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  1. AU="Fan-tao KONG"
  2. AU="Field, R C"
  3. AU="Coombes, Brandon J"
  4. AU="Garay, Raúl O."
  5. AU="Jingfeng Xue"
  6. AU="Kelliher, Christina M"
  7. AU="Busby, Marjorie G"

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  1. Artikel ; Online: Impact of climate change on maize yield in China from 1979 to 2016

    Jian-zhai WU / Jing ZHANG / Zhang-ming GE / Li-wei XING / Shu-qing HAN / Chen SHEN / Fan-tao KONG

    Journal of Integrative Agriculture, Vol 20, Iss 1, Pp 289-

    2021  Band 299

    Abstract: Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the impact of climate change on maize yields can provide ... ...

    Abstract Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the impact of climate change on maize yields can provide effective guidance to national and international economics and politics. Panel models are unable to determine the group-wise heteroscedasticity, cross-sectional correlation and autocorrelation of datasets, therefore we adopted the feasible generalized least square (FGLS) model to evaluate the impact of climate change on maize yields in China from 1979–2016 and got the following results: (1) During the 1979–2016 period, increases in temperature negatively impacted the maize yield of China. For every 1°C increase in temperature, the maize yield was reduced by 5.19 kg 667 m–2 (1.7%). Precipitation increased only marginally during this time, and therefore its impact on the maize yield was negligible. For every 1 mm increase in precipitation, the maize yield increased by an insignificant amount of 0.043 kg 667 m–2 (0.014%). (2) The impacts of climate change on maize yield differ spatially, with more significant impacts experienced in southern China. In this region, a 1°C increase in temperature resulted in a 7.49 kg 667 m–2 decrease in the maize yield, while the impact of temperature on the maize yield in northern China was insignificant. For every 1 mm increase in precipitation, the maize yield increased by 0.013 kg 667 m–2 in southern China and 0.066 kg 667 m–2 in northern China. (3) The resilience of the maize crop to climate change is strong. The marginal effect of temperature in both southern and northern China during the 1990–2016 period was smaller than that for the 1979–2016 period.
    Schlagwörter climate change ; maize yield ; FGLS model ; China ; Agriculture (General) ; S1-972
    Thema/Rubrik (Code) 950
    Sprache Englisch
    Erscheinungsdatum 2021-01-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Automatic image segmentation method for cotton leaves with disease under natural environment

    Jian-hua ZHANG / Fan-tao KONG / Jian-zhai WU / Shu-qing HAN / Zhi-fen ZHAI

    Journal of Integrative Agriculture, Vol 17, Iss 8, Pp 1800-

    2018  Band 1814

    Abstract: In order to improve the image segmentation performance of cotton leaves in natural environment, an automatic segmentation model of diseased leaf with active gradient and local information is proposed. Firstly, a segmented monotone decreasing edge ... ...

    Abstract In order to improve the image segmentation performance of cotton leaves in natural environment, an automatic segmentation model of diseased leaf with active gradient and local information is proposed. Firstly, a segmented monotone decreasing edge composite function is proposed to accelerate the evolution of the level set curve in the gradient smooth region. Secondly, canny edge detection operator gradient is introduced into the model as the global information. In the process of the evolution of the level set function, the guidance information of the energy function is used to guide the curve evolution according to the local information of the image, and the smooth contour curve is obtained. And the main direction of the evolution of the level set curve is controlled according to the global gradient information, which effectively overcomes the local minima in the process of the evolution of the level set function. Finally, the Heaviside function is introduced into the energy function to smooth the contours of the motion and to increase the penalty function φ(x) to calibrate the deviation of the level set function so that the level set is smooth and closed. The results showed that the model of cotton leaf edge profile curve could be obtained in the model of cotton leaf covered by bare soil, straw mulching and plastic film mulching, and the ideal edge of the ROI could be realized when the light was not uniform. In the complex background, the model can segment the leaves of the cotton with uneven illumination, shadow and weed background, and it is better to realize the ideal extraction of the edge of the blade. Compared with the Geodesic Active Contour (GAC) algorithm, Chan-Vese (C-V) algorithm and Local Binary Fitting (LBF) algorithm, it is found that the model has the advantages of segmentation accuracy and running time when processing seven kinds of cotton disease leaves images, including uneven lighting, leaf disease spot blur, adhesive diseased leaf, shadow, complex background, unclear diseased leaf edges, and ...
    Schlagwörter local binary fitting model ; natural environment ; cotton ; disease leaves ; image segmentation ; Agriculture (General) ; S1-972
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2018-08-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel: Automatic image segmentation method for cotton leaves with disease under natural environment

    ZHANG, Jian-hua / Fan-tao KONG / Jian-zhai WU / Shu-qing HAN / Zhi-fen ZHAI

    CAAS. Publishing services by Elsevier B.V Journal of integrative agriculture. 2018 Aug., v. 17, no. 8

    2018  

    Abstract: In order to improve the image segmentation performance of cotton leaves in natural environment, an automatic segmentation model of diseased leaf with active gradient and local information is proposed. Firstly, a segmented monotone decreasing edge ... ...

    Abstract In order to improve the image segmentation performance of cotton leaves in natural environment, an automatic segmentation model of diseased leaf with active gradient and local information is proposed. Firstly, a segmented monotone decreasing edge composite function is proposed to accelerate the evolution of the level set curve in the gradient smooth region. Secondly, canny edge detection operator gradient is introduced into the model as the global information. In the process of the evolution of the level set function, the guidance information of the energy function is used to guide the curve evolution according to the local information of the image, and the smooth contour curve is obtained. And the main direction of the evolution of the level set curve is controlled according to the global gradient information, which effectively overcomes the local minima in the process of the evolution of the level set function. Finally, the Heaviside function is introduced into the energy function to smooth the contours of the motion and to increase the penalty function φ(x) to calibrate the deviation of the level set function so that the level set is smooth and closed. The results showed that the model of cotton leaf edge profile curve could be obtained in the model of cotton leaf covered by bare soil, straw mulching and plastic film mulching, and the ideal edge of the ROI could be realized when the light was not uniform. In the complex background, the model can segment the leaves of the cotton with uneven illumination, shadow and weed background, and it is better to realize the ideal extraction of the edge of the blade. Compared with the Geodesic Active Contour (GAC) algorithm, Chan-Vese (C-V) algorithm and Local Binary Fitting (LBF) algorithm, it is found that the model has the advantages of segmentation accuracy and running time when processing seven kinds of cotton disease leaves images, including uneven lighting, leaf disease spot blur, adhesive diseased leaf, shadow, complex background, unclear diseased leaf edges, and staggered condition. This model can not only conduct image segmentation of cotton leaves under natural conditions, but also provide technical support for the accurate identification and diagnosis of cotton diseases.
    Schlagwörter algorithms ; cotton ; energy ; foliar diseases ; leaves ; lighting ; models ; mulching ; plastic film mulches ; soil ; straw mulches ; weeds
    Sprache Englisch
    Erscheinungsverlauf 2018-08
    Umfang p. 1800-1814.
    Erscheinungsort Elsevier B.V.
    Dokumenttyp Artikel
    ZDB-ID 2660426-7
    ISSN 2095-3119
    ISSN 2095-3119
    DOI 10.1016/S2095-3119(18)61915-X
    Datenquelle NAL Katalog (AGRICOLA)

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  4. Artikel ; Online: Spatial-Temporal Changes in Grain Production, Consumption and Driving Mechanism in China

    Shi-wei XU / Jian-zhai WU / Wei SONG / Zhi-qiang LI / Zhe-min LI / Fan-tao KONG

    Journal of Integrative Agriculture, Vol 12, Iss 2, Pp 374-

    2013  Band 385

    Abstract: The spatial-temporal patterns of grain production and consumption have an important influence on the effective national grain supply on condition of tight balance in the total grain amount in China. In this paper, we analyze the spatial-temporal patterns ...

    Abstract The spatial-temporal patterns of grain production and consumption have an important influence on the effective national grain supply on condition of tight balance in the total grain amount in China. In this paper, we analyze the spatial-temporal patterns of grain production, consumption and the driving mechanism for their evolution processes in China. The results indicate that both gravity centers of grain production and consumption in China moved toward the northern and eastern regions, almost in the same direction. The coordination of grain production and consumption increased slightly from 1995 to 2007 but decreased from 2000 to 2007. There is a spatial difference between the major districts of output increase and the strong growth potential in grain consumption, which indicates an increasing difficulty in improving the regional coordination of grain production and consumption. The movement of the gravity center of grain production is significantly correlated with regional differences in grain production policy, different economic development models, and spatial disparity of land and water resource use. For grain consumption, the main driving factors include rapid urbanization, the upgrade of food consumption structure, and distribution of food industries.
    Schlagwörter grain production ; grain consumption ; gravity center ; driving mechanism ; Agriculture (General) ; S1-972
    Thema/Rubrik (Code) 669
    Sprache Englisch
    Erscheinungsdatum 2013-02-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel: Spatial-Temporal Changes in Grain Production, Consumption and Driving Mechanism in China

    XU, Shi-wei / Fan-tao KONG / Jian-zhai WU / Wei SONG / Zhe-min LI / Zhi-qiang LI

    Chinese Academy of Agricultural Sciences Journal of integrative agriculture. 2013 Feb., v. 12

    2013  

    Abstract: The spatial-temporal patterns of grain production and consumption have an important influence on the effective national grain supply on condition of tight balance in the total grain amount in China. In this paper, we analyze the spatial-temporal patterns ...

    Abstract The spatial-temporal patterns of grain production and consumption have an important influence on the effective national grain supply on condition of tight balance in the total grain amount in China. In this paper, we analyze the spatial-temporal patterns of grain production, consumption and the driving mechanism for their evolution processes in China. The results indicate that both gravity centers of grain production and consumption in China moved toward the northern and eastern regions, almost in the same direction. The coordination of grain production and consumption increased slightly from 1995 to 2007 but decreased from 2000 to 2007. There is a spatial difference between the major districts of output increase and the strong growth potential in grain consumption, which indicates an increasing difficulty in improving the regional coordination of grain production and consumption. The movement of the gravity center of grain production is significantly correlated with regional differences in grain production policy, different economic development models, and spatial disparity of land and water resource use. For grain consumption, the main driving factors include rapid urbanization, the upgrade of food consumption structure, and distribution of food industries.
    Schlagwörter crop production ; food consumption ; food industry ; grain consumption ; issues and policy ; models ; spatial variation ; temporal variation ; urbanization ; China
    Sprache Englisch
    Erscheinungsverlauf 2013-02
    Umfang p. 374-385.
    Erscheinungsort Elsevier B.V.
    Dokumenttyp Artikel
    ZDB-ID 2660426-7
    ISSN 2095-3119
    ISSN 2095-3119
    DOI 10.1016/S2095-3119(13)60236-1
    Datenquelle NAL Katalog (AGRICOLA)

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  6. Artikel ; Online: Price Transmission in China's Swine Industry with an Application of MCM

    Shi-wei XU / Zhe-min LI / Li-guo CUI / Xiao-xia DONG / Fan-tao KONG / Gan-qiong LI

    Journal of Integrative Agriculture, Vol 11, Iss 12, Pp 2097-

    2012  Band 2106

    Abstract: The paper studies the relationship, adjustment ability, path, efficiency and intensity of price transmission in the swine industry chain in China, which consists of the prices of corn, compound feed for fattening pig, piglet, pig and pork. Monthly prices ...

    Abstract The paper studies the relationship, adjustment ability, path, efficiency and intensity of price transmission in the swine industry chain in China, which consists of the prices of corn, compound feed for fattening pig, piglet, pig and pork. Monthly prices covering a period of 18 yr (1994-2011) are analyzed using a Market-Chain Cooperated Model (MCM). The empirical results show that there exists a stable long-term cointegration and short-term dynamic relationship in the price system. First, the adjustment speed of each price series is very slow and the transmission path is top-down and one-way significantly. Second, the price from upstream to downstream lags about 2 mon, while there is no lag in price transmission from midstream to downstream. Third, in terms of price transmission intensity, the price of pig impacted greatly on pork price, not only in the current period but also through the whole period. Besides, the price of corn has the largest lagged effects on pork price. According to the above empirical results, we suggest that government should strengthen monitoring and early warning of the swine industry chain, especially the upstream and midstream, attach great importance to the timely adjustment of feed prices and perfect the measures of price subsidy.
    Schlagwörter price transmission ; Market-Chain Cooperated Model ; swine industry chain ; Agriculture (General) ; S1-972
    Thema/Rubrik (Code) 330
    Sprache Englisch
    Erscheinungsdatum 2012-12-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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