Plant height is an important parameter of plant phenotype as one indicator of plant growth. In view of the complexity and scale limitation in current measurement systems, a scaleless method is ...proposed for the automatic measurement of plant height based on monocular computer vision. In this study, four peppers planted side by side were used as the measurement objects. Two color images of the measurement object were obtained by using a monocular camera at different shooting heights. Binary images were obtained as the images were processed by super-green grayscale and the Otsu method. The binarized images were transformed into horizontal one-dimensional data by the statistical number of vertical pixels, and the boundary points of multiple plants in the image were found and segmented into single-plant binarized images by filtering and searching for valleys. The pixel height was extracted from the segmented single plant image and the pixel displacement of the height was calculated, which was substituted into the calculation together with the reference height displacement to obtain the realistic height of the plant and complete the height measurements of multiple plants. Within the range of 2–3 m, under the light condition of 279 lx and 324 lx, this method can realize the rapid detection of multi-plant phenotypic parameters with a high precision and obtain more accurate plant height measurement results. The absolute error of plant height measurement is not more than ±10 mm, and the absolute proportion error is not more than ±4%.
The soybean is a significant legume crop, providing several vital dietary components. Extreme heat stress negatively affects soybean yield and quality, especially at the germination stage. Continuous ...change in climatic conditions is threatening the global food supply and food security. Therefore, it is a critical need of time to develop heat-tolerant soybean genotypes. Different molecular techniques have been developed to improve heat stress tolerance in soybean, but until now complete genetic mechanism of soybean is not fully understood. Various molecular methods, like quantitative trait loci (QTL) mapping, genetic engineering, transcription factors (TFs), transcriptome, and clustered regularly interspaced short palindromic repeats (CRISPR), are employed to incorporate heat tolerance in soybean under the extreme conditions of heat stress. These molecular techniques have significantly improved heat stress tolerance in soybean. Besides this, we can also use specific classical breeding approaches and different hormones to reduce the harmful consequences of heat waves on soybean. In future, integrated use of these molecular tools would bring significant results in developing heat tolerance in soybean. In the current review, we have presented a detailed overview of the improvement of heat tolerance in soybean and highlighted future prospective. Further studies are required to investigate different genetic factors governing the heat stress response in soybean. This information would be helpful for future studies focusing on improving heat tolerance in soybean.
A Face Recognition Method Based on CNN Xie, Zhiming; Li, Junjie; Shi, Hui
Journal of physics. Conference series,
11/2019, Letnik:
1395, Številka:
1
Journal Article
Recenzirano
Odprti dostop
The traditional face recognition technology is more complicated for the extraction of facial image features and the selection of classifiers, and the recognition rate is not high. With the continuous ...maturity of the convolutional neural network from handwritten digit recognition to face recognition, A face recognition algorithm that tests CNN using the Python+Keras framework. The method mainly involves two aspects. One is to observe the influence on the network by changing the number of neurons in the hidden layer; the other is to observe the influence on the network by changing the number of feature maps of the convolutional layer 1 and the convolutional layer 2. The best CNN model is 36-76-1024 through multiple sets of experimental tests. The model can automatically extract facial image features and classify them. Using adam optimizer and softmax classifier for face recognition can make training faster convergence and more. Effectively improve accuracy and use the Dropout method to avoid overfitting. The experimental results show that the recognition rate of the CNN model on the olivettifaces face database is 97.5%. When the optimal CNN model is used, the average recognition rate is close to 100%, which verifies the validity and accuracy of the algorithm and model.
The accurate detection of green citrus in natural environments is a key step in realizing the intelligent harvesting of citrus through robotics. At present, the visual detection algorithms for green ...citrus in natural environments still have poor accuracy and robustness due to the color similarity between fruits and backgrounds. This study proposed a multi-scale convolutional neural network (CNN) named YOLO BP to detect green citrus in natural environments. Firstly, the backbone network, CSPDarknet53, was trimmed to extract high-quality features and improve the real-time performance of the network. Then, by removing the redundant nodes of the Path Aggregation Network (PANet) and adding additional connections, a bi-directional feature pyramid network (Bi-PANet) was proposed to efficiently fuse the multilayer features. Finally, three groups of green citrus detection experiments were designed to evaluate the network performance. The results showed that the accuracy, recall, mean average precision (mAP), and detection speed of YOLO BP were 86, 91, and 91.55% and 18 frames per second (FPS), respectively, which were 2, 7, and 4.3% and 1 FPS higher than those of YOLO v4. The proposed detection algorithm had strong robustness and high accuracy in the complex orchard environment, which provides technical support for green fruit detection in natural environments.
Recently, both ensemble clustering and semi-supervised clustering have emerged as important paradigms of traditional clustering. Ensemble clustering seeks to integrate multiple clustering results ...from different methods or the same methods with different parameters. Semi-supervised clustering involves using a small amount of class membership information in some samples for the learning process. Meanwhile, Semi-Supervised Ensemble Clustering (SSEC) has attracted increasing attention due to its high performance. However, most SSEC algorithms are configured based on partitional clustering techniques, and there are few attempts on hierarchical clustering techniques. Even in existing hierarchy-based SSEC algorithms, prior knowledge is not sufficiently used and is often applied to create primary partitions. To address these problems, we propose a Semi-supervised Hierarchical Ensemble Clustering framework based on a novel Similarity metric and stratified feature Sampling, which we call SHECSS. SHECSS uses the information of all primary partitions according to their strength to calculate the similarity between samples. Also, SHECSS is equipped with a stratified feature sampling mechanism that can improve the diversity of primary partitions and deal with high-dimensional data. Here, the primary partitions are created based on multiple hierarchical clustering techniques, and the target partition is configured by a consensus function based on the clusters clustering policy. Experimental results show the effectiveness and efficiency of SHECSS compared to representative clustering methods.
The research aimed to determine the effects of Si application on photosynthetic characteristics of maize on saline-alkaline soil, including photosynthetic rate ( P n ), stomatal conductance ( g s ), ...transpiration rate (E), and intercellular CO2 concentration ( C i ) of maize in the field with five levels (0, 45, 90, 150, and 225 kg·ha−1) of Si supplying. Experimental results showed that the values of P n , g s , and C i of maize were significantly enhanced while the values of E of maize were dramatically decreased by certain doses of silicon fertilizers, which meant that Si application with proper doses significantly increased photosynthetic efficiency of maize in different growth stages under stressing environment of saline-alkaline soil. The optimal dose of Si application in this experiment was 150 kg·ha−1 Si. It indicated that increase in maize photosynthesis under saline-alkaline stress took place by Si application with proper doses, which is helpful to improve growth and yield of maize.
There is little information regarding the dynamics of fermentation products and the bacterial community in silage prepared with alfalfa (MS), perennial ryegrass (LP), and their mixture in the karst ...region. In this study, we explored the effects of combining MS with LP in different ratios (100% MS, 70% MS + 30% LP, 50% MS + 50% LP, 30% MS + 70% LP and 100% LP; fresh matter basis) on silage chemical composition, fermentation quality, bacterial communities and predicted functions during the ensiling process. Each treatment was prepared in triplicate and stored at room temperature (22-25°C) for 7, 15, and 45 days. The dry matter (DM) and water-soluble carbohydrate content of the silages increased as the LP proportion in the mixed silage increased; at 45 days, the 70% MS + 30% LP, 50% MS + 50% LP and 30% MS + 70% LP silages contained higher (
< 0.05) CP content than the 100% MS and 100% LP silages. The 30% MS + 70% LP and 100% LP silages exhibited lower (
< 0.05) pH and higher (
< 0.05) LA content than the other silages; at 45 days, none of the silages contained PA or BA. As fermentation proceeded, the abundance of harmful (
and
) and beneficial (
,
,
, and
) microorganisms decreased and increased, respectively, as the LP proportion in the mixed silage increased. The predicted functional distribution of microbial communities and metabolic pathways revealed that the 30% MS + 70% LP and 100% LP silages had a stronger capacity for fermentation and a weaker capacity for nitrate reduction than the other silages. Moreover, as the fermentation proceeded, the 30% MS + 70% LP and 100% LP treatments enhanced the functions of "Metabolism," "Genetic information processing" and "Organismal systems" at level 1, the functions of "Amino acid metabolism" and "Nucleotide metabolism" at level 2, and the functions of "Metabolic pathways," "Biosynthesis of secondary metabolites," "Biosynthesis of antibiotics" and "Purine metabolism" at level 3. Thus, adding LP could improve the fermentation quality of MS silage by changing the composition and metabolic function of microbes; furthermore, ensiling 30% alfalfa with 70% ryegrass can produce high-quality silage in the karst region.
We present a multi-sensor dataset of bimanual human-to-human object handovers. The dataset consists of 240 recordings obtained from 12 pairs of participants performing bimanual object handovers with ...10 objects, and 120 recordings obtained from the same 12 pairs of participants performing unimanual handovers with 5 of those objects. Each recording includes the giver and receiver's 13 upper-body bone position and orientation trajectories, position trajectories for the 27 markers placed on their upper bodies, object position and orientation trajectories, and two RGB-D data streams. The motion trajectories are recorded at 120Hz and the RGB-D streams are recorded at 30Hz. The recordings are annotated with the three handover phases: reach, transfer, and retreat. The dataset also includes four anthropometric measurements of the participants: height, waistline height, arm span, and weight. Our dataset could help investigations of the bimanual reaching motions and grasps utilized by humans while performing handovers. Also, it can be used to train robots to perform bimanual object handovers with humans.
Premise of the Study: Calocedrus is among the genera with a typical eastern Asian-western North American disjunct distribution today. The origin of its modern distribution pattern can be better ...understood by examining its fossil record. Methods: The present article reports for the first time a new fossil species of this genus based on compressed material from the Oligocene Ningming Formation of Guangxi, South China, in its present major distribution area in eastern Asia. Key Results: Calocedrus huashanensis sp. nov. is most similar to the two extant eastern Asian species, C. macrolepis and C. formosana, in gross morphology of foliage shoots and bears a close resemblance to the latter in cuticle structure. It shows a general similarity to the North American fossil representatives of the genus in alternately branched foliage shoots but is clearly different from the European Paleogene species characterized by oppositely branched leafy shoots. Conclusions: This discovery provides new evidence for the floristic exchange of this genus between eastern Asia and North America before the Oligocene (most likely in the Eocene), presumably via the Bering land bridge. The flattened leafy shoots and dimorphic leaves with thin cuticle, open stomatal pits, and shallowly sunken guard cells of the present fossils suggest a rather humid climate during the Oligocène in the Ningming area, South China.
The objectives of the study were to determine the effects of silicon on photosynthetic characteristics of maize on alluvial soil, including total chlorophyll contents, photosynthetic rate P n , ...stomatal conductance g s , transpiration rate ( E ), and intercellular CO2 concentration C i using the method of field experiment, in which there were five levels (0, 45, 90, 150, and 225 kg·ha−1) of silicon supplying. The results showed that certain doses of silicon fertilizers can be used successfully in increasing the values of total chlorophyll contents, P n , and g s and decreasing the values of E and C i of maize leaves, which meant that photosynthetic efficiency of maize was significantly increased in different growth stages by proper doses of Si application on alluvial soil, and the optimal dose of Si application was 150 kg·ha−1. Our results indicated that silicon in proper amounts can be beneficial in increasing the photosynthetic ability of maize, which would be helpful for the grain yield and growth of maize.
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