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Fragrant pears have been one of the most favorite types in pear industry. However, manual picking cannot fully meet the demands of large-scale production, due to the labor intensity. Mechanical picking has the potential to significantly reduce the labor demands for the high productivity. Among them, the visual recognition has been one of the most key elements among the various picking robots. The complex orchard environment with the variable lighting, weather conditions, foliage obstructions and fruit overlap has also posed the significant challenges on both conventional image processing and machine learning-based object detection, thereby impeding the accurate identification of fragrant pears. This study aims to improve the accuracy and detection speeds in such unstructured settings. An optimized YOLOv8n-based object detection was introduced to specifically identify the fragrant pear. A dataset was also comprised of 4 500 images of fragrant pears. A variety of conditions were considered using image collection and data augmentation, such as different lighting and foliage obstructions within orchard environments. The Min-Max normalization was employed to consider the fragrant pear harvesting. A comprehensive evaluation was conducted on five lightweight YOLO versions: YOLOv3-tiny, YOLOv5n, YOLO6n, YOLOv7-tiny, and YOLOv8n. Different weights were assigned to optimize the model selection, in terms of the mAP, precision, recall, inference time, parameters and model size. The network structure was streamlined for the object detection of fragrant pear with YOLOv8n as the baseline. Four key areas were focused to optimize the model. Initially, the network backbone was redesigned to promote the network inference speed. The impact of the C2f structure on speed was assessed to replace the certain redundant C2f components. Subsequently, an effective PConv module was integrated into the detection head of network, in order to better recognize the obscured images. A weight-sharing strategy was also coupled with the detection head parameters to reduce the parameters. Additionally, the combination of simSPPF and Inner IoU was further augmented the inference speed and bounding box regression performance. Comparative trials were then conducted on the object detection of fragrant pear. The results revealed that the superior comprehensive performance was achieved in the YOLOv8n. A higher weighted score of 83.4% was obtained after the Min-Max normalization, compared with the YOLOv3-tiny, YOLOv5n, YOLOv6n, and YOLOv7-tiny. Thus, the baseline network was selected for the subsequent research. Optimization experiments were carried out with C2f structures. The replacement of C2f was identified in the 15th and 2nd layers of the network with Conv and Conv_Res modules, in order to enhance the computational efficiency. The optimization scheme was determined for the backbone network. Ablation experiments were conducted to verify the efficacy of the various improved modules. The refined YOLOv8n was achieved the superior accuracy and detection speed on the fragrant pear dataset, with a 0.4 and 0.5 percentage point increase in the F0.5 score and mean average precision, respectively, compared with the original YOLOv8n model. Detection speeds on GPU and CPU devices increased by 34.0% and 24.4%, respectively, indicating the rates of 99.4 and 15.3 frames per second, respectively. This high-precision and rapid detection can provide the valuable technical support to the real-time detection of fragrant pears in natural orchard environments. The improved model can also be expected to deploy into the fragrant pear picking robots. [ABSTRACT FROM AUTHOR]

【Objective】By comparing the quality of ‘Cuiguan’ pear fruits under five different bag treatments, from which the bag that can improve the appearance quality of fruits and has less impact on the internal quality of the fruits was selected, with an aim to provide a basis for screening of bag types in the production of ‘Cuiguan’.【Method】Five different bags were selected for bagging treatments of the ‘Cuiguan’ pear fruits, taking fruits without bagging as control, and the impacts of five different bagging treatments on the quality of ‘Cuiguan’ pear fruits were clarified.【Result】The results showed that the effects of five different bagging treatments on the single fruit weight, transverse diameter, longitudinal diameter, fruit shape index, hardness, pericarp L* value, pericarp b* value, soluble solids content, soluble sugar content of ‘Cuiguan’ pear fruits were relatively small and their coefficients of variation were below 10%. However, bagging could reduce soluble solids content and soluble sugar content by 21.9% and 23.9%, respectively, which had negative effects on the internal quality of the pear fruits. Compared with the control, the chlorophyll content of ‘Cuiguan’ pear fruit after bagging decreased by 73.6%, and the greenness of the inner part of fruit reduced, leading to a lighter color of the fruit surface; the color difference L * value rose by 20. 6% and it significantly improved the brightness and fineness of the fruit surface, which increased its appearance quality and commercial value. Bagging had an impact on the contents of aroma substances in the pericarp of ‘Cuiguan’ pears, and the contents of α-farnesene, hexanal and ethyl acetate in the pericarp increased, and the content of 2-hexenal reduced, making the aroma more intense.【Conclusion】The principal component analysis and comprehensive analysis show that, the double-layer paper bag with yellow outside and white inside can increase the pericarp L * value and pericarp a * value ‘Cuiguan’ pear, further enhance the fineness of the fruit surface, improve the appearance quality of Cuiguan pear fruits, with higher comprehensive ranking, which can enhance the appearance quality of the fruits while minimize the negative impacts of bagging on the internal quality at the same time. [ABSTRACT FROM AUTHOR]

In order to explore the prediction model of the initial flowering period of fragrant pears in Xinjiang, and identify the most suitable flower viewing day of fragrant pears during the flowering period, the meteorological elements and the daily sequences of the initial flowering period of fragrant pears production areas in Aksu, Alar, Luntai and Korla of Xinjiang from 1990 to 2020 were analyzed by the stepwise regression method, and the prediction model of the meteorological index of fragrant pears main production areas in Korla of Xinjiang was established in combination with the human comfort index, which was expected to provide reference for Xinjiang Tourism meteorological service. The results showed that: (1) the composition factors of the prediction model for the initial flowering period of Korla fragrant pear in Xinjiang were the average maximum temperature in March, the soil temperature in depth of 0cm in March, the average temperature in March, and the soil temperature in depth of 40cm in March. There was a linear relationship (negative correlation) between the diurnal sequence and the air temperature at the beginning of flowering in Alar and Korla, and a linear relationship (multiple correlation) between the soil temperature and air temperature in Aksu and Luntai. The probability of model error within 3 days in normal years was 93.5% in Alar, 93.5% in Aksu, 100% in Korla and 96.8% in Luntai. (2) The optimized human comfort index was divided into four levels: the most suitable, sub-suitable, general and unsuitable. The most suitable days for the optimized human comfort index were 22 days in Alar, 24 days in Aksu, 16 days in Korla and 18 days in Luntai before and after the flowering period in 2022. (3) The meteorological index of fragrant pear flower appreciation takes the intersection of the suitable flowering period and the human comfort index, and was divided into four grades: the most suitable (five-star recommended index), sub-suitable (four-star recommended index), general (three-star recommended index) and unsuitable (one-star recommended index). In 2022, the five-star recommended flower viewing days were from April 11 to April 14 in Aksu, from April 10 to April 15 in Alar, from April 10 to April 15 in Korla, and from April 11 to April 14 in Luntai, respectively. The simulation results were in line with the reality. The meteorological index of fragrant pear flower appreciation, combined with the body temperature and the flowering period, had good application value and potential in the follow-up prediction of fragrant pear initial flowering period and the tourism meteorological service in Xinjiang. [ABSTRACT FROM AUTHOR]

It is important to judge the density of pear flower accurately for automatic thinning. In order to judge the density of pear flowers precisely and achieve the purpose of automatic flower thinning, a density classification of pear flower images method based on improved density peak clustering algorithm was proposed in this study. The pear flower image samples used in the experiment were taken from the research base of Hebei Agricultural University, Niugang Village, Yi County, Baoding City, Hebei Province, and the variety was three-year-old Qiuyue. In this study, the images of pear flowers in natural environment were collected on April 18, 2021, when the pear flowers were in full bloom. The pear flower recognition images with high detection accuracy were obtained by using the depth learning model to detect the pear flower. The central coordinates of the target detection frame were extracted from the recognition images to obtain the data points that needed to be clustered. Secondly, in order to achieve the density classification of pear flower images, the method of selecting the cluster center was improved according to the shortcomings of the original density peak clustering algorithm in the density classification of pear flower and the requirements of pear flower density classification. The decision graph was divided into four parts by four groups of local density and center offset distance segmentation thresholds to select the cluster centers. These four parts corresponded to four grades of high, medium and low density and no thinning treatment. The accurate classification of pear flower images with reasonable density was realized. Finally, to solve the problem of inaccurate clustering classification of pear flower distribution with only cluster distribution, sparse distribution and large-scale close-up, the calculation method of dij parameter of distance between two points was improved. The pear flower scale and density grading standard were unified, and reasonable density grading could be achieved for all distribution types of pear flower images. The experimental results showed that the proposed algorithm could adapt to pear flower images of different scales. The accuracy of scale prediction was 94.89%, and the accuracy of density classification was 94.29%. Compared with the existing methods, the proposed method could achieve the density classification of local flower clusters in natural environment. the algorithm in this paper was compared with K-means algorithm and DBSCAN algorithm, and the accuracy of density classification was 94.29% and 68.57% respectively. Although the density classification accuracy of K-Means clustering algorithm was high, it lacked the algorithm steps to automatically select the clustering centers of different density classification, and was too sensitive to noise points. The density calculation method of DBSCAN algorithm lacked continuity, and the division of density grade was not precise enough. Based on the comprehensive analysis of density classification accuracy and cluster center selection method, the improved density peak clustering algorithm in this paper had the best effect. The clustering centers of different density grade could be automatically selected and the error of random initialization of clustering centers could be reduced. The proposed algorithm was robust to noise points and could eliminate noise points effectively. The proposed algorithm adopted soft statistics method for density calculation, which had continuity and was more accurate for density classification. It provides technical support for analyzing the density of pear flower and machine intelligent flower thinning. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the effects of duck manure application on soil environmental quality and pear quality and to promote the scientific application of duck manure to partially replace chemical fertilizers in pear planting. Under the condition of equal nitrogen substitution, the duck manure alternative fertilizer program in this study was divided into five groups including the control group (CK), 30% (DM1), 40% (DM2), 50% (DM3), and 60% (DM4). The duck manure was applied to the pear tree soil in April and July. Soil and pear samples were collected in October. The soil environmental quality (soil pH, soil nutrients, heavy metals, antibiotics) and pear quality parameters (soluble solids, soluble sugars, vitamin C) were also analyzed. The results showed that all the duck manure replacement treatments (DM1-DM4) could significantly increase the soil pH (6%-21%) compared with the control group, and the organic matter of deeper soil (40-60cm) was improved. The most significant effect on increasing the content of available phosphorus and available potassium in the soil was also found in the DM3 group. Fortunately, the contents of heavy metals in different soil layers of each treatment fully meet the requirements of pollution-free and green food producing areas for soil environment. The results also indicated that the application of duck manure improved the pear quality, and the soluble solids, soluble sugars, and vitamin C of pear were increased by 5.21%-17.44%, 2.50%-8.45%, and 0.39%-11.01%, respectively. The results showed that 30% duck manure replacing had the best effect on improving pear quality, while 50% duck manure replacing had the best effect on improving soil environment quality. [ABSTRACT FROM AUTHOR]

【Objective】 This paper aimed to study the pathogen and biological characteristics of three leaf diseases of Amomum tsaoko Crevost et Lemarie in Yunnan province, and to provide theoretical basis for the control of leaf spot of A.tsaoko. 【Method】Three fungal diseases were discovered from A.tsaoko plantation in Nujiang Prefecture, Yunnan province. Three strains, including CG-N01, CG-N02 and CG-N03 were obtained by single spore culture, their pathogenicity was determined, spore morphology was observed according to morphological characteristics, and pathogen was identified by phylogenetic tree constructed by multi-gene sequence analysis (rDNA-ITS, tub2, LSU and tef-1 α), and biological characteristics were determined. 【Result】 The morphological characteristics of CG-N01, CG-N02 and CG-N03 were in accordance with the typical characters of Pyrus costina, Phoma matteuccola and Colletotrichum mondsii, respectively. The rDNA-ITS, LSU and tef-1 α sequences of CG-N01 were 489, 901 and 475 bp, respectively ( the login numbers were MN596209, MN689811 and MN696687, respectively) ; The rDNA-ITS, LSU and tef-1 α sequences of the strain CG-N02 were 517, 997 and 529 bp respectively (the login numbers were MN596212, MN650644 and MN696686, respectively) ; The rDNA-ITS, tub2 and tef-1 α sequences of strain CG-N03 were 560, 926 and 738 bp, respectively ( the login numbers were MN596210, MN650645 and MN696688, respectively). Purified strains of CG-N01, CG-N02 and CG-N03 had high homology with P. costina, P. matteuccola and C. simmondsii, respectively. Biological determination showed that strain CG-N01 was advantageous to mycelium growth and conidia formation under the conditions of 28 ℃, alternating light and dark, and pH 6.0. Strains CG-N02 and CG-N03 were favorable for sporulation at 25 ℃, alternating light and darkness, and pH 8.0. 【Conclusion】 This study first reported that C. simmondsii can infect and cause Colletotrichum gloeosporioides, the biological characteristics of the pathogens of leaf spot, leaf blast and anthracnose were determined to provide scientific basis and theory support for the diversity study and effective control of the disease. [ABSTRACT FROM AUTHOR]

The study was to compare the nutritional value and rumen fermentation parameters of four unconventional feedstuffs for ruminant. The nutrient composition analysis and in vitro fermentation method were used to evaluate the nutritional value and rumen fermentation indexes of four unconventional feedstuffs including sorghum straw, reed grass, date powder and pear residue. The results showed that the disappearance rate of dry matter (DM) of date powder was extremely higher than that of other feeds in vitro (P<0.01). The rumen disappearance rate of crude protein (CP) of pear pomace was extremely higher than that of other feeds in vitro (P<0.01). The disappearance rate of all nutrients in reed grass were extremely lower than that of other feeds in vitro (P<0.01). The 48 h gas production and gas production rate of slow degradation fraction (c) for date powder was extremely higher than that of other feeds (P<0.01), while that of reed grass was extremely lower than that of other feeds (P<0.01). Compared with oat grass, the content of total volatile fatty acid (TVFA) of date powder and pear pomace was significantly increased (P<0.05), and pH value was significantly decreased (P<0.05). The experiment indicates that the nutritive and usable value of jujube powder and pear residue are better. The nutrient composition of sorghum straw is similar to that of oat grass, but the degree of fiber decomposition is lower than that of oat grass, so it can be processed to improve its utilization. The feedable value of reed is low. [ABSTRACT FROM AUTHOR]

[Objectives]In order to quickly add or replace the protein tag of the target gene, we established the multi-tag recombination ligase method, which could be applied as a useful tool in exploring gene functions. [Methods]Utilizing homologous recombinase reaction, the target gene and protein tag along wit digested vector were simultaneously connected, and the rapid protein tag addition or replacement of the target gene was subsequently accomplished. [Results]The multi-tag recombinant ligase method had certain advantages over the fusion PCR method and T4 DNA ligase method in terms of time and steps. S7-RNase in pear was applied as the target gene for assay certification. Utilizing the homologous recombinase reaction, the S7-RNase and GFP protein tags were successfully linked and constructed on the pCold-TF vector. At temperature of 15 ℃,the recombinant plasmid S7-RNase-GFP-pCold-TF was prokaryotically expressed and the recombinant protein was successfully expressed when the final concentration of IPTG was 0.5 mmol·L-1. Simultaneously, the GFP protein tag in the p1300-35S-GFP vector was successfully replaced with the mCherry protein tag, and the recombinant plasmid p1300-35S-S7-RNase-mCherry was successfully expressed in tobacco cells. [Conclusions]Multi-tag recombination ligase method is fast, simple and efficient, and it is suitable for constructing a variety of multiple protein tags or replacing a certain protein tag expression vector, so this method is a reliable and efficient new method to obtain the protein tags required by the target gene. [ABSTRACT FROM AUTHOR]

Firmness is one of the important indicators for the internal quality of fruits. Natural frequency has widely been expected to evaluate the fruit firmness in recent years. Several indices have successfully been applied for the firmness of sphere-shaped fruits using the natural frequency and fruit mass. However, the fruit with non-spherical or irregular shapes cannot be suitable for firmness evaluation, due mainly to the fact that the fruit shape can interfere with the resonance frequency. Thus, some dual-frequency indices were established to measure the firmness of fruit with ellipsoidal shapes. Nevertheless, these indices cannot accurately evaluate the firmness of complex and irregular pears. In this study, a Fourier descriptor was established as a reliable shape descriptor to evaluate the firmness, thereby representing complex, irregular, or a larger variation of pear shapes. Firstly, the shape images of pears were captured by a camera. Then, the boundary edges of pear images were extracted to calculate the normalized radiuses. After that, a Fourier transform was performed on the normalized radius to obtain the Fourier descriptor. Finally, the first 15 Fourier descriptors were screened to describe the complex shapes of pears. Meanwhile, an experimental modal combined with the Finite Element Method (FEM) was utilized to analyze the effect of fruit shape on the natural frequency. Three modes included bending, compression, and breathing during a test. The natural frequency was easy to measure the equatorial region of the pear fruit in the compression mode. The largest deformation appeared, when the pear was impacted on this region. As such, the pear was assumed to be linearly elastic, homogeneous and isotropic material in the FEM. A process of reverse engineering was utilized to form the geometric model of pears. The 3D 4-node tetrahedral structural solid element was selected, allowing three translational and three rotational degrees of freedom at each node. Consequently, three shapes and natural frequencies in FE modal analysis were highly related to the experimental data. Therefore, the FEM model was expected to analyze the influence of Fourier descriptors on the natural frequency of the pear. These results indicated that the first Fourier descriptor (F1) had a significant effect on the natural frequencies of three modes. The frequency decreased linearly for the bending and compression mode, and increased linearly for the breathing mode, with the increasing of the F1. A new firmness index was established using the relationship between the F1 and frequency in the compression mode. Finally, an M-T penetration test was conducted to investigate the correlation between the nondestructive and destructive firmness indices. By comparison, the Coefficient of Determination (COD) was 0.892 for the new index SE(F1) with the destructive M-T firmness tester. Two dual-frequency firmness indices for the ellipsoidal fruit and firmness index SE(q), the COD were 0.733, 0.775, 0.765, and 0.746, respectively, for traditional spherical firmness index. Therefore, the new firmness index can accurately evaluate the firmness of complex and irregular shape pears. Consequently, this finding can provide promising practical guidance for the nondestructive detection of the firmness of differently shaped pears using resonance in intelligent agriculture. [ABSTRACT FROM AUTHOR]

Xinjiang Autonomous Region has been the main pear producing area in China, due to the unique climate conditions. The types and tastes of local pear cultivars have brought rich germplasm resources to maintain the genetic diversity of pear under the climatic changes and the evolving demand of a market. A Pyrussinkiangensisyü belonging to Pomaceae of Rosaceae is the major component of oriental pears. However, a simplex pear variety has become an increasingly prominent issue in recent years. In particular, Korla fragrant pear with relatively concentrated market time cannot meet the ever-increasing high demand for diversified pear variety. Therefore, it is necessary to breed local pear varieties with different maturity, diversified taste, and individualization for better sustainable development of characteristic forest and fruit industry in Xinjiang. In this study, a quality evaluation model was established for 8 types of local pear cultivars using factor analysis. Eight types of test materials included ‘Piqan red pear’, ‘Piqanjujula’, ‘Piqanpock marked yellow pear’, ‘late-maturing tax pear’, ‘Piqan early-maturing jujula’, ‘Nogay pear’, ‘Yaglik pear’, and ‘Kuqajujula’. 14 internal and external indexes of fruit quality were selected to determine the comprehensive quality score. The results showed that there were great differences in the variation coefficient of 14 fruit quality indexes in 8 types of local pear cultivars, where the maximum variation coefficient was the color difference value a* (red-green difference) of 225.40%. There were the medium variation coefficients of single fruit weight, fruit longitudinal diameter, fruit core weight, color difference value L*, fruit hardness, total acid content, and sugar-acid ratio, ranging from 20.0% to 45.0%. Furthermore, relatively small variation coefficients (<20.0%) were found in the rest of the fruit quality indexes. There were also different levels of correlation among the fruit quality indexes. Additionally, a factor analysis was utilized to extract four common factors with eigenvalues greater than 1, where the cumulative variance contribution rate was 88.90%. Specifically, the contribution rate of the first common factor was 31.15%, which was mainly determined by the fruit longitudinal diameter, single fruit weight, fruit core weight, fruit transverse diameter, and fruit shape index, indicating the fruit size, core size, and fruit shape. The contribution rate of the second common factor was 23.31%, which was determined by the sugar-acid ratio, fruit firmness, sugar content, and total acid content, indicating the taste quality and the strength of transportation. The third common factor accounted for 18.29%, which was determined by the color difference value L*, a*, and b*, representing the color difference level of the fruit surface. The contribution rate of the fourth common factor was 16.15%, which was determined by the edible rate and the length of the fruit stalk, reflecting the size of the edible part and the wind resistance of the fruit. An excellent level order of 8 local pear cultivars was achieved in the quality evaluation model: ‘Nogay pear’, ‘Yaglik pear’, ‘Kuqajujula’, ‘Piqanpock marked yellow pear’, ‘Piqanjujula’, ‘Piqan red pear’, ‘Piqan early-maturing jujula’, and ‘late-maturing tax pear’. The results provide reference for rational application and scientific popularization of local pear cultivars in Xinjiang. [ABSTRACT FROM AUTHOR]

[Objectives] The aim of this paper was to explore the physiological mechanism of gibberellin (GA) effects on delaying leaf abscission in ' Hosui' pear, which could provide reference for controlling the early leaf abscission in pear. [Methods] Taking the abscission zone from the petiole of 'Hosui ' pear with normal growth (control group) and early leaf abscission as materials, through paraffin section observation, the contents of gibberellins and reactive oxygen species and the activities of antioxidant enzymes were determined and their physiological differences were analyzed. At the same time, the effects of gibberellin on leaf retention, antioxidant enzyme activity and active oxygen content were detected by spraying plant growth regulators. [Results] Through the observation of paraffin section, it was found that the petiole abscission zone of ' Hosui' pear with early leaf abscission had obvious constriction, and the cells in the abcsission zone were smaller than the adjacent cells and had dense cytoplasm. Compared with the control group, in the petiole abscission zone of the early leaf abscission group, the contents of GA3 and GA4 with physiological activity and GA12, the key intermediate of gibberellin synthesis significantly decreased, the activities of superoxide dismutase, peroxidase and catalase significantly decreased, and the contents of superoxide anion and hydrogen peroxide significantly increased. Exogenous gibberellin spraying could increase the activity of antioxidant enzymes in the detached zone of petiole, reduce the content of reactive oxygen species and increase the retention rate of leaves. [Conclusions] The appropriate concentration of gibberellin can promote the activity of antioxidant enzymes, reduce the content of reactive oxygen species and delay the occurrence of leaf abscission. [ABSTRACT FROM AUTHOR]

[ Objective] The secondary flowering ( abnormal) of pears is common in southern China. The interaction between environmental factors and plant genetic factors in this process and the key genetic elements remain to be identified. The present paper aimed to identify SPL ( SQUAMOSA promoter- Binding protein like) gens in the genome of Pyrus bretschneideri and studies its expression changes in secondary flower induction. [ Method] In our previous study, we explored the physiological changes of simulating secondary flowering by leaf defoliation and had determined the transcriptomic changes of the process. Based on the existing genomic data of Pyrus bretschneideri Rehd., the SPLencoding gene was identified from the whole genome scale, and the transcriptome data of the secondary flower induction process was combined to mine the candidate genes involved in the process. [ Result] A total of 34 typical SPL protein family members were obtained, and only three members were arranged in tandem on the current pear reference genome. The phylogenetic analysis classified 34 members into 8 evolutionary groups, in consistence with other species 'SPL classifications. Transcriptional analysis of the secondary flowering induction and uninduced materials of 'Hosui' showed that only two of the 34 SPL protein-coding genes were significantly differentially expressed, of which Pbr038289 was significantly up-regulated, while Pbr002303 was significantly decreased. [Conclusion] These two proteins are expected to become important targets for in-depth study of the flowering regulation in pear. [ABSTRACT FROM AUTHOR]

[Objective] To grasp the phenotypic genetic diversity and variation of Yunnan Sichuan pear rootstock resources, and to screen the important indicators of type division. [Method] Taking the main producing areas of central and southern Yunnan pear as the main line, field investigation was used to determine 132 sampling points in 14 sampling points. The 14 phenotypic traits of leaves and fruits of Sichuan pear wild resources were analyzed for variation. [Result] The phenotypic traits of 132 Sichuan pears varied greatly, with the coefficient of variation of quality traits ranging from 10.222% to 37.589%, and the largest was fruit. Shape; the coefficient of variation of quantitative traits is between 11.658% and 43.725%, and the largest is the weight of a single fruit. The cluster analysis of 5 principal components shows that 132 wild Sichuan pears are divided into 2 categories, 10 subcategories, between each subcategory There are significant differences in traits. [Conclusion] There is an extremely rich diversity of wild pear rootstock resources in Yunnan, and the variation mainly comes from within the population; the fruit shape, the presence or absence of fruit edges, the shape of the leaf tip, the horizontal diameter of the leaves, the horizontal diameter of the fruit, etc. 5 Character traits are an important index for the classification of fruit and leaf traits of Sichuan pear. [ABSTRACT FROM AUTHOR]

Core browning in Korla pear (Pyrus bretschneideri Rehd.) occurs generally during storage at room temperature. The browning disorder can significantly reduce the shelf stability, and thereby to cause considerable economic losses. Moreover, the browning part of pears can be taken in the juicing process, leading to the juice toxins over the safety limit for drinking. Therefore, a reliable and rapid method has been urgently demanding to nondestructively detect internal disorder for high-quality fruits. In this study, an acoustic system using the piezoelectric beam transducers was developed for nondestructively detecting disorder of pears with different internal browning. The obtained response signals were analyzed to extract 11 statistical features in time domain, and seven statistical features in frequency domain. Accordingly, three modes of feature vectors were formed in the time domain, frequency domain, and time-frequency domain. A Compensation Distance Evaluation Technology (CDET) was also used to evaluate the sensitivities of each parameter in feature vectors. Normally, the larger values of sensitivity evaluation factor can imply the higher sensitivities to the browning classes of pears. Based on sensitivity evaluation factors values in the healthy and browning of pears, the descending order of 11 time-domain features were the mean (T1), shape factor (T11), kurtosis (T6), square root amplitude value (T5), clearance indicator (T8), peak (T3), impulse factor (T9), root mean square (T2), short-time energy (T4), kurtosis factor (T7), and crest factor (T10). The sensitivities of seven frequency-domain features were also ranked in order, the variance (F2), mean square (F6), root mean square (F7), standard deviation (F3), mean (F1), kurtosis (F4), and gravity (F5). Combining two types of features, the descending order of all the features was as follows: T11, F2, T6, T5, F7, F6, T1, F3, F4, F1, F5, T8, T3, T9, T2, T4, T10, and T7. In the slight browning and moderate browning of pears, the sensitivities of time-domain features can be ranked in the descending order of T7, T11, T8, T3, T9, T10, T6, T2, T5, T4, and T1. The obtained order for the frequency-domain features was F4, F3, F7, F6, F1, F5, and F2. In the combined time-frequency features, the order was as follows: T11, T8, F6, T3, F7, F3, T7, F4, F1, F2, T9, F5, T10, T6, T2, T5, T4, and T1. Subsequently, a K-nearest neighbor (KNN) algorithm was utilized to train the classifier using the first n sensitive features as the inputted data. Therefore, a browning discrimination model was constructed for the moderate disorder, whereas, a slight browning discrimination model for the mild disorder. Both models performed the best, when combining the features from the time-domain and frequency-domain. In the browning discrimination model, a high overall accuracy of 91.84 % was obtained with the specific feature vectors, including three time-domain features (T11, T6 and T5), and one frequency-domain feature (F2). In slight browning discrimination model, the slight browning of pears can be further identified with an accuracy of 81.82 %. In the case of slight browning, the specific feature vectors were adopted, including two time-domain features (T11 and T8), and one frequency-domain feature (F6). In the confusion matrix analysis, the high values of F1 indicated that two discrimination models can be used to achieve the high robustness and performance, and further to be generalized for the identification of fruits. These findings can provide a sound theoretical basis and strategy for the industrial real-time in-line detection, and automatic grading in the internal browning disorder of pears. [ABSTRACT FROM AUTHOR]

【Objective】In order to find out the factors affecting the difference of fruit firmness between ‘Korla fragrant pear’ and its bud mutation ‘Sha 01’, the aim was to provide reference for breeding new varieties of ‘Korla fragrant pear’. 【Method】In mature stage, the fruit characters, the content of cell wall components and enzymes activity in ‘Korla fragrant pear’ and ‘Sha 01’ were measured and correlated with fruit firmness with or without pericarp. 【Result】(i)The fruit firmness with and without pericarp of ‘Sha 01’ were both significantly lower than that of ‘Korla fragrant pear’, and the fruit weight and shape index were very significantly negatively correlated and very significantly positively correlated with fruit firmness.(ii)The SP content was very significantly negatively correlated with fruit firmness in the pericarp. The PP content was very significantly positively correlated with fruit firmness in the pulp, and the hemicellulose content was very significantly negatively correlated with fruit firmness.(iii)The activity of PL, PE, cellulase and xylanase in the pericarp were very significantly negatively correlated with the firmness, and significantly negatively correlated with activity of PG and PAL. The activity of PG and cellulase in the pulp were very significantly negatively correlated with the firmness, and significantly negatively correlated with activity of PE, PAL and xylanase. The activity of PPO was very significantly positively correlated with fruit firmness. 【Conclusion】The SP and hemicellulose content, the activity of PG, PL, cellulase, xylanase and PPO in the pericarp, the PP and hemicellulose content, the activity of PG, cellulase, xylanase and PPO in the pulp, single fruit weight and fruit shape index are the factors that affect the difference in fruit firmness between the two varieties. [ABSTRACT FROM AUTHOR]

In this work, the toxicity of difenoconazole to Colletotrichum fructicola at different development stages and its indoor control efficacy were determined. The sensitive baseline of C. fructicola to difenoconazole at major pear cultivation areas in South China (Hubei, Anhui, Jiangxi, Jiangsu, Zhejiang and Fujian Province) was established. The conidia germination and germ tube elongation of six representative strains treated by difenoconazole were determined by spore germination rate method. And its indoor efficacy was tested using detached pear leaves. The sensitivity of 120 strains of C. fructicola to difenoconazole was determined by mycelial growth rate method. The results indicated that difenoconazole had high inhibitory activities against mycelial growth and germ tube elongation. However, the inhibition against conidia germination of C. fructicola was weak, with the average EC50 values of (0.33 ± 0.03) μg/mL, (2.61 ± 0.26) μg/mL and (29.87 ± 1.31) μg/mL, respectively. The protective and curative effects of 160 μg/mL difenoconazole to pear anthracnose were 92% and 79%, respectively. And those of 1 000 μg/mL carbendazim were 51% and 23%, respectively. 120 strains from major pear cultivation areas in South China were sensitive to difenoconazole, and the EC50 values were in the range of 0.27-1.12 μg/mL. The frequency curves of EC50 value was continuous and unimodal, and following the positive skewness distribution. Hence, the mean EC50 value (0.59 ± 0.02) μg/mL could be recognized as baseline sensitivities of C. fructicola to difenoconazole. The study laid the foundation for the evaluation and monitoring of the field resistance of C. fructicola to the difenoconazole, and provided a theoretical basis for the application of this fungicide to control pear anthracnose in the pear cultivation area. [ABSTRACT FROM AUTHOR]

Thinning is one of the three labor-consuming sections (pruning, thinning and harvesting) in orchard management process. Chemical thinning, not only unstable but also reduces fruit safety, has been banned gradually in recent years. Pure artificial thinning, especially artificial fruit thinning, needs larger workload and higher labor cost, unsuitable seriously for the requirements of modern orchard planting. Two kinds of pear mechanical flower thinners were designed in the paper. They were three arms tractor-mounted flower thinner (TMFT) and hand-held flower thinner (HHFT), to alleviate the heavy labor pressure in the process of thinning and improve the efficiency of orchard operation. The width of TMFT was controlled by hydraulic cylinder that range from 1.2 to 1.7 m. TMFT rotation speed of thinning shaft that range from 0 to 300 r/min was controlled by electronic governor. The length of HHFT can change through adjusting the extension rod that range from 0.95 to 1.6 m. HHFT rotation speed of thinning shaft that range from 0 to 900 r/min was controlled by electronic governor too. ‘Y’ trellis ‘Cuiguan’ pear was taken as the research object in the paper. TMFT impact forces of thinning rope with different rotation speed of thinning shaft and thinning distance were measured in bench test, to find the working range of rotation speed. Field test setting 50% flower bud preserved rate (it is easier to thin flower buds than flowers) and 0.44 m/s tractor work speed, and the best rotation speed of thinning shaft was ensured: 254 r/min. Flower bud reserve rate, fruit set rate, work efficiency, fruit yield and quality of four kinds of operation methods were tested, which were TMFT combined with artificial fruit thinning, HHFT combined with artificial fruit thinning, artificial flower fruit thinning and artificial fruit thinning only. Twenty-four ‘Y’ trellis pear trees (6 a) with almost same size were selected for four operation methods. The canopies of each tree were divided into the upper middle lower three layers and five branches were selected as samples in each layer. In order to reduce the operation error, except the TMFT, the operation of each group was completed by two workers with experienced job skill. Field test show that three flower thinning methods can meet the requirement of 50% flower bud preserved rate, the coefficient of variation all less than 15%. There is no obvious difference between TMFT and artificial method in thinning quality and the stability of TMFT is the highest among test groups. Mechanical and artificial flower thinning can significantly reduce about 50% absolute fruit set rate. TMFT will damage the young fruits in a certain degree, but does not affect the yield and quality in the last. Work efficiency of TMFT was highest among flower thinning methods and 66.17% artificial fruit thinning time can be saved. TMFT has a higher requirement for pear orchard mechanization degree, suitable for large-scale mechanized pear orchard. Work efficiency of HHFT is second only to TMFT, 37.26% artificial fruit thinning time can be saved. HHFT is suitable for small and medium sized pear orchard. For fruit yield and quality, total and high quality fruit yield per tree of pure artificial fruit thinning group is higher 11.37% and 8.59% respectively than average values of three kinds of flower thinning group, but the average weight of high quality fruit and brix of sugar solids of is lower 6.58% and 1.55% respectively. The research is helpful to improve the working quality of flower thinner and provide reference for the mechanization management of pear orchard. [ABSTRACT FROM AUTHOR]

Understanding droplet distribution inside tree canopy has a great significance on optimizing spray parameters and improving spray effect. In this article, distribution of droplet penetration rate inside tree canopy during air-assisted spraying was studied by experimental method. The droplet penetration rate was defined as the ratio of droplets inside canopy along unit vertical face to that before penetrating into the canopy. The change of droplet penetration rate with tree leaf density, outlet air velocity of sprayers and sampling depth was analyzed. Disc sprayer and multi air pipe sprayer were used to spray 4 types of tree canopies of pear trees (big, medium and small sizes), wintersweet, cerasus subhirtella and punica granatum. Droplet deposition was determined in real time. The results showed that the droplet penetration rate decreased as the leaf density and sampling depth increased while it increased with increased outlet air velocity of sprayer. Among the 3 test variables of tree leaf density, outlet air velocity of sprayer and sampling depth, the sampling depth greatly affected the droplet penetration rate. Following the changing pattern of droplet penetration rate with tree leaf density, outlet air velocity of sprayer and sampling depth, 5 types of models (linear polynomial, quadratic polynomial, cubic polynomial, single exponent and quadratic exponent) were assumed to fit the changing pattern of droplet penetration rate. The quadratic exponent model had the highest accuracy with R² higher than 0.95 and the RMSE was the least from 4.1% to 5.0%. By experimental validation, the model still had relatively reliable accuracy. Thus, the quadratic exponential model was finally chosen as the suitable model. By using this model, it had to be built based on canopy of each tree. By mixing the data from different tree canopies, we tested the feasibility to estimate droplet penetration rate by a quadratic exponential model. The results showed that the R2 was still higher than 0.95 and root mean square error was 5.3%-5.7%. By validation, the relative error could be lower than 20% for mixture of wintersweet, cerasus subhirtella and pear trees but reach up to about 29% for punica granatum tree. It was because the branch structure of punica granatum was different from the other trees. The quadratic exponential model was then extended to application in calculating droplet drift rate after tree canopy in order to analyze its influencing factor. The droplet drift rate after Cerasus subhirtella tree canopy of different leaf density under different sprayer outlet air velocities was calculated using model and validated by test. The mean relative error was 16.73%, indicating that the model could be used to determine the suitable outlet air velocities for tree canopies of different growing stages and reduce the droplet drift rate. The variation coefficients of droplet distribution inside tree canopy were also calculated by the model, which was used to better explain the principle of double-side spraying pattern. In the end, the model limitation and subsequent research assumption to improve model were illustrated: spray pressure, flow rate, environmental temperature and humidity were approximately regarded as constants in this article, and in further researches, the influence on droplet penetration rate of these factors should be investigated. A unit model for estimating droplet penetration rate could be established if the tree types had similar branches and leaf structures, and in further researches, more types of trees should be chosen and classified to build mixture model to improve the model accuracy. This paper is helpful to understanding droplet distribution in tree canopy during air-assisted spraying. [ABSTRACT FROM AUTHOR]

A method was developed for the quantative determination of 15 high-risk pesticide and adjuvant (acephate, methomyl, thiamethoxam, thiabendazole, acetamiprid,simazine, pyrimethanil, fludioxonil, boscalid, methoxyfenozide, myclobutanil, fenhexamid, tetraconazole, piperonyl butoxide, chlorpyrifos) residues by SPE-ultra performance liquid chromatography-tandem mass spectrometry (SPE-UPLC-MS/MS). The samples were homogenized, extracted with acetonitrile, and cleaned-up by amino solid phase extraction column. The separation was performed on a Shimadu Shim-pack XR-ODS column (75 mm × 2.0 mm, 1.6 μm). The compounds were identified by MS/MS and multiple reaction monitoring (MRM) mode, and quantified by external standard method. The linearities of 15 pesticides and adjuvants were in the concentration range of 0.001-0.5 mg/L, with the correlation coeffecients higher than 0.999 5. At the fortified levels from 0.005 mg/kg to 0.5 mg/kg in pear, grape and apple, the average recoveries of all 15 pesticides and adjuvants ranged from 80% to 115% with the relative standard deviations varied from 5.5% to 16%. The limits of quantification (LOQs) of the analytes were ranged from 0.005 to 0.01 mg/kg. This method is simple, rapid, accutate and therefore, suitable for the confirmation and quantification of the 15 pesticides and adjuvants in fruits. [ABSTRACT FROM AUTHOR]

Understanding droplet distribution inside tree canopy has a great significance on optimizing spray parameters and improving spray effect. In this article, distribution of droplet penetration rate inside tree canopy during air-assisted spraying was studied by experimental method. The droplet penetration rate was defined as the ratio of droplets inside canopy along unit vertical face to that before penetrating into the canopy. The change of droplet penetration rate with tree leaf density, outlet air velocity of sprayers and sampling depth was analyzed. Disc sprayer and multi air pipe sprayer were used to spray 4 types of tree canopies of pear trees (big, medium and small sizes), wintersweet, cerasus subhirtella and punica granatum. Droplet deposition was determined in real time. The results showed that the droplet penetration rate decreased as the leaf density and sampling depth increased while it increased with increased outlet air velocity of sprayer. Among the 3 test variables of tree leaf density, outlet air velocity of sprayer and sampling depth, the sampling depth greatly affected the droplet penetration rate. Following the changing pattern of droplet penetration rate with tree leaf density, outlet air velocity of sprayer and sampling depth, 5 types of models (linear polynomial, quadratic polynomial, cubic polynomial, single exponent and quadratic exponent) were assumed to fit the changing pattern of droplet penetration rate. The quadratic exponent model had the highest accuracy with R2 higher than 0.95 and the RMSE was the least from 4.1% to 5.0%. By experimental validation, the model still had relatively reliable accuracy. Thus, the quadratic exponential model was finally chosen as the suitable model. By using this model, it had to be built based on canopy of each tree. By mixing the data from different tree canopies, we tested the feasibility to estimate droplet penetration rate by a quadratic exponential model. The results showed that the R2 was still higher than 0.95 and root mean square error was 5.3%-5.7%. By validation, the relative error could be lower than 20% for mixture of wintersweet, cerasus subhirtella and pear trees but reach up to about 29% for punica granatum tree. It was because the branch structure of punica granatum was different from the other trees. The quadratic exponential model was then extended to application in calculating droplet drift rate after tree canopy in order to analyze its influencing factor. The droplet drift rate after Cerasus subhirtella tree canopy of different leaf density under different sprayer outlet air velocities was calculated using model and validated by test. The mean relative error was 16.73%, indicating that the model could be used to determine the suitable outlet air velocities for tree canopies of different growing stages and reduce the droplet drift rate. The variation coefficients of droplet distribution inside tree canopy were also calculated by the model, which was used to better explain the principle of double-side spraying pattern. In the end, the model limitation and subsequent research assumption to improve model were illustrated: spray pressure, flow rate, environmental temperature and humidity were approximately regarded as constants in this article, and in further researches, the influence on droplet penetration rate of these factors should be investigated. A unit model for estimating droplet penetration rate could be established if the tree types had similar branches and leaf structures, and in further researches, more types of trees should be chosen and classified to build mixture model to improve the model accuracy. This paper is helpful to understanding droplet distribution in tree canopy during air-assisted spraying. [ABSTRACT FROM AUTHOR]

Ｙｕｎｎａｎ ｉｓ ｆａｍｏｕｓ ｆｏｒ ｉｔｓ ｆｌｏｒｉｐｈａｇｉａ ｃｕｌｔｕｒｅ, ａｎｄ ｔｈｅ ｃｏｒｒｅｌａｔｅｄ ｔｒａｄｉｔｉｏｎａｌ ｋｎｏｗｌｅｄｇｅ ｉｓ ｃｒｕｃｉａｌ ｆｏｒ ｅｄｉｂｌｅ ｆｌｏｗｅｒ ｒｅｓｏｕｒｃｅ ｅｘｐｌｏｒａｔｉｏｎ. “Ｔａｎｇｌｉ” ｆｌｏｗｅｒ, ａ ｇｅｎｅｒａｌ ａｎｄ ｃｏｌｌｅｃｔｉｖｅ ｎａｍｅ ｆｏｒ ａ ｇｒｏｕｐ ｏｆ ｐｏｐｕｌａｒ ｍｅｄｉｃｉｎａｌ ｅｄｉｂｌｅ ｆｌｏｗｅｒｓ ｉｎ Ｙｕｎｎａｎ Ｐｒｏｖｉｎｃｅ, ｂｅｌｏｎｇｓ ｔｏ ｇｅｎｕｓ Ｐｙｒｕｓ. Ｉｎｆｏｒｍａｔｉｏｎ ｏｎ ｗｈｉｃｈ Ｐｙｒｕｓ ｓｐｅｃｉｅｓ ａｒｅ ｕｓｅｄ ａｎｄ ｈｏｗ ｔｏ ｕｓｅ ｉｓ ｌｅｆｔ ｕｎ- ｋｎｏｗｎ. Ｉｎ ｔｈｉｓ ｓｔｕｄｙ, ｂａｓｅｄ ｏｎ ｌｉｔｅｒａｔｕｒｅｓ ｒｅｖｉｅｗ, ｗｅ ｃｏｎｄｕｃｔｅｄ ｆｉｅｌｄ ａｎｄ ｐｅａｋ ｓｅａｓｏｎ ｍａｒｋｅｔ ｓｕｒｖｅｙ, ｖｏｕｃｈｅｒ ｓｐｅｃｉｍｅｎ ｃｏｌｌｅｃｔｉｏｎ ａｎｄ ｓｅｍｉ-ｓｔｒｕｃｔｕｒｅ ｉｎｔｅｒｖｉｅｗ ｆｏｒ ｗｉｌｄ ｅｄｉｂｌｅ “Ｔａｎｇｌｉ” ｆｌｏｗｅｒ ｉｎ Ｓｉｍａｏ Ｄｉｓｔｒｉｃｔ ａｎｄ Ｍｏｊｉａｎｇ Ｃｏｕｎｔｙ ｏｆ Ｐｕｅｒ Ｃｉｔｙ ｉｎ Ｙｕｎｎａｎ Ｐｒｏｖｉｎｃｅ, ｗｈｉｃｈ ｉｓ ｏｎｅ ｏｆ ｔｈｅ ｍｏｓｔ ｐｒｏｄｕｃｔｉｖｅ ａｒｅａｓ ｆｏｒ “Ｔａｎｇｌｉ”. Ｔｈｅ ｒｅｓｕｌｔｓ ｗｅｒｅ ａｓ ｆｏｌｌｏｗｓ: (１) Ｔｈｅ ｅｄｉｂｌｅ “Ｔａｎｇｌｉ” ｆｌｏｗｅｒ ｉｎｖｏｌｖｅｄ ｔｈｒｅｅ Ｐｙｒｕｓ ｔａｘａ, ｔｈｅｙ ｗｅｒｅ Ｐ. ｐａｓｈｉａ, Ｐ. ｐａｓｈｉａ ｖａｒ. ｋｕｍａｏｎｉ ａｎｄ Ｐ. ｂｅｔｕｌｉｆｏｌｉａ' ａｍｏｎｇｓｔ ｗｈｉｃｈ Ｐ. ｐａｓｈｉａ ｗａｓ ｔｈｅ ｍｏｓｔ ｆｒｅｑｕｅｎｔｌｙ ｕｓｅｄ. (２) “Ｔａｎｇｌｉ” ｆｌｏｗｅｒ ｂｕｄｓ ｃｏｍｐｏｓｅｄ ａ ｐｒｏｍｉｎｅｎｔ ｐａｒｔ ｏｆ ｔｈｅ ｅａｒｌｙ ｓｐｒｉｎｇ ｗｉｌｄ ｅｄｉｂｌｅ ｃｏｌｌｅｃｔｉｏｎｓ ａｎｄ ｓｈｏｗｅｄ ｎｏｔａｂｌｅ ｐｏｔｅｎｔｉａｌ ｉｎ ｂｏｔｈ ｌｏｃａｌ ａｎｄ ｅｘｔｅｒｎａｌ ｍａｒｋｅｔｓ. (３) Ｉｎｆｏｒｍａｎｔｓ ｆｒｏｍ ｄｉｆｆｅｒｅｎｔ ｅｔｈｎｉｃ ｇｒｏｕｐｓ ｐｒａｃｔｉｃｅ ｔｈｅ ｐｏｓｔ-ｈａｒｖｅｓｔ ｔｒｅａｔｍｅｎｔ ａｎｄ ｐｒｅｐａｒａｔｉｏｎ ｈａｄ ｈｉｇｈ ｃｏｎｓｉｓｔｅｎｃｙ. (４) Ｈｅａｔ-ｃｌｅａｒｉｎｇ, ａｄａｐｔ ｔｏ ｔｈｅ ｓｅａｓｏｎ ａｌｔｅｒｎａｔｉｏｎ ａｎｄ ｃｏｎｔａｍｉｎａｔｉｏｎ ｆｒｅｅ ｗｅｒｅ ｌｉｓｔｅｄ ａｓ ｔｈｅ ｍｏｓｔ ｓｐｅｃｉｆｉｃ ａｉｍｓ ｆｏｒ ｅａｔｉｎｇ “Ｔａｎｇｌｉ” ｆｌｏｗｅｒｓ. Ｔｈｉｓ ｓｔｕｄｙ ｐｒｏｖｉｄｅｓ ｒｅｆｅｒｅｎｃｅｓ ｆｏｒ ｔａｘｏｎｏｍｉｃ ｉｎｆｏｒｍａｔｉｏｎ ｏｎ ｔｈｅ “Ｔａｎｇｌｉ” ｆｌｏｗｅｒｓ, ｔｒａｄｉｔｉｏｎａｌ ｋｎｏｗｌｅｄｇｅ ｏｎ ｔｈｅｉｒ ｐｒｏｃｅｓｓ ａｎｄ ｕｓｅｓ, ａｎｄ ｆｏｒ ｅｓｔｉｍａｔｉｏｎ ｏｆ ｒｅｓｏｕｒｃｅ ｖａｌｕｅ ａｎｄ ｉｎｆｌｕｅｎｃｅ, ｆｌｏｗｅｒｓ ｆｏｒ ａ ｗｉｄｅｒ ｍａｒｋｅｔ ａｎｄ ｔｏ ａ ｖａｌｕｅ-ａｄｄｅｄ ｐｒｏｄｕｃｔ, ａｎｄ ｐｒｏ-ｖｉｄｅｓ ｐｈｙｓｉｏｌｏｇｉｃａｌ ｓｉｇｎｉｆｉｃａｎｃｅ ａｎｄ ｃｕｌｔｕｒａｌ ｉｓｓｕｅ ｏｆ ｅｄｉｂｌｅ ｆｌｏｗｅｒｓ ａｓ ｗｅｌｌ. [ABSTRACT FROM AUTHOR]

Laser speckle is a new technology for non-destructive detection in agriculture. When laser light with good coherence irradiates on the optically rough surface or the surface with some kind of activity, the scattering light will interfere with each other and form a mottled pattern called laser speckle. The laser speckle contains various information of the reflector, such as the roughness, the particle's motion and the temperature information. Huangguan pears were used as the object in this research to investigate the possibility of identifying the defects from the stem/calyx and the sound area of pears based on laser speckle technology. A laser speckle imaging system was established which contained a semiconductor laser (635 nm, 50 mw) applied as the light source and a digital signal generator applied as the trigger source of the CCD (charge coupled device) camera. Two hundred pears including one hundred sound pears and one hundred pears with the defect (rot) were tested. The speckle images of defect (rot) parts and good parts (calyx/stem, sound area) of the pears were collected under the same condition. First of all, the speckle images were converted into the grayscale images using Matlab 2011b. The method of Fujii and the weighted generalized differences method (WGD) were used to analyze the grayscale speckle images to get the images of Fujii and WGD. Then gray level co-occurrence matrix (GLCM) was used to extract the mean and the standard deviation values of the angular second moment (ASM), entropy (ENT), moment of inertia (INE) and correlation (COR) from the images of Fujii and WGD, respectively. Therefore, in total, 16 features were extracted. The performance of each feature was evaluated by the receiver operator characteristic (ROC) curve. According to the ROC curves, the features whose values of the area under the curves (AUC) were higher than 0.5 were chosen for further analysis. The best threshold value of each selected feature was calculated by Youden's index. The classification analysis based on single feature was tested using the best threshold value. Besides, the classification analysis based on multiple features was carried out by the binary logistic regression. The combination of every two features was tested to get better classification accuracy. The results showed that there were seven features whose AUC values were bigger than 0.5. In classification of single feature, the ASM extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were 96.4% and 96.7% respectively. In classification of multiple features, the combination of the ASM and standard deviation of correlation extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were both 97.5%. In order to find out the causes of the error, the original RGB (red, green and blue) images of the misjudged samples were studied. It turned out that the defect area which was misjudged to be normal was not obvious. Besides, the defect area was larger than the light spot whose diameter was 20 mm which could not cover the defect area completely. Therefore, the texture features of laser speckle images of misjudged samples were closer to the sound area than the defect area, which led to the miscalculation. This research shows that the method of laser speckle imaging is feasible in the detection of pear defect (rot) and stem/calyx. [ABSTRACT FROM AUTHOR]

Laser speckle is a new technology for non-destructive detection in agriculture. When laser light with good coherence irradiates on the optically rough surface or the surface with some kind of activity, the scattering light will interfere with each other and form a mottled pattern called laser speckle. The laser speckle contains various information of the reflector, such as the roughness, the particle's motion and the temperature information. Huangguan pears were used as the object in this research to investigate the possibility of identifying the defects from the stem/calyx and the sound area of pears based on laser speckle technology. A laser speckle imaging system was established which contained a semiconductor laser (635 nm, 50 mw) applied as the light source and a digital signal generator applied as the trigger source of the CCD (charge coupled device) camera. Two hundred pears including one hundred sound pears and one hundred pears with the defect (rot) were tested. The speckle images of defect (rot) parts and good parts (calyx/stem, sound area) of the pears were collected under the same condition. First of all, the speckle images were converted into the grayscale images using Matlab 2011b. The method of Fujii and the weighted generalized differences method (WGD) were used to analyze the grayscale speckle images to get the images of Fujii and WGD. Then gray level co-occurrence matrix (GLCM) was used to extract the mean and the standard deviation values of the angular second moment (ASM), entropy (ENT), moment of inertia (INE) and correlation (COR) from the images of Fujii and WGD, respectively. Therefore, in total, 16 features were extracted. The performance of each feature was evaluated by the receiver operator characteristic (ROC) curve. According to the ROC curves, the features whose values of the area under the curves (AUC) were higher than 0.5 were chosen for further analysis. The best threshold value of each selected feature was calculated by Youden's index. The classification analysis based on single feature was tested using the best threshold value. Besides, the classification analysis based on multiple features was carried out by the binary logistic regression. The combination of every two features was tested to get better classification accuracy. The results showed that there were seven features whose AUC values were bigger than 0.5. In classification of single feature, the ASM extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were 96.4% and 96.7% respectively. In classification of multiple features, the combination of the ASM and standard deviation of correlation extracted from WGD image had the best performance whose overall accuracies of calibration and validation sets were both 97.5%. In order to find out the causes of the error, the original RGB (red, green and blue) images of the misjudged samples were studied. It turned out that the defect area which was misjudged to be normal was not obvious. Besides, the defect area was larger than the light spot whose diameter was 20 mm which could not cover the defect area completely. Therefore, the texture features of laser speckle images of misjudged samples were closer to the sound area than the defect area, which led to the miscalculation. This research shows that the method of laser speckle imaging is feasible in the detection of pear defect (rot) and stem/calyx. [ABSTRACT FROM AUTHOR]

Using scanning electron microscopy and optical microscopy system, morphology and exine ornamentation of 10 local pear varieties were observed; Cluster analysis on six quantitative traits was done based on results of pollen morphology observation study. The results showed that: pollen size range of these local pear varieties was from small to medium; Most of local pear varieties were prolate except Fangshanpiao pear and Chinese sand pear and Tapi pear which were perprolate; Every local pear variety belonged to N3P4C5 type which had 3 germinal colporate lasting almost to two ends of the colporat; There were little traces of germinal apertures on base of germinal colporat. The pollen was oblong or elliptic in side view and was trilobate triangle or trilobate circular in polar view; The equatorial view of these local pear varieties were oval and appeared to be cloven; There were striped or retculate exine ornamentation and perforation in the surface. According to the results of cluster analysis, such results were conjectured: Fangshanpiao pear, Hanyuan white pear, bread pear, osmanthus pear and Dayexue pear belonged to Pyrus bretschneideri Rehd, while Tapi pear belonged to Pyrus Brestchneideri Nak. [ABSTRACT FROM AUTHOR]