为指导日光温室番茄高产节水优质的灌溉施肥,以番茄为研究对象,设置3种施肥方式(总施肥量相同,施肥时间不同,其中F1:不施底肥,番茄移栽后随水追施总肥量的30%,剩余70%平分6次追肥,F2:底肥施1/2,剩余平分6次追肥,F3:全施底肥不追肥)和3...为指导日光温室番茄高产节水优质的灌溉施肥,以番茄为研究对象,设置3种施肥方式(总施肥量相同,施肥时间不同,其中F1:不施底肥,番茄移栽后随水追施总肥量的30%,剩余70%平分6次追肥,F2:底肥施1/2,剩余平分6次追肥,F3:全施底肥不追肥)和3种土壤水势的灌水下限(W1:-30 k Pa,W2:-50 k Pa,W3:-70 k Pa),研究滴灌条件下水肥耦合对番茄耗水量、产量、水分利用效率和品质的影响.结果表明:施肥方式对番茄的耗水量差异不具有统计学意义,而灌水下限对耗水量有极显著性影响,且耗水量与灌水量呈极显著的正相关关系(P<0.01);与产量最大处理F2W1相比,F2W2处理产量降低6.91%,但节水14.83%,水分利用效率提高8.51%;TTS质量分数与平均单果重呈极显著负相关,而与除糖酸比外其他影响品质指标呈显著性正相关关系;综合考虑产量、WUE及TTS质量分数,利用TOPSIS综合评价方法,确定了温室滴灌条件下番茄节水调质的最优灌溉施肥模式为:移栽前施入底肥为总肥量的50%,移栽后灌水20 mm,进入开花坐果期以后,20 cm土层的土壤水势控制在-50 k Pa以上,每次灌水定额为10 mm,剩余肥料每隔1次灌水追肥1次,将剩余50%的肥料分6次追肥.研究成果为制定日光温室番茄节水高产优质的灌溉模式提供了理论依据.展开更多
Greenhousing is a technique to bridge season gap in vegetable production and has been widely used worldwide. Calculation of water requirement of crops grown in greenhouse and determination of their irrigation schedule...Greenhousing is a technique to bridge season gap in vegetable production and has been widely used worldwide. Calculation of water requirement of crops grown in greenhouse and determination of their irrigation schedules in arid and semi-arid regions are essential for greenhouse maintenance and have thus attracted increased attention over the past decades. The most common method used in the literature to estimate crop evapotranspiration（ET） is the Penman-Monteith（PM） formula. When applied to greenhouse, however, it often uses canopy resistance instead of surface resistance. It is understood that the surface resistance in greenhouse is the result of a combined effect of canopy restriction and soil-surface restriction to water vapor flow, and the relative dominance of one restriction over another depends on crop canopy. In this paper, we developed a surface resistance model in a way similar to two parallel resistances in an electrical circuit to account for both restrictions. Also, considering that wind speed in greenhouse is normally rather small, we compared three methods available in the literature to calculate the aerodynamic resistance, which are the r_a^1 method proposed by Perrier（1975a, b）, the r_a^2 method proposed by Thom and Oliver（1977）, and the r_a^3 method proposed by Zhang and Lemeu（1992）. We validated the model against ET of tomatoes in a greenhouse measured from sap flow system combined with micro-lysimeter in 2015 and with weighing lysimeter in 2016. The results showed that the proposed surface resistance model improved the accuracy of the PM model, especially when the leaf area index was low and the greenhouse was being irrigated. We also found that the aerodynamic resistance calculated from the r_a^1 and r_a^3 methods is applicable to the greenhouse although the latter is slightly more accurate than the former. The proposed surface resistance model, together with the r_a^3 method for aerodynamic resistance, offers an improved approach to estimate ET in greenhouse using the PM formula.展开更多
In this study the principal component analysis (PCA) and geographically weighted regression (GWR) are combined to estimate the spatial distribution of water requirement of the winter wheat in North China while the eff...In this study the principal component analysis (PCA) and geographically weighted regression (GWR) are combined to estimate the spatial distribution of water requirement of the winter wheat in North China while the effect of the macroand micro-topographic as well as the meteorological factors on the crop water requirement is taking into account. The spatial distribution characteristic of the water requirement of the winter wheat in North China and its formation are analyzed based on the spatial variation of the main affecting factors and the regression coefficients. The findings reveal that the collinearity can be effectively removed when PCA is applied to process all of the affecting factors. The regression coefficients of GWR displayed a strong variability in space, which can better explain the spatial differences of the effect of the affecting factors on the crop water requirement. The evaluation index of the proposed method in this study is more efficient than the widely used Kriging method. Besides, it could clearly show the effect of those affecting factors in different spatial locations on the crop water requirement and provide more detailed information on the region where those factors suddenly change. To sum up, it is of great reference significance for the estimation of the regional crop water requirement.展开更多
文摘为指导日光温室番茄高产节水优质的灌溉施肥,以番茄为研究对象,设置3种施肥方式(总施肥量相同,施肥时间不同,其中F1:不施底肥,番茄移栽后随水追施总肥量的30%,剩余70%平分6次追肥,F2:底肥施1/2,剩余平分6次追肥,F3:全施底肥不追肥)和3种土壤水势的灌水下限(W1:-30 k Pa,W2:-50 k Pa,W3:-70 k Pa),研究滴灌条件下水肥耦合对番茄耗水量、产量、水分利用效率和品质的影响.结果表明:施肥方式对番茄的耗水量差异不具有统计学意义,而灌水下限对耗水量有极显著性影响,且耗水量与灌水量呈极显著的正相关关系(P<0.01);与产量最大处理F2W1相比,F2W2处理产量降低6.91%,但节水14.83%,水分利用效率提高8.51%;TTS质量分数与平均单果重呈极显著负相关,而与除糖酸比外其他影响品质指标呈显著性正相关关系;综合考虑产量、WUE及TTS质量分数,利用TOPSIS综合评价方法,确定了温室滴灌条件下番茄节水调质的最优灌溉施肥模式为:移栽前施入底肥为总肥量的50%,移栽后灌水20 mm,进入开花坐果期以后,20 cm土层的土壤水势控制在-50 k Pa以上,每次灌水定额为10 mm,剩余肥料每隔1次灌水追肥1次,将剩余50%的肥料分6次追肥.研究成果为制定日光温室番茄节水高产优质的灌溉模式提供了理论依据.
基金funded by the Science and Technology Innovation Project of Chinese Academy of Agricultural Sciences(FIRI2016-07)
文摘Greenhousing is a technique to bridge season gap in vegetable production and has been widely used worldwide. Calculation of water requirement of crops grown in greenhouse and determination of their irrigation schedules in arid and semi-arid regions are essential for greenhouse maintenance and have thus attracted increased attention over the past decades. The most common method used in the literature to estimate crop evapotranspiration（ET） is the Penman-Monteith（PM） formula. When applied to greenhouse, however, it often uses canopy resistance instead of surface resistance. It is understood that the surface resistance in greenhouse is the result of a combined effect of canopy restriction and soil-surface restriction to water vapor flow, and the relative dominance of one restriction over another depends on crop canopy. In this paper, we developed a surface resistance model in a way similar to two parallel resistances in an electrical circuit to account for both restrictions. Also, considering that wind speed in greenhouse is normally rather small, we compared three methods available in the literature to calculate the aerodynamic resistance, which are the r_a^1 method proposed by Perrier（1975a, b）, the r_a^2 method proposed by Thom and Oliver（1977）, and the r_a^3 method proposed by Zhang and Lemeu（1992）. We validated the model against ET of tomatoes in a greenhouse measured from sap flow system combined with micro-lysimeter in 2015 and with weighing lysimeter in 2016. The results showed that the proposed surface resistance model improved the accuracy of the PM model, especially when the leaf area index was low and the greenhouse was being irrigated. We also found that the aerodynamic resistance calculated from the r_a^1 and r_a^3 methods is applicable to the greenhouse although the latter is slightly more accurate than the former. The proposed surface resistance model, together with the r_a^3 method for aerodynamic resistance, offers an improved approach to estimate ET in greenhouse using the PM formula.
基金supported by the National Basic Research Program of China (2006CB403406)the National Natural Science Foundation of China(51079154)the National HighTech Research & Development Program of China (2011AA100502)
文摘In this study the principal component analysis (PCA) and geographically weighted regression (GWR) are combined to estimate the spatial distribution of water requirement of the winter wheat in North China while the effect of the macroand micro-topographic as well as the meteorological factors on the crop water requirement is taking into account. The spatial distribution characteristic of the water requirement of the winter wheat in North China and its formation are analyzed based on the spatial variation of the main affecting factors and the regression coefficients. The findings reveal that the collinearity can be effectively removed when PCA is applied to process all of the affecting factors. The regression coefficients of GWR displayed a strong variability in space, which can better explain the spatial differences of the effect of the affecting factors on the crop water requirement. The evaluation index of the proposed method in this study is more efficient than the widely used Kriging method. Besides, it could clearly show the effect of those affecting factors in different spatial locations on the crop water requirement and provide more detailed information on the region where those factors suddenly change. To sum up, it is of great reference significance for the estimation of the regional crop water requirement.
