-mean-square error of prediction (RMSEP) of prediction models of the three modes of measurement using prepreocessor of MSC were compared for their ability to estimate SSC. The models resulted in ranges of 0.37~0.57°Brix, 0.65~0.72°Brix, 0.39~0.51°Brix for interactance, full- and semi-transmission, respectively. As shown, modes of semi-transmission and interactance resulted about the same level of prediction accuracy and were noted as modes of high performance to predict SSC.