Use of thermal and visible imagery for estimating crop water status of irrigated grapevine
Use of thermal and visible imagery for estimating crop water status of irrigated grapevine
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DOI：
10.1093/jxb/erl115
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发表时间：
2007-03-01
影响因子：
6.9
通讯作者：
Cohen, S.
中科院分区：
文献类型：
--
作者：
Moeller, M.;Alchanatis, V.;Cohen, S.
获得高品质的酿酒葡萄取决于在生长季节保持作物轻度至中度水分胁迫的能力。本研究探讨使用热成像监测水胁迫。以酿酒葡萄（葡萄属vinifera cv.梅洛）葡萄园在以色列北方。灌溉处理包括轻度、中度和重度胁迫。热和可见光（RGB）的作物图像拍摄了四天的中午，分别与前视红外热成像系统和数码相机，都安装在卡车起重机15米以上的树冠。在后处理中使用铝十字来匹配可见光图像和热图像，并且使用人工湿表面来估计参考湿温度（T-wet）。作物参数包括茎水势（Psi（stem））、叶导度（g（L））和叶面积指数（LAI）。在2 m高度测量气象参数。CWSI与g（L）高度相关，与Psi（stem）中度相关。CWSI-g（L）关系在整个季节都非常稳定，但CWSI-Psi（茎）的截距和斜率变化很大。后者大概反映了CWSI和PSI（茎）之间的生理关系的非直接性质。CWSI与g（L）关系的最高R-2为0.91（n=12），当CWSI使用冠层中心的温度、人工湿表面的T-wet和空气温度加5 ℃的参考干温度计算时获得。使用由Penman-Monteith方程反演计算的T-wet和由人工增湿的冠层部分估算的T-wet也得到了与g（L）高度相关的作物水分胁迫估算值（R-2分别为0.89和0.82），而使用由气候数据计算的“理论”参考温度的作物水分胁迫指数在季节后期显示出显著的偏差。不同CWSI估计的参数变异性和鲁棒性进行了讨论。未来的研究应致力于将热成像技术发展成为适用于不同作物的灌溉调度工具。
Achieving high quality wine grapes depends on the ability to maintain mild to moderate levels of water stress in the crop during the growing season. This study investigates the use of thermal imaging for monitoring water stress. Experiments were conducted on a wine-grape (Vitis vinifera cv. Merlot) vineyard in northern Israel. Irrigation treatments included mild, moderate, and severe stress. Thermal and visible (RGB) images of the crop were taken on four days at midday with a FLIR thermal imaging system and a digital camera, respectively, both mounted on a truck-crane 15 m above the canopy. Aluminium crosses were used to match visible and thermal images in post-processing and an artificial wet surface was used to estimate the reference wet temperature (T-wet). Monitored crop parameters included stem water potential (Psi(stem)), leaf conductance (g(L)), and leaf area index (LAI). Meteorological parameters were measured at 2 m height. CWSI was highly correlated with g(L) and moderately correlated with Psi(stem). The CWSI-g(L) relationship was very stable throughout the season, but for that of CWSI-Psi(stem) both intercept and slope varied considerably. The latter presumably reflects the non-direct nature of the physiological relationship between CWSI and Psi(stem). The highest R-2 for the CWSI to g(L) relationship, 0.91 (n=12), was obtained when CWSI was computed using temperatures from the centre of the canopy, T-wet from the artificial wet surface, and reference dry temperature from air temperature plus 5 degrees C. Using T-wet calculated from the inverted Penman-Monteith equation and estimated from an artificially wetted part of the canopy also yielded crop water-stress estimates highly correlated with g(L) (R-2=0.89 and 0.82, respectively), while a crop water-stress index using 'theoretical' reference temperatures computed from climate data showed significant deviations in the late season. Parameter variability and robustness of the different CWSI estimates are discussed. Future research should aim at developing thermal imaging into an irrigation scheduling tool applicable to different crops.