风胁迫对三种叶菜的机械损伤及预测模型
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摘要
为了研究风害对不同叶菜的影响,本研究通过模拟风洞试验,以上海青,四季小白菜,玻璃生菜3种叶菜为试验材料,分别在5,15,25 m/s风速条件下设置5,10,15 min的风胁迫处理,采用电导率法、伤口染色目测法、伤口色泽L值测定法研究风胁迫对不同种类叶菜造成的机械损伤,并对以上3种测定方法进行了综合评价,进而建立相应的数学模型。结果表明:风速和风胁迫时间两因子均对3种叶菜的相对电导率、目测等级、L值有显著性影响;两者的交互作用对上海青和四季小白菜的相对电导率有显著性影响,但对玻璃生菜的相对电导率无显著影响;另外,两者的交互作用对3种叶菜的目测等级均影响显著,但对3种叶菜的L值影响均不显著。25 m/s和15 m/s风对3种叶菜都可引起显著机械损伤,其中,在25 m/s持续15 min风处理下机械损伤最为严重,在此处理组合下,上海青、四季小白菜和玻璃生菜的相对电导率分别高于对照214.70%,228.96%,266.92%;目测等级分别高于对照2.3,2.4和3.6级;L值分别低于对照21.17%,38.91%,42.73%。显然,与上海青和四季小白菜相比,玻璃生菜更容易受到风害影响。Gauss2D拟合模型中,3种叶菜机械损伤拟合模型的决定系数R2均超过0.95,证明该拟合模型能较好地预测不同叶菜遭受风害后的机械损伤程度,可以为风害机械损伤预测提供理论基础。
Mechanical damage caused by wind may lead to economic loss in the production of leafy vegetables,especially during harvest time. Shanghaiqing,four-season Chinese cabbage,and glass lettuce are planted widely in the southeastern coast of China. However,the magnitude of the mechanical damage caused by wind is uncertain. In addition,the relationship between wind stress and mechanical damage to leaves has rarely been studied. To resolve these problems,three leafy vegetables were used to evaluate the mechanical effects of wind on plants through a simulated wind tunnel. During this experiment,these three species were subjected to ten treatments—a control treatment,three levels of wind speeds( 5 m/s,15 m/s,25 m/s) and three different durations of wind exposure( 5 min,10 min,15 min). To quantify the mechanical damage caused by wind,three detection methods—the conductivity,wound staining visual,and L value measurement methods—were used. Then,a comprehensive assessment method was proposed by evaluating the three detection methods and using them to assess the degree of mechanical damage. Moreover,a Gauss2 D equation was used to establish a prediction model for mechanical damages caused by wind for the three species. The results showed that the relative conductivity,visual level,and L value were significantly affected by wind speed and stress time. The interaction of wind speed and stress timehad significant effects on relative conductivity of Shanghaiqing and four-season Chinese cabbage,while having no significant effect on the relative conductivity of glass lettuce. The interaction of wind speed and stress time had significant effects on visual grade while having no significant effect on L values. Mechanical damage to the three leafy vegetables occurred mainly after being exposed to the 25 m/s and 15 m/s wind conditions,while the 5 m/s wind speed had little effect. For Shanghaiqing,four-season Chinese cabbage,and glass lettuce,the mechanical damage was most serious after exposure to the 25 m/s wind condition for 15 min. The relative conductivities were 214. 70%,228. 96%,266. 92% higher than the control; the visual levels were 2.3,2.4,and 3.6 higher than the control; L values were 21.17%,38.91%,and 42.73%lower than the control,respectively. Among the three leafy vegetables,the glass lettuce was the most susceptible to wind damage according to a comprehensive evaluation of mechanical damage. This susceptibility may be due to the higher leaf water content and lower leaf cellulose content in glass lettuce. Mechanical damage under different wind speeds and wind stress times was fitted by a Gauss2 D function. The higher R2(0.9552—0.9840) showed that these models fit the data well.The mechanical damage caused by wind can be predicted using these prediction models,which provide a reference for leafy vegetable crops,and provide early warning of mechanical damage from wind stress.
Mechanical damage caused by wind may lead to economic loss in the production of leafy vegetables,especially during harvest time. Shanghaiqing,four-season Chinese cabbage,and glass lettuce are planted widely in the southeastern coast of China. However,the magnitude of the mechanical damage caused by wind is uncertain. In addition,the relationship between wind stress and mechanical damage to leaves has rarely been studied. To resolve these problems,three leafy vegetables were used to evaluate the mechanical effects of wind on plants through a simulated wind tunnel. During this experiment,these three species were subjected to ten treatments—a control treatment,three levels of wind speeds( 5 m/s,15 m/s,25 m/s) and three different durations of wind exposure( 5 min,10 min,15 min). To quantify the mechanical damage caused by wind,three detection methods—the conductivity,wound staining visual,and L value measurement methods—were used. Then,a comprehensive assessment method was proposed by evaluating the three detection methods and using them to assess the degree of mechanical damage. Moreover,a Gauss2 D equation was used to establish a prediction model for mechanical damages caused by wind for the three species. The results showed that the relative conductivity,visual level,and L value were significantly affected by wind speed and stress time. The interaction of wind speed and stress timehad significant effects on relative conductivity of Shanghaiqing and four-season Chinese cabbage,while having no significant effect on the relative conductivity of glass lettuce. The interaction of wind speed and stress time had significant effects on visual grade while having no significant effect on L values. Mechanical damage to the three leafy vegetables occurred mainly after being exposed to the 25 m/s and 15 m/s wind conditions,while the 5 m/s wind speed had little effect. For Shanghaiqing,four-season Chinese cabbage,and glass lettuce,the mechanical damage was most serious after exposure to the 25 m/s wind condition for 15 min. The relative conductivities were 214. 70%,228. 96%,266. 92% higher than the control; the visual levels were 2.3,2.4,and 3.6 higher than the control; L values were 21.17%,38.91%,and 42.73%lower than the control,respectively. Among the three leafy vegetables,the glass lettuce was the most susceptible to wind damage according to a comprehensive evaluation of mechanical damage. This susceptibility may be due to the higher leaf water content and lower leaf cellulose content in glass lettuce. Mechanical damage under different wind speeds and wind stress times was fitted by a Gauss2 D function. The higher R2(0.9552—0.9840) showed that these models fit the data well.The mechanical damage caused by wind can be predicted using these prediction models,which provide a reference for leafy vegetable crops,and provide early warning of mechanical damage from wind stress.
引文
[1]王艳红,何维明,于飞海,江洪,余树全,董鸣.植物响应对风致机械刺激研究进展.生态学报,2010,30(3):794-800.
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[4]Schindler D,Bauhus J,Mayer H.Wind effects on trees.European Journal of Forest Research,2012,131(1):159-163.
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[7]孙怀卫,杨金忠,王修贵.塑料大棚气流场模拟及作物蒸腾量计算.农业工程学报,2011,27(11):236-241.
[8]李霞,薛绪掌,王国栋,解迎革,李邵,陈菲.风速对盆栽苋菜蒸腾及物质积累的影响.中国生态农业学报,2009,17(6):1143-1148.
[9]南江,赵晓英,原慧,张琳琳.霸王和木本猪毛菜在遮风和不遮风环境下的表型特征差异.生态学报,2014,34(20):5758-5765.
[10]王林,代永欣,樊兴路,张芸香,黄平,万贤崇.风对黄花蒿水力学性状和生长的影响.生态学报,2015,35(13):4454-4461.
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[14]Moore J R,Watt M S.Modelling the influence of predicted future climate change on the risk of wind damage within New Zealand's planted forests.Global Change Biology,2015,21(8):3021-3035.
[15]Hughes L.Climate change and Australia:trends,projections and impacts.Austral Ecology,2003,28(4):423-443.
[16]Dupont S,Pivato D,Brunet Y.Wind damage propagation in forests.Agricultural and Forest Meteorology,2015,214-215:243-251.
[17]李树岩,王宇翔,胡程达,闫瑛.抽雄期前后大风倒伏对夏玉米生长及产量的影响.应用生态学报,2015,26(8):2405-2413.
[18]Mac Kerron D K L.Wind damage to the surface of strawberry leaves.Annals of Botany,1976,40(2):351-354.
[19]Thompson J R.The effect of wind on grasses II.mechanical damage in Festuca arundinacea schreb.Journal of Experimental Botany,1974,25(5):965-972.
[20]曲浩,赵学勇,岳广阳,王少昆.科尔沁沙地几种常见植物对风胁迫的生理响应.中国沙漠,2009,29(4):668-673.
[21]移小勇,赵哈林,张铜会,李玉强,刘新平,卓鸿.挟沙风对土壤风蚀的影响研究.水土保持学报,2005,19(3):58-61.
[22]Poulikakos L D,Saneinejad S,Gilani M S,Jerjen I,Lehmann E,Derome D.Forced convective drying of wet porous asphalt imaged with neutron radiography.Advanced Engineering Materials,2013,15(11):1136-1145.
[23]宝乐尔其木格.中国沿海风特性研究[D].青岛:中国海洋大学,2011.
[24]李超,魏建苏,严文莲,俞剑蔚,彭小燕.江苏沿海大风特征及其变化分析.气象科学,2013,33(5):584-589.
[25]王巍竹.中国沿海大风阵风系数特征分析.广东科技,2014,(16):139-139.
[26]李合生.植物生理生化实验原理和技术.北京:高等教育出版社,2000.
[27]王向阳,于胜爽,潘炎,吕丽.青菜机械损伤的检测方法研究.北方园艺,2014,(5):26-30.
[28]Van Soest P J,Wine R H.Determination of lignin and cellulose in acid-detergent fiber with permanganate.Journal of the Association of Official Analytical Chemists,1968,51:780-785.
[29]薛桂萍,程辉,张星,吴菊薪.多种评价方法在农业气象灾情评价中的综合应用.中国农业气象,2008,29(3):361-364.
[30]马骏,李昌晓,魏虹,马朋,杨予静,任庆水,张雯.三峡库区生态脆弱性评价.生态学报,2015,35(21):7117-7129.
[31]张国平,郭澎涛,王正银,刘洪斌.紫色土丘陵地区农田土壤养分空间分布预测.农业工程学报,2013,29(6):113-120.
[32]Geeraerd A H,Valdramidis V P,Devlieghere F,Bernaert H,Debevere J,Van Impe J F.Development of a novel approach for secondary modelling in predictive microbiology:incorporation of microbiological knowledge in black box polynomial modelling.International Journal of Food Microbiology,2004,91(3):229-244.
[33]李萍.黄花梨模拟运输振动引起的机械损伤与品质损害[D].杭州:浙江大学,2014.
[34]申江,李超,和晓楠.叶菜类蔬菜公路冷藏运输模拟实验研究.食品科技,2011,36(5):70-79.
[35]李晓娟.鸭梨机械损伤机理及运输包装研究[D].天津:天津科技大学,2008.
[36]陈文烜.水蜜桃、梨减压保鲜技术及机制研究[D].北京:中国农业大学,2015.
[37]杜庆平,李伶利,徐强,陈学好.加工类型黄瓜果实脆度与其组织结构的关系.湖北农业科学,2012,51(5):940-942.
[38]吴志华,李天会,张华林,谢耀坚.沿海防护林树种木麻黄和相思生长和抗风性状比较研究.草业学报,2010,19(4):166-175.
[2]Cleugh H A,Miller J M,B9hm M.Direct mechanical effects of wind on crops.Agroforestry Systems,1998,41(1):85-112.
[3]De Langre E.Effects of wind on plants.Annual Review of Fluid Mechanics,2008,40:141-168.
[4]Schindler D,Bauhus J,Mayer H.Wind effects on trees.European Journal of Forest Research,2012,131(1):159-163.
[5]Grace J.Plant Response to Wind.London:Academic Press,1977.
[6]Russell G,Grace J.The effect of wind on grasses V.leaf extension diffusive conductance photosynthesis in the wind tunnel.Journal of Experimental Botany,1978,29(5):1249-1258.
[7]孙怀卫,杨金忠,王修贵.塑料大棚气流场模拟及作物蒸腾量计算.农业工程学报,2011,27(11):236-241.
[8]李霞,薛绪掌,王国栋,解迎革,李邵,陈菲.风速对盆栽苋菜蒸腾及物质积累的影响.中国生态农业学报,2009,17(6):1143-1148.
[9]南江,赵晓英,原慧,张琳琳.霸王和木本猪毛菜在遮风和不遮风环境下的表型特征差异.生态学报,2014,34(20):5758-5765.
[10]王林,代永欣,樊兴路,张芸香,黄平,万贤崇.风对黄花蒿水力学性状和生长的影响.生态学报,2015,35(13):4454-4461.
[11]张家诚,林之光.中国气候.上海:上海科学技术出版社,1985.
[12]Wurman J,Kosiba K,Robinson P.In situ,Doppler radar,and video observations of the interior structure of a tornado and the wind-damage relationship.Bulletin of the American Meteorological Society,2013,94(6):835-846.
[13]Rae D A,Armbruster W S,Edwards M E,Svengrd-Barre M.Influence of microclimate and species interactions on the composition of plant and invertebrate communities in alpine northern Norway.Acta Oecologica,2006,29(3):266-282.
[14]Moore J R,Watt M S.Modelling the influence of predicted future climate change on the risk of wind damage within New Zealand's planted forests.Global Change Biology,2015,21(8):3021-3035.
[15]Hughes L.Climate change and Australia:trends,projections and impacts.Austral Ecology,2003,28(4):423-443.
[16]Dupont S,Pivato D,Brunet Y.Wind damage propagation in forests.Agricultural and Forest Meteorology,2015,214-215:243-251.
[17]李树岩,王宇翔,胡程达,闫瑛.抽雄期前后大风倒伏对夏玉米生长及产量的影响.应用生态学报,2015,26(8):2405-2413.
[18]Mac Kerron D K L.Wind damage to the surface of strawberry leaves.Annals of Botany,1976,40(2):351-354.
[19]Thompson J R.The effect of wind on grasses II.mechanical damage in Festuca arundinacea schreb.Journal of Experimental Botany,1974,25(5):965-972.
[20]曲浩,赵学勇,岳广阳,王少昆.科尔沁沙地几种常见植物对风胁迫的生理响应.中国沙漠,2009,29(4):668-673.
[21]移小勇,赵哈林,张铜会,李玉强,刘新平,卓鸿.挟沙风对土壤风蚀的影响研究.水土保持学报,2005,19(3):58-61.
[22]Poulikakos L D,Saneinejad S,Gilani M S,Jerjen I,Lehmann E,Derome D.Forced convective drying of wet porous asphalt imaged with neutron radiography.Advanced Engineering Materials,2013,15(11):1136-1145.
[23]宝乐尔其木格.中国沿海风特性研究[D].青岛:中国海洋大学,2011.
[24]李超,魏建苏,严文莲,俞剑蔚,彭小燕.江苏沿海大风特征及其变化分析.气象科学,2013,33(5):584-589.
[25]王巍竹.中国沿海大风阵风系数特征分析.广东科技,2014,(16):139-139.
[26]李合生.植物生理生化实验原理和技术.北京:高等教育出版社,2000.
[27]王向阳,于胜爽,潘炎,吕丽.青菜机械损伤的检测方法研究.北方园艺,2014,(5):26-30.
[28]Van Soest P J,Wine R H.Determination of lignin and cellulose in acid-detergent fiber with permanganate.Journal of the Association of Official Analytical Chemists,1968,51:780-785.
[29]薛桂萍,程辉,张星,吴菊薪.多种评价方法在农业气象灾情评价中的综合应用.中国农业气象,2008,29(3):361-364.
[30]马骏,李昌晓,魏虹,马朋,杨予静,任庆水,张雯.三峡库区生态脆弱性评价.生态学报,2015,35(21):7117-7129.
[31]张国平,郭澎涛,王正银,刘洪斌.紫色土丘陵地区农田土壤养分空间分布预测.农业工程学报,2013,29(6):113-120.
[32]Geeraerd A H,Valdramidis V P,Devlieghere F,Bernaert H,Debevere J,Van Impe J F.Development of a novel approach for secondary modelling in predictive microbiology:incorporation of microbiological knowledge in black box polynomial modelling.International Journal of Food Microbiology,2004,91(3):229-244.
[33]李萍.黄花梨模拟运输振动引起的机械损伤与品质损害[D].杭州:浙江大学,2014.
[34]申江,李超,和晓楠.叶菜类蔬菜公路冷藏运输模拟实验研究.食品科技,2011,36(5):70-79.
[35]李晓娟.鸭梨机械损伤机理及运输包装研究[D].天津:天津科技大学,2008.
[36]陈文烜.水蜜桃、梨减压保鲜技术及机制研究[D].北京:中国农业大学,2015.
[37]杜庆平,李伶利,徐强,陈学好.加工类型黄瓜果实脆度与其组织结构的关系.湖北农业科学,2012,51(5):940-942.
[38]吴志华,李天会,张华林,谢耀坚.沿海防护林树种木麻黄和相思生长和抗风性状比较研究.草业学报,2010,19(4):166-175.