• Title/Summary/Keyword: crop modelling

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Modelling the capture of spray droplets by barley

  • Cox, S.J.;Salt, D.W.;Lee, B.E.;Ford, M.G.
    • Wind and Structures
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    • v.5 no.2_3_4
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    • pp.127-140
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    • 2002
  • This paper presents some of the results of a project whose aim has been to produce a full simulation model which would determine the efficacy of pesticides for use by both farmers and the bio-chemical industry. The work presented here describes how crop architecture can be mathematically modelled and how the mechanics of pesticide droplet capture can be simulated so that if a wind assisted droplet-trajectory model is assumed then droplet deposition patterns on crop surfaces can be predicted. This achievement, when combined with biological response models, will then enable the efficacy of pesticide use to be predicted.

Estimation of the Second Flight Season of Chilo suppressalis (Lepidoptera: Crambidae) Adults in the Northeastern Chinese Areas (중국 동북부 지역에서 이화명나방(Chilo suppressalis)(Crambidae) 2화기 성충 발생 시기 추정)

  • Jung, Jin Kyo;Kim, Eun Young;Yang, Woonho;Lee, Seuk-Ki;Shin, Myeong Na;Yang, Jung-Wook;Ju, Hongguang;Jin, Dongcun;Pao, Jin;Wang, Jichun;Zhu, Feng
    • Korean journal of applied entomology
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    • v.61 no.2
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    • pp.335-347
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    • 2022
  • We investigated the emergence patterns of Chilo suppressalis (Lepidoptera: Crambidae) adults using sex pheromone traps in the three northeastern areas, Dandong (40°07'N 124°23'E) (Liaoning province), and Gongzhuling (43°30'N 124°49') and Longjing (42°46'N 129°26'E) (Jilin province), China, in 2020 and 2021. Two times of adult flight seasons were isolated clearly during the rice growing periods in the all areas, in which the first season from mid May to late July, and the second season from mid July to mid September were observed. The adult emergence seasons in the areas at higher latitude were later than that at lower latitude. Using the adult emergence data during the first flight seasons, the second flight seasons were estimated through insect phenology modelling, and compared with the observed data. Temperature-dependent life history models (developmental rate, development completion, survival rate, adult aging rate, total fecundity, oviposition completion, and adult survival completion) were collected or constructed for each life stage of C. suppressalis, in which the data from the four previous studies were used. Those models were combined in an insect phenology estimation software, PopModel, and operated for the observed areas. In the results, the phenology modelling operated with the models based on the data of shorter larval periods in the previous studies estimated more accurately the second flight seasons. In 2021, we investigated the change of damaged hill ratios of rice with observing the adult emergence at Dandong and Longjing, 2021. The increase periods of damaged hill ratios of rice were observed two times during the total rice cultivation season, which may be caused by different generations of C. suppressalis larvae.

Mathematical Description of Seedling Emergence of Rice and Echinochloa species as Influenced by Soil burial depth

  • Kim Do-Soon;Kwon Yong-Woong;Lee Byun-Woo
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.51 no.4
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    • pp.362-368
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    • 2006
  • A pot experiment was conducted to investigate the effects of soil burial depth on seedling emergences of rice (Oryza sativa) and Echinochloa spp. and to model such effects for mathematical prediction of seedling emergences. When the Gompertz curve was fitted at each soil depth, the parameter C decreased in a logistic form with increasing soil depth, while the parameter M increased in an exponential form and the parameter B appeared to be constant. The Gompertz curve was combined by incorporating the logistic model for the parameter C, the exponential model for the parameter M, and the constant for the parameter B. This combined model well described seedling emergence of rice and Echinochloa species as influenced by soil burial depth and predicted seedling emergence at a given time after sowing and a soil burial depth. Thus, the combined model can be used to simulate seedling emergence of crop sown in different soil depths and weeds present in various soil depths.

Determining the gaps in agricultural information, such as crop phonology, crop moisture status, and drought indices, to improve agrometeorological analyses for agriculture (농업기상분석 향상을 위한 농업정보간 격차 도출)

  • Stone, Roger-C;Peter Hayman;Holger Meinke
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.6 no.2
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    • pp.94-106
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    • 2004
  • Determining those gaps in agricultural and other information to improve agrometeorological analyses for agriculture is a large task. The effective integration of appropriate data systems, including remote sensing systems, with agricultural systems modelling capability is described as a worthy outcome in this endeavour. Data issues, including those associated with data length, quality, maintenance, and archiving remain serious issues to be addressed. The role of remote sensing and geographic information systems in agrometeorology is important and is explored here. The value of simulation models to provide the synthesis for future agrometeorological requirements is further elucidated.

Modelling N Dynamics and Crop Growth in Organic Rice Production Systems using ORYZA2000 (ORYZA2000을 이용한 유기 벼 재배 시스템의 질소 동태 및 벼 생육 모의)

  • Shin, Jae-Hoon;Lee, Sang-Min;Ok, Jung-Hun;Nam, Hong-Sik;Cho, Jung-Lai;An, Nan-Hee;Kim, Kwang-Su
    • Korean Journal of Organic Agriculture
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    • v.25 no.4
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    • pp.805-819
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    • 2017
  • The study was carried out to develop a mathematical model for evaluating the effect of organic fertilizers in organic rice production systems. A function to simulate the nitrogen mineralization process in the paddy soil has been developed and integrated into ORYZA2000 crop growth model. Inorganic nitrogen in the soil was estimated by single exponential models, given temperature and C:N ratio of organic amendments. Data collected from the two-year field experiment were used to evaluate the performance of the model. The revised version of ORYZA2000 provided reasonable estimates of key variables for nitrogen dynamics and crop growth in the organic rice production systems. Coefficient of determination between the measured value and simulated value were 0.6613, 0.8938, and 0.8092, respectively for soil inorganic nitrogen, total dry matter production, and rice yield. This means that the model could be used to quantify nitrogen supplying capacity of organic fertilizers relative to chemical fertilizer. Nitrogen dynamics and rice growth simulated by the model would be useful information to make decision for organic fertilization in organic rice production systems.