Entity

Time filter

Source Type


Li Y.,Nanjing Agricultural University | Sun G.,Jiangsu Province Engineering Laboratory for Modern Facility Agriculture Technology and Equipment | Wang X.,Jiangsu Province Engineering Laboratory for Modern Facility Agriculture Technology and Equipment
Mathematical Problems in Engineering | Year: 2014

The computational fluid dynamics technology is applied as the environmental control model, which can include the greenhouse space. Basic environmental factors are set to be the control objects, the field information is achieved via the division of layers by height, and numerical characteristics of each layer are used to describe the field information. Under the natural ventilation condition, real-time requirements, energy consumption, and distribution difference are selected as index functions. The optimization algorithm of adaptive simulated annealing is used to obtain optimal control outputs. A comparison with full-open ventilation shows that the whole index can be reduced at 44.21% and found that a certain mutual exclusiveness exists between the temperature and velocity field in the optimal course. All the results indicate that the application of CFD model has great advantages to improve the control accuracy of greenhouse. © 2014 Yongbo Li et al. Source


Zhang F.,Nanjing Agricultural University | Chen S.,Nanjing Agricultural University | Jiang J.,Nanjing Agricultural University | Guan Z.,Nanjing Agricultural University | And 3 more authors.
PLoS ONE | Year: 2013

Flowering time is an important trait in chrysanthemum, but its genetic basis remains poorly understood. An intra-specific mapping population bred from the cross between the autumn-flowering cultivar 'Yuhualuoying' and the summer-flowering 'Aoyunhanxiao' was used to determine the number and relative effect of QTL segregating for five measures of flowering time. From flowering time data recorded over two consecutive seasons, 35 additive QTL were detected, each explaining between 5.8% and 22.7% of the overall phenotypic variance. Of these, 13 were detected in both years. Nine genomic regions harboring QTL for at least two of the five traits were identified. Ten pairs of loci epistatically determined the flowering time, but their contribution to the overall phenotypic variance was less than for the additive QTL. The results suggest that flowering time in chrysanthemum is principally governed by main effect QTL but that epistasis also contributes to the genetic architecture of the trait, and the major QTL identified herein are useful in our ongoing efforts to streamline the improvement of chrysanthemum via the use of molecular methodology. © 2013 Zhang et al. Source


Qian Y.,Nanjing Agricultural University | Qian Y.,Jiangsu Province Engineering Laboratory for Modern Facility Agriculture Technology and Equipment | Yin W.,Nanjing Agricultural University | Lin X.,Nanjing Agricultural University | And 2 more authors.
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2014

Rice seed surface morphology is an important aspect of seed purity identification and recognition. Considering that artificial recognition and identification methods have some faults, which including low efficiency, high labor costs, and poor accuracy. So scientifically selecting quality rice seeds by using computer vision methods is important. Different models and methods have been established in the field of crop seed identification. Studies on rice seed speciation analysis methods indicate that the current detection methods in computer vision mainly analyze 2D information and that the use of 3D models is lacking. This paper proposes a 3D rice seed reconstruction system which can be used to measure the morphology of rice seed, with more accurate shape measure parameters and more comprehensive appearance characteristics and defect expression. In this paper, a new crop seed reconstruction system that supports fast and accurate recognition was designed to build a 3D surface morphology. The depth-from-focus (DFF) method was applied in the analysis of crop surface morphology. Image sequences were acquired by using a specific vision device through setting different distances between the camera lens and the rice seed. High-pass filtering was used to extract pixels and analyze strength value changes in the frequency domain. The second-order differential was employed to strengthen the value in the frequency domain by using the improved Laplacian operator. The threshold statistical analysis was conducted in pixel windows, by which each pixel generated a value which showed the focusing condition. The focusing measure of the image sequence effectively determined the estimated depth value of a pixel, and a focusing pixel stack could be defined based on these values. Using the characteristics of the Gaussian distribution of the focal depth estimation value, the Gaussian interpolation was calculated to obtain a more precise surface morphology depth value. As a result, a depth image collected based on the estimated depth value of the pixel was developed. Finally, through depth image smoothing and edge pixel processing, a 3D point cloud could be produced. Thus, a rice seed reconstruction system which can be used in rice seed identification and recognition was designed. This novel system supports three main patterns, namely, shape, texture, and 3D recognition. Through further calculations, the surface morphology characteristics of seed are obtained. The new 3D surface morphology reconstruction system can effectively overcome the deficiencies of traditional seed speciation analysis methods and can be served as an important reference for researchers. Finally, the BP neural network model was constructed to support the variety identification. Suitable neural network algorithm was selected for five different sorts of rice seed, and the final identification rate is 90%. The research can provide a reference for study of three-dimension shape and texture in automation crops variety identification field. Source


Song A.,Nanjing Agricultural University | Song A.,Jiangsu Province Engineering Laboratory for Modern Facility Agriculture Technology and Equipment | Wang L.,Nanjing Agricultural University | Chen S.,Nanjing Agricultural University | And 5 more authors.
Plant Physiology and Biochemistry | Year: 2015

MicroRNA (miRNA) is involved in many developmental processes and various abiotic stress responses in plants. As nitrogen is a limited element for plant growth, comparative analyses of miRNAs responding to low nitrogen stress is important for improving the nitrogen use efficiency (NUE). We used high-throughput sequencing to detect the response of miRNAs to low nitrogen stress in the roots and leaves of Chrysanthemum nankingense. Compared with the control, the differential expression was more than 2-fold in 81 miRNAs in roots and 101 miRNAs in leaves. The identified miRNAs showed overlapping or unique response to nitrate limitation in roots and leaves, including several members of known miRNA families with low nitrogen stress response, such as miR156, miR169, and miR393. The potential target genes of these miRNAs were also identified. The total amount of predicted target genes was 219, and the corresponding amount of matched miRNAs was 37 in roots and 44 in leaves. Moreover, we used 5' RLM-RACE to map the cleavage sites in four predicted target genes. The differential expression level of miRNAs and target genes was verified by quantitative real-time polymerase chain reaction (qRT-PCR). According to the functional characteristics of the predicted target genes, they were divided into three main categories: transcription factors, kinases, and metabolism. © 2015. Source


Wang H.,Nanjing Agricultural University | Wang H.,Jiangsu Province Engineering Laboratory for Modern Facility Agriculture Technology and Equipment | Jiang J.,Nanjing Agricultural University | Chen S.,Nanjing Agricultural University | And 5 more authors.
BMC Genomics | Year: 2013

Background: Hybridization is a major driver of evolution in plants. In a number of plant species, the process of hybridization has been revealed to be accompanied by wide-ranging genetic and epigenetic alterations, some of which have consequences on gene transcripts. The Asteraceae family includes a number of polyploid species, and wide crossing is seen as a viable means of genetically improving ornamental species such as Chrysanthemum spp. However, the consequences of hybridization in this taxon have yet to be characterized. Results: Amplified fragment length polymorphism (AFLP), methylation sensitive amplification polymorphism (MSAP) and cDNA-AFLP profiling of the two intergeneric hybrids C. nankingense × Tanacetum vulgare and C. crassum × Crossostephium chinense were employed to characterize, respectively, the genomic, epigenomic and transcriptomic changes induced by the hybridization event. The hybrids' AFLP profiles included both the loss of specific parental fragments and the gain of fragments not present in either parent's profile. About 10% of the paternal fragments were not inherited by the hybrid, while the corresponding rate for the maternal parent fragments was around 4-5%. The novel fragments detected may have arisen either due to heterozygosity in one or other parent, or as a result of a deletion event following the hybridization. Around one half of the cDNA-AFLP fragments were common to both parents, about 30% were specific to the female parent, and somewhat under 20% specific to the male parent; the remainder (2.9-4.7%) of the hybrids' fragments were not present in either parent's profile. The MSAP fingerprinting demonstrated that the hybridization event also reduced the amount of global cytosine methylation, since > 50% of the parental fragments were methylated, while the corresponding frequencies for the two hybrids were 48.5% and 50.4%. Conclusions: Combining two different Asteraceae genomes via hybridization clearly induced a range of genomic and epigenomic alterations, some of which had an effect on the transcriptome. The rapid genomic and transcriptomic alterations induced by hybridization may accelerate the evolutionary process among progenies. © 2013 Wang et al.; licensee BioMed Central Ltd. Source

Discover hidden collaborations