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可移動式高通量紫外-可見光熒光儀——MULTIPLEX ON-THE-GO

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具體成交價以合同協(xié)議為準
  • 公司名稱 上海澤泉科技有限公司
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  • 更新時間 2020/11/27 21:11:09
  • 訪問次數(shù) 183

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詳細信息 在線詢價

主要功能

高通量獲取葉綠素、類黃酮、花青素、氮素狀態(tài)及吸收狀況、冠層孔隙度等多個植物表型數(shù)據(jù)和 12 種原始熒光信號。


測量參數(shù)

氮平衡指數(shù)

葉綠素指數(shù)

類黃酮指數(shù)

花青素指數(shù)

冠層孔隙度

氮素吸收利用情況

12 種熒光信號


應用領(lǐng)域

品種篩選

植物生理學

果實成熟期判定

化肥、農(nóng)藥篩選


主要技術(shù)參數(shù)

Multiplex 技術(shù)參數(shù)

測量材料:葉片和果實

測量面積:80 cm2(可定制其他面積)

采集頻率:60 Hz(大可達 200 Hz)

測量距離:200 mm

工作溫度:5 - 45 攝氏度

供電:通過 FA-BOX

輸出:通過 RS232 至 FA-BOX

重量:3 kg

尺寸:170 * 170 mm

防水等級:IP65

FA-BOX 技術(shù)參數(shù)

數(shù)據(jù)分類:兩種(通過短按和長按鍵實現(xiàn))

可兼容不同型號的 GPS、RFID 系統(tǒng)或其他相關(guān)傳感器

連接:1 個 Multiplex;1 個 GPS;4 個 RS232,1 個可選的 CAN

供電:12V DC(可通過車、蓄電池等供電)

用戶界面:包含 4 個功能鍵,以及警告提醒

存儲:USB(16 G)

重量:600 g

尺寸:150 * 105 * 55 mm

防水等級:IP65


選購指南

配置:

Multiplex 傳感器,F(xiàn)A-BOX 數(shù)采和 GPS。


0000.png

Multiplex On-the-go 系統(tǒng)組成


數(shù)據(jù)格式:


數(shù)據(jù)格式.png



應用案例

1.  果實測量


果實測量.png

Multiplex On-the-go 果實測量

果實特性實時描述,制作收獲期地圖,指導選擇性收獲。


2.  葉片測量


葉片測量.png

Multiplex On-the-go 葉片測量

冠層孔隙度調(diào)查;氮素狀態(tài)、吸收情況調(diào)查;缺綠病調(diào)查;脅迫區(qū)域鑒定。


3.  集成至表型平臺測量


表型平臺測量.png

Multiplex On-the-go 集成至表型平臺測量

高通量獲取葉綠素、類黃酮、花青素、氮素狀態(tài)等植物表型測量參數(shù)。


4.  施肥方案篩選

施肥方案對比.jpg

不同施肥方案對比



產(chǎn)地:法國 Force-A



參考文獻

Cerovic ZG, Moise N, Agati G, Latouche G, Ben Ghozlen N, Meyer S(2008). New portable optical sensors for the assessment of winegrape phenolic maturity based on berry fluorescence. J. Food Comp. Anal., 21, 650–654. (Dx & Mx)

Bramley RGV, Le Moigne M, Evain S, Ouzman J, Florin L, Fadaili EM, Hinze CJ, Cerovic ZG(2011). On–the–go sensing of grape berry anthocyanins during commercial harvest: development and prospects. Aust. J. Grape Wine Res. doi:10.1111/j.1755–0238.2011.00158.x. (Mx)

Cerovic ZG, Goutouly JP, Hilbert G, Destrac Irvine A, Martinon V, Moise N(2009). Mapping winegrape quality attributes using portable fluorescence–based sensors. In FRUTIC 09. Conception, Chile. (Ed. S Best) (Progap INIA, Chillian, Chile), 301–310. (Mx)

Zhang Y, Tremblay N, Zhu J(2012). A first comparison of Multiplex® for the assessment of corn nitrogen status. Journal of Food, Agriculture & Environment, 10(1), 1008–1016. (Mx)

Baluja J, Diago M.P, Goovaerts P, Tardaguila J(2012). Assessment of the spatial variability of anthocyanins in grapes using a fluorescence sensor: relationships with vine vigour and yield. Precision Agri., doi: 10.1007/s11119–012–9261–x. (Mx)

Agati G, D'Onofrio C, Ducci E, Cuzzola A, Remorini D, Tuccio L, Lazzini F, Mattii G(2013). Potential of a multiparametric optical sensor for determining in situ the maturity components of red and white vitis vinifera wine grapes. J Agric Food Chem. (Mx)

Bürling K, Cerovic ZG, Cornic G, Ducruet JM, Noga G, Hunsche M(2013). Fluorescence–based sensing of drought–induced stress in the vegetative phase of four contrasting wheat genotypes. Environmental and Experimental Botany. 89, 51–59. (Dx & Mx)

Bahar A, Kapluno T, Zutahy Y, Daus A, Lurie S, Lichter A(2012). Auto-fluorescence for analysis of ripening in Thompson Seedless and colour in Crimson Seedless table grapes. Australian Journal of Grape and Wine Research, 18(3), 353-359.

Matese A, Capraro F, Primicerio J, Gualato G, Di Gennaro SF, Agati G(2013). Mapping of vine vigor by UAV and anthocyanin content by a non–destructive fluorescence technique. Precision Agriculture, 13, 201–208. (Mx)

Baluja J, Diago MP, Goovaerts P, Tardaguila J(2012). Spatio–temporal dynamics of grape anthocyanin accumulation in a Tempranillo vineyard monitored by proximal sensing Australian Journal of Grape and Wine Research, 18(2), 173–182. (Mx)

Giovanni Agatia, Lara Foschi, Nicola Grossi, Marco Volterrani(2015). In field non-invasive sensing of the nitrogen status in hybrid bermudagrass (Cynodon dactylon × C. transvaalensis Burtt Davy) by a fluorescence-based method. European Journal of Agronomy, 63, 89-96.

Longchamps L, Khosla R(2014). Early detection of nitrogen variability in maize using fluorescence. Agronomy Journal. 106(2), 511-518. (Mx)

Bramley R(2012). Mixed fortunes in crop quality sensing. 15th Symposium on Precision Agriculture in Australasia, Mildura, 22-26.

Cerovic ZG, Ben Ghozlen N, Milhade C, Obert M, Debuisson S, Le Moigne M(2015). Non-destructive diagnostic test for nitrogen nutrition of grapevine (Vitis vinifera L.) based on Dualex leaf-clip measurements in the field. Journal of Agricultural and Food Chemistry, 63, 3669–3680. (Dx)

Agati G, Foschi L, Grossi N, Guglielminetti L, Cerovic ZG, Volterrani M(2013). Fluorescence–based versus reflectance proximal sensing of nitrogen content in Paspalum vaginatum and Zoysia matrella turfgrasses. European Journal of Agronomy, 45, 39–51. (Mx)

Diago MP, Rey Carames C, Le Moigne M, Fadaili Em, Tardaguila J, Cerovic ZG(2016). Calibration of non-invasive fluorescence-based sensors for the manual and on-the-go assessment of grapevine vegetative status in the field. Australian Journal of Grape and Wine Research, 22(3), 438-449.

Scoging P, Siko S, Taylor R(2014). Calibration of a hand–held instrument for measuring condensed tannin concentration based on UV– and red–excited fluorescence. African Journal of Range & Forage Science, 31(1),  1–4. (Dx)

Galambo?ová J, Macak M, Zivcak M, Rataj V, Slamka P, Olsovska, K(2014). Comparison of spectral reflectance and multispectrally induced fluorescence to determine winter wheat nitrogen deficit.  (Mx)

Dybro N(2015). Agronomy based crop production system. 2015 ASABE Annual International.

Mercenaro L, Usai G, Fadda C, Nieddu G, del Caro A(2016). Intra-varietal agronomical variability in Vitis vinifera L. cv. Cannonau Investigated by Fluorescence, Texture and Colorimetric Analysis. S. Afr. J. Enol. Vitic.,  37(1), 67-78.

Galambo?ová J, Macák M, ?iv?ák M, Rataj V, Slamka P, Ol?ovská, K. (2014) Comparison of spectral reflectance and multispectrally induced fluorescence to determine winter wheat nitrogen deficit. Advanced Materials Research, 1059, 127-133. (Mx)

Song XY, Wang JH, Gu XH, Xu XG(2015). Winter wheat GPC estimation with fluorescence-based sensor measurements of canopy. SPIE Proceedings, 9637, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII, 96371L , doi:10.1117/12.2195289.

Saiz-Rubio V, Rovira-Mas F(2016). Preliminary Approach for Real-time Mapping of Vineyards from an Autonomous Ground Robot. 2016 ASABE Annual International Meeting.

Peteinatos GG, Korsaeth A, Berge T, Gerhards R(2016). Using Optical Sensors to Identify Water Deprivation, Nitrogen Shortage, Weed Presence and Fungal Infection in Wheat. Agriculture, 6(2), 24, doi:10.3390/agriculture6020024.

Caramés CR(2015). The spatial variability of vegetative status in vineyards using non-destructive sensors.   

Tisseyre B(2012). Sensing systems embedded in machines: towards a better management of operations in viticulture. ISHS Acta Horticulturae 978: I International Workshop on Vineyard Mechanization and Grape and Wine Quality. 10.17660/ActaHortic.2013.978.1.

Zecha CW, Link J, Claupein W(2013). sensor platforms: categorisation and research applications in precision farming. J. Sens. Sens. Syst., 2, 51–72.



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