Article(id=1277293323714953487, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1277293236137890180, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1000-2561.2024.11.018, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1712764800000, receivedDateStr=2024-04-11, revisedDate=1713715200000, revisedDateStr=2024-04-22, acceptedDate=null, acceptedDateStr=null, onlineDate=1782460059335, onlineDateStr=2026-06-26, pubDate=1732464000000, pubDateStr=2024-11-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1782460059335, onlineIssueDateStr=2026-06-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1782460059335, creator=13701087609, updateTime=1782460059335, updator=13701087609, issue=Issue{id=1277293236137890180, tenantId=1146029695717560320, journalId=1235980609244409860, year='2024', volume='45', issue='11', pageStart='2243', pageEnd='2486', issueExtLink='null', onlineDate='null', pubDate='1732464000000', pubDateStr='2024-11-25', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1782460038455, creator='13701087609', updateTime=1782815269280, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1278783182988358204, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1277293236137890180, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1278783182988358205, tenantId=1146029695717560320, journalId=1235980609244409860, issueId=1277293236137890180, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=2398, endPage=2406, ext={EN=ArticleExt(id=1277293324084052241, articleId=1277293323714953487, tenantId=1146029695717560320, journalId=1235980609244409860, language=EN, title=Effects of Spraying Parameters for Plant Protection Unmanned Aerial Vehicle on Deposition Distribution of Droplets in Mango Canopy, columnId=1236292524264968282, journalTitle=Chinese Journal of Tropical Crops, columnName=Plant Protection & Bio-safety, runingTitle=null, highlight=null, articleAbstract=

Plant protection unmanned aerial vehicle (UAVs) operational parameters have remarkable effects on droplet distribution in UAVs spraying, which significantly affects pesticide utilization rate and treatment effectiveness. The study was aimed to explore the effects of operating parameters of electric UAVs on droplet deposition distribution in mango trees canopy and to enhance the efficiency of targeted deposition by UAVs. The DJI T40 multi-rotor electric plant protection UAV was used and the main operational parameters including droplet sizes (80, 100, 120 μm), flight height (2.0, 2.5, 3.0 m) and flight speed (3.0, 4.0, 5.0 m/s) were optimized by an orthogonal test. When the droplet size was 80 μm with 2.0 m of flight height and 3.0 m/s of flight speed, the droplet deposition density, coverage rate and uniformity in each canopy of mango trees were significantly larger than those of the other groups. There was a negative correlation between droplet deposition density, coverage rate and flight height, flight speed. The results of range analysis showed that droplet size was the main factor affecting the deposition density of droplet in mango canopy. The flight height was the main factor affecting the coverage rate of spray droplets on the front side of the lower canopy leaves and the back side of the inner canopy leaves of mango trees. The flight speed was the main factor affecting the coverage rate of spray droplets on the back side of the upper canopy leaves of mango trees. The spray diameter of the front and back of the leaves of the other layers was the main factor affecting the droplet coverage rate. The droplet distribution within mango canopy exhibited significant variation, with droplet size being the primary factor determining uniformity, followed by flight speed and flight height. In our current study, according to the droplet deposition density, coverage rate and uniformity in mango canopy, the best operating parameters of T40 multi-rotor electric plant protection UAV were obtained as follows: droplet size of 80 μm, operation height of 2.0 m, and operation speed of 3.0 m/s. It could provide fundamental guidance of the operation of small UAVs for the aerial spraying of mango trees and other similar orchards.

, authors=null, authorsList=Bingjie WANG, Bo PAN, Changyuan DU, Lei JIANG, Yong LIN, Shaoshuai ZHANG, authorCompany=null, correspAuthors=Lei JIANG, Yong LIN, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1277293332816593231, articleId=1277293323714953487, tenantId=1146029695717560320, journalId=1235980609244409860, language=CN, title=植保无人飞机作业参数对雾滴在杧果冠层沉积分布的影响, columnId=1236292524520820846, journalTitle=热带作物学报, columnName=植物保护与生物安全, runingTitle=null, highlight=null, articleAbstract=

植保无人飞机作业参数对无人飞机喷洒过程中的雾滴分布有显著影响,从而影响农药的利用率和病虫害的防治效果。为探究多旋翼植保无人飞机作业参数对杧果树冠层喷雾质量与效果的影响,以提高植保无人飞机施药的对靶高效沉积,本研究应用大疆T40型植保无人飞机采用正交试验对杧果树进行喷雾作业,对主要作业参数雾滴粒径(80、100、120 μm)、作业高度(2.0、2.5、3.0 m)、作业速度(3.0、4.0、5.0 m/s)进行优选。结果表明:施药参数为雾滴粒径80 μm、作业高度2.0 m、作业速度3.0 m/s时,植保无人飞机雾滴在杧果树各个冠层的雾滴沉积密度、覆盖率、雾滴均匀性等均显著大于其他处理组。雾滴沉积密度、覆盖率、作业高度与作业速度呈负相关。极差分析结果显示,雾滴粒径是影响杧果树冠层雾滴沉积密度的主要因素;作业高度是影响杧果树下层叶片正面与内层叶片背面雾滴覆盖率的主要因素;作业速度是影响杧果树上层叶片背面雾滴覆盖率的主要因素;其余各层叶片正面与背面的喷雾粒径是影响雾滴覆盖率的主要因素。植保无人飞机在杧果树冠层的雾滴分布差异性较大,影响雾滴均匀性的主要因素是雾滴粒径,其次是作业速度、作业高度。根据T40多旋翼植保无人飞机在杧果树冠层的雾滴沉积密度、雾滴覆盖率、雾滴均匀性结果综合得到植保无人飞机在杧果树上作业的最佳参数组合为雾滴粒径80 μm,作业高度2.0 m,作业速度3.0 m/s,为小型植保无人飞机在杧果及其他类似果园空中喷洒作业提供指导。

, authors=

王冰洁(1993—),女,硕士,助理研究员,研究方向:现代施药技术与农药毒理。

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* 姜蕾(JIANG Lei),E-mail:
林勇(LIN Yong),E-mail:
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王冰洁(1993—),女,硕士,助理研究员,研究方向:现代施药技术与农药毒理。

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王冰洁(1993—),女,硕士,助理研究员,研究方向:现代施药技术与农药毒理。

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Numerical simulation on gas-liquid phase flow of large-scale plant protection unmanned aerial vehicle spraying[J]. Transactions of the Chinese Society for Agricultural Machinery,2017, 48(9): 62-69. (in Chinese), articleTitle=Numerical simulation on gas-liquid phase flow of large-scale plant protection unmanned aerial vehicle spraying, refAbstract=null)], funds=[Fund(id=1277293346460664224, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, awardId=321MS074, language=CN, fundingSource=海南省自然科学基金项目(321MS074), fundOrder=null, country=null), Fund(id=1277293346510995873, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, awardId=1630042022011, language=CN, fundingSource=中央级公益性科研院所基本科研业务费专项(1630042022011), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1277293333034697041, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, xref=1., ext=[AuthorCompanyExt(id=1277293333043085650, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333034697041, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan 571101, China), AuthorCompanyExt(id=1277293333047279955, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333034697041, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.中国热带农业科学院环境与植物保护研究所,海南海口 571101)]), AuthorCompany(id=1277293333282160980, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, xref=2., ext=[AuthorCompanyExt(id=1277293333290549589, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333282160980, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.Key Laboratory of Integrated Pest Management of Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan 571101, China), AuthorCompanyExt(id=1277293333298938198, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333282160980, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.农业农村部热带作物病虫害综合治理重点实验室,海南海口 571101)]), AuthorCompany(id=1277293333345075543, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, xref=3., ext=[AuthorCompanyExt(id=1277293333353464152, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333345075543, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China), AuthorCompanyExt(id=1277293333361852762, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333345075543, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.华中农业大学植物科学技术学院,湖北武汉 430070)]), AuthorCompany(id=1277293333433155932, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, xref=4., ext=[AuthorCompanyExt(id=1277293333437350237, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333433155932, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan 571101, China), AuthorCompanyExt(id=1277293333449933150, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, companyId=1277293333433155932, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=4.中国热带农业科学院,海南海口 571101)])], figs=[ArticleFig(id=1277293343759532430, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Fig. 1, caption=Schematic diagram of sample, figureFileSmall=PDXo2dMsGAGQlH0AJSUhIQ==, figureFileBig=j/unaMojADIf4+itmMN5oQ==, tableContent=null), ArticleFig(id=1277293344942326159, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=图1, caption=采样示意图, figureFileSmall=PDXo2dMsGAGQlH0AJSUhIQ==, figureFileBig=j/unaMojADIf4+itmMN5oQ==, tableContent=null), ArticleFig(id=1277293345126875536, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 1, caption=

Test factors and levels

, figureFileSmall=null, figureFileBig=null, tableContent=
水平Leve因素Factor
A雾滴粒径Droplet size/μmB作业高度Working height/mC作业速度Working speed/(m·s-1)
1802.03
21002.54
31203.05
), ArticleFig(id=1277293345206567313, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=表1, caption=

试验因素与水平

, figureFileSmall=null, figureFileBig=null, tableContent=
水平Leve因素Factor
A雾滴粒径Droplet size/μmB作业高度Working height/mC作业速度Working speed/(m·s-1)
1802.03
21002.54
31203.05
), ArticleFig(id=1277293345277870482, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 2, caption=

Relevant meteorological parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment风速Wind speed/(m·s-1)温度Temperature/℃湿度Humidity/%
A1B1C10.232.464
A1B2C21.232.861
A1B3C30.833.154
A2B1C21.433.257
A2B2C32.234.354
A2B3C12.335.545
A3B1C31.835.937
A3B2C11.235.241
A3B3C21.035.237
), ArticleFig(id=1277293345437254035, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=表2, caption=

相关气象参数

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment风速Wind speed/(m·s-1)温度Temperature/℃湿度Humidity/%
A1B1C10.232.464
A1B2C21.232.861
A1B3C30.833.154
A2B1C21.433.257
A2B2C32.234.354
A2B3C12.335.545
A3B1C31.835.937
A3B2C11.235.241
A3B3C21.035.237
), ArticleFig(id=1277293345508557204, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 3, caption=

Droplet deposition density under different operating parameters of UAV

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
A1B1C182.433±12.208a71.519±11.199a97.315±4.655a8.936±2.071a23.920±4.705a20.615±0.958a
A1B2C246.364±8.889b48.403±10.565b53.197±1.230b5.742±2.553abc3.524±1.291cd2.607±0.370cd
A1B3C336.911±2.101bc28.153±15.430c22.545±8.022c6.556±3.659ab4.980±0.608cd4.527±0.820bc
A2B1C223.713±1.100de31.165±7.727c21.148±4.435c4.619±0.579bc8.145±2.158bc4.732±1.015b
A2B2C312.805±3.075e29.233±8.352c10.975±2.285de2.915±1.270bc2.826±1.261d4.457±0.843bc
A2B3C117.995±4.983de20.079±1.334c14.855±2.008cde3.580±0.168bc7.335±0.283bc4.910±0.617b
A3B1C315.444±5.769e21.473±4.050c7.378±1.018e2.884±2.411c2.108±1.165d3.288±0.968bcd
A3B2C112.199±3.734e20.539±5.916c7.625±1.405e2.859±1.564c2.353±0.875d1.785±0.428d
A3B3C230.885±5.158cd23.041±6.554c19.663±3.840cd3.489±1.169bc1.976±1.081d2.345±0.688d
), ArticleFig(id=1277293345571471765, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=表3, caption=

无人机不同作业参数下的雾滴沉积密度

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
A1B1C182.433±12.208a71.519±11.199a97.315±4.655a8.936±2.071a23.920±4.705a20.615±0.958a
A1B2C246.364±8.889b48.403±10.565b53.197±1.230b5.742±2.553abc3.524±1.291cd2.607±0.370cd
A1B3C336.911±2.101bc28.153±15.430c22.545±8.022c6.556±3.659ab4.980±0.608cd4.527±0.820bc
A2B1C223.713±1.100de31.165±7.727c21.148±4.435c4.619±0.579bc8.145±2.158bc4.732±1.015b
A2B2C312.805±3.075e29.233±8.352c10.975±2.285de2.915±1.270bc2.826±1.261d4.457±0.843bc
A2B3C117.995±4.983de20.079±1.334c14.855±2.008cde3.580±0.168bc7.335±0.283bc4.910±0.617b
A3B1C315.444±5.769e21.473±4.050c7.378±1.018e2.884±2.411c2.108±1.165d3.288±0.968bcd
A3B2C112.199±3.734e20.539±5.916c7.625±1.405e2.859±1.564c2.353±0.875d1.785±0.428d
A3B3C230.885±5.158cd23.041±6.554c19.663±3.840cd3.489±1.169bc1.976±1.081d2.345±0.688d
), ArticleFig(id=1277293345642774934, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 4, caption=

Range analysis of droplet deposition density

, figureFileSmall=null, figureFileBig=null, tableContent=
项目ItemA雾滴粒径Droplet size
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K1165.708148.074173.05721.23532.42327.748
K254.51380.47646.97811.11418.30614.098
K358.52865.05334.6679.2316.4367.418
55.23649.35857.6867.07810.8089.249
18.17126.82515.6593.7056.1024.699
19.50921.68411.5563.0772.1452.473
极差37.06527.67446.1304.0018.6636.776
较优水平A1A1A1A1A1A1
项目ItemB作业高度Working height
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K1121.589124.156125.84216.43934.17328.632
K271.36898.17471.79711.5168.7038.848
K385.79171.27357.06313.62514.29111.782
40.53041.38541.9475.48011.3919.545
23.78932.72523.9323.8392.9012.949
28.59723.75819.0214.5424.7643.927
极差16.74117.62722.9261.6418.4906.596
较优水平B1B1B1B1B1B1
项目ItemC作业速度Working speed
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层In layer
K1112.626112.136119.79515.37533.60827.310
K2100.961102.60994.00813.85013.6459.683
K365.16078.85840.89812.3559.91412.272
37.54237.37939.9325.12511.2039.103
33.65434.20331.3364.6174.5483.228
21.72026.28613.6334.1183.3054.091
极差15.82211.09326.2991.0077.8985.875
较优水平C1C1C1C1C1C1
), ArticleFig(id=1277293345714078103, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=表4, caption=

雾滴沉积密度极差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
项目ItemA雾滴粒径Droplet size
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K1165.708148.074173.05721.23532.42327.748
K254.51380.47646.97811.11418.30614.098
K358.52865.05334.6679.2316.4367.418
55.23649.35857.6867.07810.8089.249
18.17126.82515.6593.7056.1024.699
19.50921.68411.5563.0772.1452.473
极差37.06527.67446.1304.0018.6636.776
较优水平A1A1A1A1A1A1
项目ItemB作业高度Working height
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K1121.589124.156125.84216.43934.17328.632
K271.36898.17471.79711.5168.7038.848
K385.79171.27357.06313.62514.29111.782
40.53041.38541.9475.48011.3919.545
23.78932.72523.9323.8392.9012.949
28.59723.75819.0214.5424.7643.927
极差16.74117.62722.9261.6418.4906.596
较优水平B1B1B1B1B1B1
项目ItemC作业速度Working speed
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层In layer
K1112.626112.136119.79515.37533.60827.310
K2100.961102.60994.00813.85013.6459.683
K365.16078.85840.89812.3559.91412.272
37.54237.37939.9325.12511.2039.103
33.65434.20331.3364.6174.5483.228
21.72026.28613.6334.1183.3054.091
极差15.82211.09326.2991.0077.8985.875
较优水平C1C1C1C1C1C1
), ArticleFig(id=1277293345852490136, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 5, caption=

Droplet coverage ratio under different operating parameters of UAV

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
A1B1C112.784±0.173a7.248±1.513a11.516±2.514a0.412±0.163a1.077±0.342a0.792±0.104a
A1B2C24.109±0.3343c5.215±2.434ab6.166±1.771b0.219±0.131a0.233±0.132cd0.185±0.079cd
A1B3C34.294±0.193c3.778±2.255b2.140±0.635c0.412±0.139a0.459±0.118bc0.436±0.036b
A2B1C23.099±0.589cd4.269±1.285ab2.658±1.644c0.362±0.027a0.573±0.067b0.284±0.022bcd
A2B2C31.795±0.043d4.654±2.404ab1.310±0.348c0.245±0.080a0.286±0.126cd0.325±0.102bc
A2B3C12.817±1.365cd2.285±0.209b1.843±0.887c0.421±0.131a0.583±0.021b0.323±0.170bc
A3B1C33.479±1.151cd4.969±1.600ab1.255±0.074c0.303±0.125a0.193±0.112d0.394±0.041b
A3B2C12.290±1.218d4.214±2.484ab1.297±0.947c0.395±0.350a0.216±0.050cd0.162±0.098d
A3B3C26.828±1.356b4.515±0.009ab3.084±0.113c0.330±0.052a0.140±0.098d0.132±0.060d
), ArticleFig(id=1277293345919599001, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=表5, caption=

无人机不同作业参数下的雾滴覆盖率

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
A1B1C112.784±0.173a7.248±1.513a11.516±2.514a0.412±0.163a1.077±0.342a0.792±0.104a
A1B2C24.109±0.3343c5.215±2.434ab6.166±1.771b0.219±0.131a0.233±0.132cd0.185±0.079cd
A1B3C34.294±0.193c3.778±2.255b2.140±0.635c0.412±0.139a0.459±0.118bc0.436±0.036b
A2B1C23.099±0.589cd4.269±1.285ab2.658±1.644c0.362±0.027a0.573±0.067b0.284±0.022bcd
A2B2C31.795±0.043d4.654±2.404ab1.310±0.348c0.245±0.080a0.286±0.126cd0.325±0.102bc
A2B3C12.817±1.365cd2.285±0.209b1.843±0.887c0.421±0.131a0.583±0.021b0.323±0.170bc
A3B1C33.479±1.151cd4.969±1.600ab1.255±0.074c0.303±0.125a0.193±0.112d0.394±0.041b
A3B2C12.290±1.218d4.214±2.484ab1.297±0.947c0.395±0.350a0.216±0.050cd0.162±0.098d
A3B3C26.828±1.356b4.515±0.009ab3.084±0.113c0.330±0.052a0.140±0.098d0.132±0.060d
), ArticleFig(id=1277293345999290778, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 6, caption=

Range analysis of droplet coverage ratio

, figureFileSmall=null, figureFileBig=null, tableContent=
项目ItemA雾滴粒径Droplet size
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K121.18716.24019.8221.0431.7691.414
K27.71111.2085.8101.0281.4420.932
K312.59713.6975.6361.0280.5490.688
7.0625.4136.6070.3480.5890.471
2.5703.7361.9370.3430.4800.311
4.1994.5661.8790.3430.1830.229
极差4.4921.6774.7280.0050.4060.242
较优水平A1A1A1A1A1A1
项目ItemB作业高度Working height
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K119.36116.48615.4281.0771.8431.470
K28.19414.0828.7730.8600.7350.672
K313.93910.5777.0671.1631.1820.891
6.4545.4955.1430.3590.6140.490
2.7314.6942.9240.2860.2450.224
4.6473.5262.3560.3880.3940.297
极差3.7231.9702.7870.1020.3690.266
较优水平B1B1B1B3B1B1
项目ItemC作业速度Working speed
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K117.89013.74714.6561.2291.8761.277
K214.03613.99911.9080.9110.9460.602
K39.56913.4004.7040.9590.9381.155
5.9634.5824.8850.4100.6250.426
4.6794.4663.9690.3040.3150.201
3.1904.4671.5680.3200.3130.385
极差2.7730.1163.3170.1060.3120.225
较优水平C1C1C1C1C1C1
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雾滴覆盖率极差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
项目ItemA雾滴粒径Droplet size
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K121.18716.24019.8221.0431.7691.414
K27.71111.2085.8101.0281.4420.932
K312.59713.6975.6361.0280.5490.688
7.0625.4136.6070.3480.5890.471
2.5703.7361.9370.3430.4800.311
4.1994.5661.8790.3430.1830.229
极差4.4921.6774.7280.0050.4060.242
较优水平A1A1A1A1A1A1
项目ItemB作业高度Working height
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K119.36116.48615.4281.0771.8431.470
K28.19414.0828.7730.8600.7350.672
K313.93910.5777.0671.1631.1820.891
6.4545.4955.1430.3590.6140.490
2.7314.6942.9240.2860.2450.224
4.6473.5262.3560.3880.3940.297
极差3.7231.9702.7870.1020.3690.266
较优水平B1B1B1B3B1B1
项目ItemC作业速度Working speed
叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
K117.89013.74714.6561.2291.8761.277
K214.03613.99911.9080.9110.9460.602
K39.56913.4004.7040.9590.9381.155
5.9634.5824.8850.4100.6250.426
4.6794.4663.9690.3040.3150.201
3.1904.4671.5680.3200.3130.385
极差2.7730.1163.3170.1060.3120.225
较优水平C1C1C1C1C1C1
), ArticleFig(id=1277293346158674332, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 7, caption=

Coefficient of variation (CV) of droplet deposition density

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
A1B1C114.80915.6584.78323.17819.6704.649
A1B2C210.78321.8272.31244.44936.64414.194
A1B3C34.53254.80935.58155.80612.19918.115
A2B1C22.98024.79520.97112.53026.48921.451
A2B2C312.96828.57320.82043.56844.62618.923
A2B3C138.9116.64353.9104.6793.85112.559
A3B1C332.05818.86113.80283.61555.27929.448
A3B2C124.17628.80518.42654.70037.19423.996
A3B3C242.27928.44419.52933.50154.71229.353
), ArticleFig(id=1277293346242560413, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=表7, caption=

雾滴沉积密度变异系数

, figureFileSmall=null, figureFileBig=null, tableContent=
处理Treatment叶正面Front of leaf叶背面Back of leaf
上层Upper layer下层Under layer内层Inner layer上层Upper layer下层Under layer内层Inner layer
A1B1C114.80915.6584.78323.17819.6704.649
A1B2C210.78321.8272.31244.44936.64414.194
A1B3C34.53254.80935.58155.80612.19918.115
A2B1C22.98024.79520.97112.53026.48921.451
A2B2C312.96828.57320.82043.56844.62618.923
A2B3C138.9116.64353.9104.6793.85112.559
A3B1C332.05818.86113.80283.61555.27929.448
A3B2C124.17628.80518.42654.70037.19423.996
A3B3C242.27928.44419.52933.50154.71229.353
), ArticleFig(id=1277293346322252190, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=EN, label=Tab. 8, caption=

Range analysis of droplet deposition homogeneity

, figureFileSmall=null, figureFileBig=null, tableContent=
项目ItemA雾滴粒径Droplet sizeB作业高度Working heightC作业速度Working speed
K165.66670.83865.100
K266.54181.16574.541
K3104.69684.90297.263
10.94411.80610.850
11.09013.52712.423
17.44914.15016.211
极差6.5052.3445.361
), ArticleFig(id=1277293346380972447, tenantId=1146029695717560320, journalId=1235980609244409860, articleId=1277293323714953487, language=CN, label=表8, caption=

雾滴沉积均匀性极差分析

, figureFileSmall=null, figureFileBig=null, tableContent=
项目ItemA雾滴粒径Droplet sizeB作业高度Working heightC作业速度Working speed
K165.66670.83865.100
K266.54181.16574.541
K3104.69684.90297.263
10.94411.80610.850
11.09013.52712.423
17.44914.15016.211
极差6.5052.3445.361
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植保无人飞机作业参数对雾滴在杧果冠层沉积分布的影响
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王冰洁 1, 2 , 潘波 1, 2 , 杜长远 3 , 姜蕾 1, 2, * , 林勇 1, 2, * , 张少帅 4
热带作物学报 | 植物保护与生物安全 2024,45(11): 2398-2406
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热带作物学报 |植物保护与生物安全 2024 , 45 (11) : 2398 -2406
植保无人飞机作业参数对雾滴在杧果冠层沉积分布的影响
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王冰洁(1993—),女,硕士,助理研究员,研究方向:现代施药技术与农药毒理。

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王冰洁1, 2, 潘波1, 2, 杜长远3, 姜蕾1, 2, * , 林勇1, 2, * , 张少帅4
作者信息
  • 1.中国热带农业科学院环境与植物保护研究所,海南海口 571101
  • 2.农业农村部热带作物病虫害综合治理重点实验室,海南海口 571101
  • 3.华中农业大学植物科学技术学院,湖北武汉 430070
  • 4.中国热带农业科学院,海南海口 571101
通讯作者:
* 姜蕾(JIANG Lei),E-mail:
林勇(LIN Yong),E-mail:
Effects of Spraying Parameters for Plant Protection Unmanned Aerial Vehicle on Deposition Distribution of Droplets in Mango Canopy
Bingjie WANG1, 2, Bo PAN1, 2, Changyuan DU3, Lei JIANG1, 2, * , Yong LIN1, 2, * , Shaoshuai ZHANG4
Affiliations
  • 1.Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan 571101, China
  • 2.Key Laboratory of Integrated Pest Management of Tropical Crops, Ministry of Agriculture and Rural Affairs, Haikou, Hainan 571101, China
  • 3.College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, China
  • 4.Chinese Academy of Tropical Agricultural Sciences, Haikou, Hainan 571101, China
出版时间: 2024-11-25 doi: 10.3969/j.issn.1000-2561.2024.11.018
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植保无人飞机作业参数对无人飞机喷洒过程中的雾滴分布有显著影响,从而影响农药的利用率和病虫害的防治效果。为探究多旋翼植保无人飞机作业参数对杧果树冠层喷雾质量与效果的影响,以提高植保无人飞机施药的对靶高效沉积,本研究应用大疆T40型植保无人飞机采用正交试验对杧果树进行喷雾作业,对主要作业参数雾滴粒径(80、100、120 μm)、作业高度(2.0、2.5、3.0 m)、作业速度(3.0、4.0、5.0 m/s)进行优选。结果表明:施药参数为雾滴粒径80 μm、作业高度2.0 m、作业速度3.0 m/s时,植保无人飞机雾滴在杧果树各个冠层的雾滴沉积密度、覆盖率、雾滴均匀性等均显著大于其他处理组。雾滴沉积密度、覆盖率、作业高度与作业速度呈负相关。极差分析结果显示,雾滴粒径是影响杧果树冠层雾滴沉积密度的主要因素;作业高度是影响杧果树下层叶片正面与内层叶片背面雾滴覆盖率的主要因素;作业速度是影响杧果树上层叶片背面雾滴覆盖率的主要因素;其余各层叶片正面与背面的喷雾粒径是影响雾滴覆盖率的主要因素。植保无人飞机在杧果树冠层的雾滴分布差异性较大,影响雾滴均匀性的主要因素是雾滴粒径,其次是作业速度、作业高度。根据T40多旋翼植保无人飞机在杧果树冠层的雾滴沉积密度、雾滴覆盖率、雾滴均匀性结果综合得到植保无人飞机在杧果树上作业的最佳参数组合为雾滴粒径80 μm,作业高度2.0 m,作业速度3.0 m/s,为小型植保无人飞机在杧果及其他类似果园空中喷洒作业提供指导。

植保无人飞机  /  杧果  /  作业参数  /  雾滴  /  沉积分布

Plant protection unmanned aerial vehicle (UAVs) operational parameters have remarkable effects on droplet distribution in UAVs spraying, which significantly affects pesticide utilization rate and treatment effectiveness. The study was aimed to explore the effects of operating parameters of electric UAVs on droplet deposition distribution in mango trees canopy and to enhance the efficiency of targeted deposition by UAVs. The DJI T40 multi-rotor electric plant protection UAV was used and the main operational parameters including droplet sizes (80, 100, 120 μm), flight height (2.0, 2.5, 3.0 m) and flight speed (3.0, 4.0, 5.0 m/s) were optimized by an orthogonal test. When the droplet size was 80 μm with 2.0 m of flight height and 3.0 m/s of flight speed, the droplet deposition density, coverage rate and uniformity in each canopy of mango trees were significantly larger than those of the other groups. There was a negative correlation between droplet deposition density, coverage rate and flight height, flight speed. The results of range analysis showed that droplet size was the main factor affecting the deposition density of droplet in mango canopy. The flight height was the main factor affecting the coverage rate of spray droplets on the front side of the lower canopy leaves and the back side of the inner canopy leaves of mango trees. The flight speed was the main factor affecting the coverage rate of spray droplets on the back side of the upper canopy leaves of mango trees. The spray diameter of the front and back of the leaves of the other layers was the main factor affecting the droplet coverage rate. The droplet distribution within mango canopy exhibited significant variation, with droplet size being the primary factor determining uniformity, followed by flight speed and flight height. In our current study, according to the droplet deposition density, coverage rate and uniformity in mango canopy, the best operating parameters of T40 multi-rotor electric plant protection UAV were obtained as follows: droplet size of 80 μm, operation height of 2.0 m, and operation speed of 3.0 m/s. It could provide fundamental guidance of the operation of small UAVs for the aerial spraying of mango trees and other similar orchards.

plant protection UAV  /  mango  /  operational parameters  /  droplet  /  deposition distribution
王冰洁, 潘波, 杜长远, 姜蕾, 林勇, 张少帅. 植保无人飞机作业参数对雾滴在杧果冠层沉积分布的影响. 热带作物学报, 2024 , 45 (11) : 2398 -2406 . DOI: 10.3969/j.issn.1000-2561.2024.11.018
Bingjie WANG, Bo PAN, Changyuan DU, Lei JIANG, Yong LIN, Shaoshuai ZHANG. Effects of Spraying Parameters for Plant Protection Unmanned Aerial Vehicle on Deposition Distribution of Droplets in Mango Canopy[J]. Chinese Journal of Tropical Crops, 2024 , 45 (11) : 2398 -2406 . DOI: 10.3969/j.issn.1000-2561.2024.11.018
杧果被称为“热带水果之王”,是世界上最重要的五大水果之一[1]。我国杧果种植面积位居世界第二,主产区在海南、广西、广东、云南和四川等地[2]。农业农村部农垦局数据显示,2021年我国杧果种植面积为37.46万hm2,产量395.8万t,其中海南的杧果种植面积为6.62万hm2,产量55.5万t。然而,热区高温高湿的气候环境导致病虫草害的滋生蔓延,农药年均使用量也相应地高于温带地区,施药次数与施药作业强度较大。海南杧果种植区多为丘陵山地,传统地面施药方式,包括背负式手动喷雾器和地面机械喷雾器,效率低,劳动强度大,面临严峻挑战[3-4]。并且传统施药器械属于大雾滴、大容量喷洒,农药浪费严重,有效利用率仅为35%左右[5-7]。目前热区果树种植人工成本的30%(甚至更高)为施药作业所消耗,杧果园劳动力短缺与管理技术落后等问题日益突出,植保无人飞机是一种高效的现代化施药器械,合理使用可以及时、快速、有效地对农作物病虫害进行防控,同时也能缓解果园劳动力短缺问题,从而提高农药利用率,实现节本增效[8-10]
大量研究发现,植保无人飞机作业参数对喷雾质量与效果有很大的影响。极飞P20无人飞机作业速度和作业高度越低在火龙果树上的喷雾效果越好[11];影响极飞P20无人飞机雾滴在荔枝树冠层穿透性的主要因素是作业高度[12]。TH-X60油动无人飞机作业高度和作业速度显著影响其在荔枝树上的喷雾效果[13]。六旋翼植保无人飞机不同喷头类型影响樱桃树冠中下层的雾滴沉积分布和均匀性[14]。3WQF120-12无人飞机作业速度越低沉积越多,对不同树形桃树喷雾的均匀性有显著性差异[15]。极飞XP 20无人飞机不同作业参数对库尔勒香梨的授粉有显著差异[16-17]。3WYD-4-22A无人飞机作业速度为2 m/s时,桃树冠层雾滴沉积量最大[18]。韦加JF01-20无人飞机作业速度越低,在苹果树上的喷雾效果越好[19]。极飞XP 20无人飞机作业速度的改变对主干型红枣花期冠层雾滴沉积密度影响最大[20]
小型电动多旋翼植保无人飞机具有使用成本低,操作保养简单,起降灵活,不需要专用的机场等优点,市场占有率较高。因此,本研究以小型四旋翼植保无人飞机(大疆T40)为研究对象,通过3因子3水平正交试验,结合雾滴沉积密度、雾滴覆盖率、均匀性等指标,优选出适用于杧果园的四旋翼无人飞机作业参数,以提高植保无人飞机雾滴在杧果冠层的有效沉积,推动我国果树施药器械与技术向现代化、智能化、轻简化方向发展。
研究对象为春梢生长期的贵妃杧果树(杧果树平均株高2.0 m,果园行距4~6 m)。于2023年4月23日在海南省三亚市崖州区开展试验。
主要设备:大疆T40四旋翼电动无人飞机,载药量为40 L,最大作业速度为7 m/s,最大有效喷幅为11 m,可调离心喷头;AVM-01型风速仪(台湾泰仪电子股份有限公司);LS-204型温湿度仪(中山市朗信电子有限公司);雾滴测试卡(重庆六六山下植保科技有限公司);卫生纸;回形针和自封袋等。
参考植保无人飞机杧果园喷洒情况,设定喷液量为30 L/hm2,喷幅为5 m,设置3个因子(雾滴粒径、作业高度、作业速度),每个变量为3个水平(表1),按照3因子3水平正交设计,设计9组试验,进行T40植保无人飞机杧果园作业参数优化试验。各处理的相关气象参数见表2
随机选择植保无人飞机中间2条航线的3株大小、树形相似的杧果树进行取样,杧果树的上层、下层和内层分别按照图1布设雾滴测试卡。在取样杧果冠层上层和下层的4个方位分别布设1个采样点,内层自上往下布设3个采样点,每株树布设11个采样点,每个采样点分别在叶片正面和背面各布设1张雾滴测试卡,每组试验共布设33个采样点,66张雾滴测试卡。用回形针将雾滴测试卡固定在每个采样点杧果叶片正面和背面。每次试验结束后收集雾滴测试卡。
扫描各个处理组的雾滴测试卡,并参照ZHU等[21]的方法,使用Deposit Scan (V1.2)软件进行分析处理,获得各个处理的雾滴沉积密度及覆盖率。采用SPSS 20.0软件处理数据,使用最小显著性差异法(LSD)比较差异显著性。
变异系数(CV)可以用来表征雾滴沉积的均匀性,若变异系数与雾滴沉积分布的均匀性呈负相关,则CV越小,雾滴沉积分布均匀性越好。变异系数计算公式为:
式中,S为同处理组采集样本标准差;Xi为每个采样点雾滴密度,即覆盖率;为各处理组雾滴密度,即覆盖率平均值;n为各处理组采样点个数。
结果显示,在不同参数下,植保无人飞机雾滴在杧果树各个冠层的沉积密度有显著差异。在各处理中,A1B1C1(雾滴粒径80 μm,作业高度2.0 m,作业速度3.0 m/s)处理的杧果树冠层上层、下层和内层叶片正面和背面的雾滴沉积密度均最大,叶片正面的雾滴沉积密度分别为82.433±18.208、71.519±13.199、97.315±4.655个/cm2,叶片背面的雾滴沉积密度分别为8.936±3.071、23.920±6.705、20.615±0.958个/cm2,显著高于其他处理组(P<0.05,表3)。
由极差分析结果显示,影响杧果树内层叶片正面雾滴沉积密度的因素从大到小依次为:喷雾粒径>作业速度>作业高度。对其余冠层叶片正面与背面雾滴沉积密度的影响从大到小依次为:喷雾粒径>作业高度>作业速度。雾滴粒径是影响杧果树植保无人飞机雾滴沉积密度的主要因素,当雾滴粒径为80 μm,作业高度为2.0 m,作业速度为3.0 m/s时,杧果各冠层的雾滴沉积密度达到最大值(表4)。根据雾滴沉积密度获得无人机的最优作业参数为A1B1C1
表5所示,无人机不同作业参数下,除杧果树下层叶片正面的雾滴覆盖率外,杧果树上、下、内层的雾滴覆盖率有组间显著性差异。在各处理中,A1B1C1(雾滴粒径80 μm,作业高度2.0 m,作业速度3.0 m/s)处理的杧果树冠层上层、下层和内层叶片正面和背面的雾滴覆盖率均最大,叶片正面的雾滴覆盖率分别为(12.784±0.173)%、(7.248±1.513)%和(11.516±2.514)%,叶片背面的雾滴覆盖率分别为(0.412±0.163)%、(1.077±0.342)%和(0.792±0.104)%。
由雾滴覆盖率极差分析结果显示,作业高度是影响杧果树下层叶片正面与内层叶片背面雾滴覆盖率的主要因素,作业速度是影响杧果树上层叶片背面雾滴覆盖率的主要因素,喷雾粒径是影响其余各层叶片正面与背面雾滴覆盖率的主要因素。当无人机作业参数为雾滴粒径80 μm,作业高度2.0 m,作业速度3.0 m/s时,其雾滴覆盖率最优(表6)。雾滴覆盖率与雾滴沉积密度的试验结果一致。
由雾滴沉积密度变异系数(CV)得出,植保无人飞机在杧果树相同冠层水平面的雾滴分布存在较大差异(表7),A1B1C1处理中,其内层叶片正面的均匀性最佳;A1B2C2处理中,其内层叶片正面的均匀性最佳;A2B1C2处理中,其上层叶片正面的均匀性最佳;A2B3C1处理中,其上层叶片背面和下层叶片背面的均匀性均较好;A1B1C1、A2B1C2、A2B3C1处理的冠层综合均匀性相对较好。雾滴沉积密度均匀性极差分析得出,影响雾滴均匀性的因素主要是雾滴粒径,其次是作业速度、作业高度。并且作业参数分别为雾滴粒径80 μm,作业高度2.0 m,作业速度3.0 m/s时,雾滴均匀性最好(表8)。
无人飞机的作业参数对液滴的分布和均匀性有很大影响。在植保无人飞机喷洒过程中,如果忽视作业参数优化,使用过高的飞行速度,或者选用过高的飞行高度,不仅难以达到良好的防治效果,还会增加农药飘移风险[22-25]。本研究通过对雾滴沉积密度、覆盖率、均匀性进行分析,优选出大疆T40型四旋翼无人飞机杧果园作业参数为雾滴粒径80 μm,作业高度2.0 m,作业速度3.0 m/s。植保无人飞机参数的改变,对雾滴在杧果树不同冠层的沉积密度、覆盖率和均匀性均有一定影响。研究发现,植保无人飞机参数的改变,导致雾滴在不同果树不同冠层的分布有显著差异[11-20]
作业速度和作业高度的降低可以有效减少飘移,提高液滴沉积量,从而提高喷洒质量[12]。本研究得出相似的结论,雾滴沉积密度、覆盖率和作业高度、作业速度存在负相关关系。可能是由于杧果采后修剪等农事操作,春梢生长期的贵妃杧果树冠层较薄,植保无人飞机自身旋翼产生的风场对其影响较小。较低的作业高度和作业速度,导致更多的喷雾雾滴向靶标生物运动。然而,由于杧果种植环境、植保无人飞机机型特性、安全和效率问题,操作高度和速度不能过低。有研究发现,飞行速度与植保无人飞机在火龙果[11]、桃树[15]、枣树[20]、小麦[26]和苹果树[19,27]冠层雾滴沉积密度存在负相关关系;随着植保无人飞机作业速度的提高,雾滴飘移风险也随之增大[15,19,28];作业高度较低时,植保无人飞机喷雾液滴在火龙果树[11]、荔枝树[13]的沉积密度较好。本研究发现,植保无人飞机在杧果树冠层的雾滴分布差异较大,影响雾滴均匀性的主要因素是雾滴粒径。本研究结果与试验的天气条件、杧果冠层大小密切相关。也有研究发现,作业高度是影响植保无人飞机液滴在荔枝树上分布均匀性的主要因素[12],可能是因为荔枝树冠层相对较大,植保无人飞机对靶下压风场对其影响较大,所以作业高度是均匀性的主要影响因素。不同果树的冠层特性差异较大,植保无人飞机的施药效果也有差异。
本研究通过对T40多旋翼植保无人飞机在杧果树冠层的雾滴沉积密度、雾滴覆盖率、雾滴均匀性的综合分析,得到适合杧果树的植保无人飞机的最佳作业参数组合,研究结果为小型植保无人飞机在杧果及其他类似果园的空中喷洒作业提供一定的基础指导。
  • 海南省自然科学基金项目(321MS074)
  • 中央级公益性科研院所基本科研业务费专项(1630042022011)
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2024年第45卷第11期
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doi: 10.3969/j.issn.1000-2561.2024.11.018
  • 接收时间:2024-04-11
  • 首发时间:2026-06-26
  • 出版时间:2024-11-25
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  • 收稿日期:2024-04-11
  • 修回日期:2024-04-22
基金
海南省自然科学基金项目(321MS074)
中央级公益性科研院所基本科研业务费专项(1630042022011)
作者信息
    1.中国热带农业科学院环境与植物保护研究所,海南海口 571101
    2.农业农村部热带作物病虫害综合治理重点实验室,海南海口 571101
    3.华中农业大学植物科学技术学院,湖北武汉 430070
    4.中国热带农业科学院,海南海口 571101

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* 姜蕾(JIANG Lei),E-mail:
林勇(LIN Yong),E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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