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Estimating leaf water content at the leaf scale in soybean inoculated with arbuscular mycorrhizal fungi from in situ spectral measurements
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作者 Weiping Kong Wenjiang Huang +4 位作者 Xianfeng Zhou hugh mortimer Lingling Ma Lingli Tang Chuanrong Li 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2019年第6期149-155,共7页
Leaf water content(LWC)of crops is a suitable parameter for evaluation of plant water status and arbuscular mycorrhizal effect on the host plant under drought stress.Remote sensing technology provides an effective ave... Leaf water content(LWC)of crops is a suitable parameter for evaluation of plant water status and arbuscular mycorrhizal effect on the host plant under drought stress.Remote sensing technology provides an effective avenue to estimate LWC in crops.However,few LWC retrieval models have been developed specifically for the arbuscular mycorrhizal inoculated crops.In this study,soybean with inoculation and non-inoculation treatments were planted under the severe drought,moderate drought and normal irrigation levels.The LWC changes under different treatments at the 30 th,45 th and 64 th day after the inoculation were investigated,and the spectral response characteristics of inoculated and non-inoculated soybean leaves under the three drought stresses were analyzed.Five types of spectral variables/indices including:raw spectral reflectance(R),continuum-removed spectral reflectance(R C),difference vegetation index(DVI),normalized difference vegetation index(NDVI)and ratio vegetation index(RVI)were applied to determine the best estimator of LWC.The results indicate that LWC decreased as the aggravating of drought stress levels.However,LWC in inoculated leaves was higher than that in the counterparts under the same drought stress level,and the values of raw reflectance measured at inoculated leaves were lower than the non-inoculated leaves,especially around 1900 nm and 1410 nm.These water spectral features were more evident in the corresponding continuum-removed spectral reflectance.The newly proposed DVI C(2280,1900)index,derived from the continuum-removed spectral reflectance at 2280 nm and the raw spectral reflectance at 1900 nm in DVI type of index,was the most robust for soybean LWC assessment,with R 2 value of 0.72(p<0.01)and root mean square error(RMSE)and mean absolute error(MAE)of 2.12%and 1.75%,respectively.This study provides a means to monitor the mycorrhizal effect on drought-induced crops indirectly and non-destructively. 展开更多
关键词 leaf water content remote sensing arbuscular mycorrhizal fungi DROUGHT CROPS
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A comparative review of the state and advancement of Site-Specific Crop Management in the UK and China
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作者 Zhenhong LI James TAYLOR +10 位作者 Lynn FREWER Chunjiang ZHAO Guijun YANG Zhenhai LI Zhigang LIU Rachel GAULTON Daniel WICKS hugh mortimer Xiao CHENG Chaoqing YU Zhanyi SUN 《Frontiers of Agricultural Science and Engineering》 2019年第2期116-136,共21页
Precision agriculture, and more specifically Site-Specific Crop Management(SSCM), has been implemented in some form across nearly all agricultural production systems over the past 25 years. Adoption has been greatest ... Precision agriculture, and more specifically Site-Specific Crop Management(SSCM), has been implemented in some form across nearly all agricultural production systems over the past 25 years. Adoption has been greatest in developed agricultural countries. In this review article, the current situation of SSCM adoption and application is investigated from the perspective of a developed(UK) and developing(China) agricultural economy. The current state-of-the art is reviewed with an emphasis on developments in position system technology and satellite-based remote sensing. This is augmented with observations on the differences between the use of SSCM technologies and methodologies in the UK and China and discussion of the opportunities for(and limitations to)increasing SSCM adoption in developing agricultural economies. A particular emphasis is given to the role of socio-demographic factors and the application of responsible research and innovation(RRI) in translating agritechnologies into China and other developing agricultural economies. Several key research and development areas are identified that need to be addressed to facilitate the delivery of SSCM as a holistic service into areas with low precision agriculture(PA) adoption. This has implications for developed as well as developing agricultural economies. 展开更多
关键词 REMOTE SENSING DECISION support responsible research and INNOVATION digital soil MAPPING
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