Pub Date : 2021-01-01DOI: 10.2480/AGRMET.D-20-00043
G. Dumbuya, H. Alemayehu, M. Hasan, Maya Matsunami, H. Shimono
In cool climates, low temperature is critical for growth and yield of sweet potato ( Ipomoea batatas L. ) . Despite its negative effects, few studies have quantified the impact. We evaluated effects of soil temperature ( T s ) on growth and yield in sweet potato from 2-year field trials in northern Japan. T s was controlled by three steps using plastic mulch at different colors ( green, black and white ) with different T s ranged in 21~24 ° C especially at early growth before the surface of the mulch covered by plant canopy. Higher T s significantly increased vine elongation, branching, and leaf appearance, and the magnitude of increased by higher T s decreased with proceeding growth stages. Increasing T s significantly increased leaf chlorophyll content and stomatal conductance. Across treatments and years, aboveground biomass was linearly and positively correlated with T s , and 58 g m -2 increased in aboveground biomass was observed per 1 ° C increase in T s . However, final storage root fresh yield was not significantly affected by high T s over years. Increased individual storage root weight at high T s was offset by decreased storage root number. The present quantitative study tested in northern Japan showed that, the enhanced aboveground growth in sweet potato at higher T s especially during early growth did not contribute to increase of storage root yields in cool climates.
在寒冷气候下，低温对甘薯的生长和产量至关重要。． 尽管它有负面影响，但很少有研究对其影响进行量化。通过在日本北部进行的2年田间试验，评价了土壤温度对甘薯生长和产量的影响。在21~24℃范围内，采用不同颜色(绿、黑、白)的地膜分三步控制温度，特别是在覆盖冠层之前的生长早期。高温度显著提高了葡萄的伸长、分枝和叶片外观，且随着生长阶段的推进，高温度增加的幅度逐渐减小。增加T显著提高叶片叶绿素含量和气孔导度。在不同处理和年份，地上生物量与T s呈线性正相关，T s每增加1°C，地上生物量增加58 g m -2。但高温度对最终贮藏根鲜产量的影响不显著。在高温度下，单株储存根重的增加被储存根数的减少所抵消。目前在日本北部进行的定量研究表明，在寒冷气候条件下，高温度条件下甘薯地上部生长的增强，特别是生长早期的增强，对贮藏根产量的增加没有贡献。
{"title":"Effect of soil temperature on growth and yield of sweet potato (Ipomoea batatas L.) under cool climate","authors":"G. Dumbuya, H. Alemayehu, M. Hasan, Maya Matsunami, H. Shimono","doi":"10.2480/AGRMET.D-20-00043","DOIUrl":"https://doi.org/10.2480/AGRMET.D-20-00043","url":null,"abstract":"In cool climates, low temperature is critical for growth and yield of sweet potato ( Ipomoea batatas L. ) . Despite its negative effects, few studies have quantified the impact. We evaluated effects of soil temperature ( T s ) on growth and yield in sweet potato from 2-year field trials in northern Japan. T s was controlled by three steps using plastic mulch at different colors ( green, black and white ) with different T s ranged in 21~24 ° C especially at early growth before the surface of the mulch covered by plant canopy. Higher T s significantly increased vine elongation, branching, and leaf appearance, and the magnitude of increased by higher T s decreased with proceeding growth stages. Increasing T s significantly increased leaf chlorophyll content and stomatal conductance. Across treatments and years, aboveground biomass was linearly and positively correlated with T s , and 58 g m -2 increased in aboveground biomass was observed per 1 ° C increase in T s . However, final storage root fresh yield was not significantly affected by high T s over years. Increased individual storage root weight at high T s was offset by decreased storage root number. The present quantitative study tested in northern Japan showed that, the enhanced aboveground growth in sweet potato at higher T s especially during early growth did not contribute to increase of storage root yields in cool climates.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"38 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69170298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.2480/agrmet.d-20-00025
A. Tani, Tomoki Mochizuki
Many VOCs are reactive in the atmosphere, may produce secondary organic aerosol (SOA), and keep photochemical ozone concentrations high by VOC-involved reactions. Accumulated studies have shown the importance of terrestrial ecosystems which can be sinks and sources of VOCs. The research progress in the exchange of volatile organic compounds (VOCs) between terrestrial ecosystems and the atmosphere was reviewed in this paper. Representative VOCs emitted from terrestrial ecosystems are low-molecular-weight oxygenated VOCs including methanol, acetone, formic and acetic acids, and terpenoids, including isoprene and monoterpenes. Terpenoid emissions have been intensively investigated from the leaf to the canopy level using advanced analytical systems, including proton-transfer-reaction mass spectrometry. Environmental factors, including temperature, light intensity, carbon dioxide and ozone concentrations, and water stress have been reported to affect terpenoid emissions from plants. The combined effects of these environments influence terpenoid emission additively or interactively, and are important in terms of VOC emission estimates against ongoing climate change. Isoprene is most abundantly released into the atmosphere among VOCs; the potential reasons why some plants release such large amounts of carbon as isoprene were summarized in this study. Among oxygenated VOCs, some compounds, including isoprene oxygenates methacrolein and methyl vinyl ketone, are bidirectionally exchanged, and both atmospheric chemical reactions and reactions under oxidative stress in leaves have been regarded as involved in bidirectional VOC exchanges. Bottom-up process-based models and top-down inverse models have been developed to estimate global and local terpenoid emissions. To validate the accuracy and precision of the models, the collection of additional in-situ ground truth data, such as long-term flux measurement data, at various sites is required. Otherwise, these models may still leave large uncertainties compared with CO2 flux models that can be validated with a large number of ground truth flux data.
{"title":"Review: Exchanges of volatile organic compounds between terrestrial ecosystems and the atmosphere","authors":"A. Tani, Tomoki Mochizuki","doi":"10.2480/agrmet.d-20-00025","DOIUrl":"https://doi.org/10.2480/agrmet.d-20-00025","url":null,"abstract":"Many VOCs are reactive in the atmosphere, may produce secondary organic aerosol (SOA), and keep photochemical ozone concentrations high by VOC-involved reactions. Accumulated studies have shown the importance of terrestrial ecosystems which can be sinks and sources of VOCs. The research progress in the exchange of volatile organic compounds (VOCs) between terrestrial ecosystems and the atmosphere was reviewed in this paper. Representative VOCs emitted from terrestrial ecosystems are low-molecular-weight oxygenated VOCs including methanol, acetone, formic and acetic acids, and terpenoids, including isoprene and monoterpenes. Terpenoid emissions have been intensively investigated from the leaf to the canopy level using advanced analytical systems, including proton-transfer-reaction mass spectrometry. Environmental factors, including temperature, light intensity, carbon dioxide and ozone concentrations, and water stress have been reported to affect terpenoid emissions from plants. The combined effects of these environments influence terpenoid emission additively or interactively, and are important in terms of VOC emission estimates against ongoing climate change. Isoprene is most abundantly released into the atmosphere among VOCs; the potential reasons why some plants release such large amounts of carbon as isoprene were summarized in this study. Among oxygenated VOCs, some compounds, including isoprene oxygenates methacrolein and methyl vinyl ketone, are bidirectionally exchanged, and both atmospheric chemical reactions and reactions under oxidative stress in leaves have been regarded as involved in bidirectional VOC exchanges. Bottom-up process-based models and top-down inverse models have been developed to estimate global and local terpenoid emissions. To validate the accuracy and precision of the models, the collection of additional in-situ ground truth data, such as long-term flux measurement data, at various sites is required. Otherwise, these models may still leave large uncertainties compared with CO2 flux models that can be validated with a large number of ground truth flux data.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69170204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.2480/AGRMET.D-20-00047
A. Hama, Kei Tanaka, Bin Chen, A. Kondoh
Use of information and communication technologies, as well as robotics, routinely saves labor and refines agricultural tasks; thus, innovative “smart farming” to maintain and enhance the quality of crops can improve the sustainability of agriculture. When managing crop growth using remote-sensing drones, the normalized difference vegetation index ( NDVI ) ̶ used to assess growth ̶ typically changes depending on sunlight conditions. In this study we have attempted to develop an empirical correction to correct for differences in sunlight conditions in drone NDVI images of paddy rice. Based on observations using a field sensor installed in a paddy field, and considering the effects of morning dew, we determined that 10:00 AM is the most appropriate time for NDVI observations in paddy rice, when the morning dew has largely evaporated. This observation time differs from that used in the radiative transmission models described in previous studies. In the drone observations, sections with lower NDVI were more strongly affected by solar altitude, and thus by time of day. Therefore, we found that when correcting NDVI according to sunlight conditions, it is necessary to adjust the correction parameters depending on the NDVI values. Based on the aforementioned results, we corrected the drone-observed NDVI and succeeded in mitigating the decline in NDVI value associated with changes in sunlight conditions, in terms of both NDVI values and NDVI images, within plots established in the ( Inoue and Yokoyama, 2017; Mee et al. , 2017 ) . The use of satellite data for farming guidance, such as optimizing harvest timing and fertilizer application ( Sakaiya et al. , 2016 ) , is an example of the
信息和通信技术以及机器人技术的使用，通常可以节省劳动力并改进农业任务;因此，保持和提高作物质量的创新“智能农业”可以提高农业的可持续性。当使用遥感无人机管理作物生长时，用于评估生长的归一化植被指数(NDVI)通常会根据阳光条件而变化。在本研究中，我们试图开发一种经验校正，以校正水稻无人机NDVI图像中光照条件的差异。基于安装在稻田中的田间传感器的观测结果，考虑到晨露的影响，我们确定上午10:00是水稻NDVI观测的最合适时间，此时晨露已经大量蒸发。这一观测时间不同于以往研究中描述的辐射传输模式中使用的观测时间。在无人机观测中，NDVI较低的区域受到太阳高度的影响更大，因此受到一天中的时间的影响。因此，我们发现在根据日照条件对NDVI进行校正时，有必要根据NDVI的值来调整校正参数。基于上述结果，我们对无人机观测到的NDVI进行了校正，并成功地在Inoue和Yokoyama, 2017;梅等人，2017)。利用卫星数据进行农业指导，如优化收获时间和施肥(Sakaiya et al.， 2016)，就是一个例子
{"title":"Examination of appropriate observation time and correction of vegetation index for drone-based crop monitoring","authors":"A. Hama, Kei Tanaka, Bin Chen, A. Kondoh","doi":"10.2480/AGRMET.D-20-00047","DOIUrl":"https://doi.org/10.2480/AGRMET.D-20-00047","url":null,"abstract":"Use of information and communication technologies, as well as robotics, routinely saves labor and refines agricultural tasks; thus, innovative “smart farming” to maintain and enhance the quality of crops can improve the sustainability of agriculture. When managing crop growth using remote-sensing drones, the normalized difference vegetation index ( NDVI ) ̶ used to assess growth ̶ typically changes depending on sunlight conditions. In this study we have attempted to develop an empirical correction to correct for differences in sunlight conditions in drone NDVI images of paddy rice. Based on observations using a field sensor installed in a paddy field, and considering the effects of morning dew, we determined that 10:00 AM is the most appropriate time for NDVI observations in paddy rice, when the morning dew has largely evaporated. This observation time differs from that used in the radiative transmission models described in previous studies. In the drone observations, sections with lower NDVI were more strongly affected by solar altitude, and thus by time of day. Therefore, we found that when correcting NDVI according to sunlight conditions, it is necessary to adjust the correction parameters depending on the NDVI values. Based on the aforementioned results, we corrected the drone-observed NDVI and succeeded in mitigating the decline in NDVI value associated with changes in sunlight conditions, in terms of both NDVI values and NDVI images, within plots established in the ( Inoue and Yokoyama, 2017; Mee et al. , 2017 ) . The use of satellite data for farming guidance, such as optimizing harvest timing and fertilizer application ( Sakaiya et al. , 2016 ) , is an example of the","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69170305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.2480/AGRMET.D-20-00036
Minseok Kang, Sungsik Cho
The eddy covariance (EC) technique-based observation system allows for researchers to determine latent and sensible heat fluxes, which are key components of the surface energy balance. The number of water and energy flux studies in Asia has increased as the number of flux measurement sites and the length of the observation periods have grown. To retrace the footprints of the AsiaFlux network and predict future research directions, we reviewed the progress in water and energy flux studies in Asia from the 1990s to the present day. This included studies on continuous evapotranspiration (ET) and surface energy balance measurements in various ecosystems, from the tropics to the polar regions. We also reviewed comparative experiments between the EC technique and other observation techniques including the use of a lysimeter or scintillometer, data processing techniques, connections between carbon and water fluxes, and multi-site syntheses. This paper discusses three remaining challenges that are hindering the derivation of scientific knowledge for ET and the surface energy balance, namely: the non-closure of the surface energy budget, imperfect compatibility between openand closed-path gas analyzers, and difficulty in partitioning ET into evaporation and transpiration. If we leverage the advantages of the EC technique (i.e., high sampling rates of ≥ 10 Hz and continuous measurement capabilities), standardized methods for correcting and partitioning can be developed in the near future.
{"title":"Progress in water and energy flux studies in Asia: A review focused on eddy covariance measurements","authors":"Minseok Kang, Sungsik Cho","doi":"10.2480/AGRMET.D-20-00036","DOIUrl":"https://doi.org/10.2480/AGRMET.D-20-00036","url":null,"abstract":"The eddy covariance (EC) technique-based observation system allows for researchers to determine latent and sensible heat fluxes, which are key components of the surface energy balance. The number of water and energy flux studies in Asia has increased as the number of flux measurement sites and the length of the observation periods have grown. To retrace the footprints of the AsiaFlux network and predict future research directions, we reviewed the progress in water and energy flux studies in Asia from the 1990s to the present day. This included studies on continuous evapotranspiration (ET) and surface energy balance measurements in various ecosystems, from the tropics to the polar regions. We also reviewed comparative experiments between the EC technique and other observation techniques including the use of a lysimeter or scintillometer, data processing techniques, connections between carbon and water fluxes, and multi-site syntheses. This paper discusses three remaining challenges that are hindering the derivation of scientific knowledge for ET and the surface energy balance, namely: the non-closure of the surface energy budget, imperfect compatibility between openand closed-path gas analyzers, and difficulty in partitioning ET into evaporation and transpiration. If we leverage the advantages of the EC technique (i.e., high sampling rates of ≥ 10 Hz and continuous measurement capabilities), standardized methods for correcting and partitioning can be developed in the near future.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69170288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.2480/agrmet.d-20-00034
R. Matsuda, Kota Hayano, T. Kawashima, K. Fujiwara
Neural network ( NN ) models with environmental data and the extent of ventilator openings as inputs have the potential to estimate the number of air exchanges per hour ( N ) in real time of a naturally ventilated greenhouse. In this study, the intraseasonal and interseasonal applicability of an NN model was verified: whether the model trained in a specific period can be applied to different periods of the same and other seasons. First, the effect of data collection periods for model training and test within the same season on the estimation accuracy of N was examined. The estimation accuracy was lowered even though the model was applied to a period immediately following that used for model training. Adjusting the training dataset so that the relative distribution of the temperature difference inside and outside the greenhouse ( ∆ T ) approaches the relative distribution of the test dataset improves the estimation accuracy slightly. However, when the model was applied to interseasonal data, such training data adjustments did not improve the estimation accuracy. This indicates that the NN model needs to be further improved for practical use to estimate N of naturally ventilated greenhouses.
{"title":"Intraseasonal and interseasonal applicability of a neural network model for real-time estimation of the number of air exchanges per hour of a naturally ventilated greenhouse","authors":"R. Matsuda, Kota Hayano, T. Kawashima, K. Fujiwara","doi":"10.2480/agrmet.d-20-00034","DOIUrl":"https://doi.org/10.2480/agrmet.d-20-00034","url":null,"abstract":"Neural network ( NN ) models with environmental data and the extent of ventilator openings as inputs have the potential to estimate the number of air exchanges per hour ( N ) in real time of a naturally ventilated greenhouse. In this study, the intraseasonal and interseasonal applicability of an NN model was verified: whether the model trained in a specific period can be applied to different periods of the same and other seasons. First, the effect of data collection periods for model training and test within the same season on the estimation accuracy of N was examined. The estimation accuracy was lowered even though the model was applied to a period immediately following that used for model training. Adjusting the training dataset so that the relative distribution of the temperature difference inside and outside the greenhouse ( ∆ T ) approaches the relative distribution of the test dataset improves the estimation accuracy slightly. However, when the model was applied to interseasonal data, such training data adjustments did not improve the estimation accuracy. This indicates that the NN model needs to be further improved for practical use to estimate N of naturally ventilated greenhouses.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69170286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.2480/AGRMET.D-20-00038
Y. Ishigooka, T. Hasegawa, T. Kuwagata, M. Nishimori, Hitomi Wakatsuki
Rice is the most important cereal crop in Japan, and therefore the impact of projected climate change on its production and quality has been assessed using rice growth models accounting for the effects of rising temperature and atmospheric CO 2 concentration ( [CO 2 ] ) on important growth processes. Recent experimental studies, however, have shown some negative effects of interactions between [CO 2 ] and temperature on yield and quality of rice which were not accounted for by previous impact assessments. This study examined the importance of [CO 2 ] × temperature interactions in the nationwide impacts of climate change on grain yield and quality of rice in Japan by 2100. We introduced new functions accounting for the effects of interactions on yield. Then we adopted the acceleration by elevated [CO 2 ] in the estimation of the occurrence of chalky grains, an indicator of appearance quality of rice. We applied the modified model to Japan at a spatial resolution of 1 km using 10 climate scenarios ( 5 Global Circulation Models × 2 representative concentration pathways [RCPs] ) from 1981 to 2100. The effects of the newly introduced negative effects of [CO 2 ] × temperature were evaluated by comparing simulations with and without the interaction in each scenario. Nationwide production was estimated to decrease by up to 28 % and the percentage of white chalky grains to increase up to 16 % relative to the previous assessment results, especially in RCP8.5, in which larger increases were projected in both temperature and [CO 2 ]. The result suggests that the positive effect of elevated [CO 2 ], which had been expected to offset the negative effect of increased temperature on rice productivity, may be limited in the future, and rice quality degradation may be more severe than predicted previously.
{"title":"Revision of estimates of climate change impacts on rice yield and quality in Japan by considering the combined effects of temperature and CO2 concentration","authors":"Y. Ishigooka, T. Hasegawa, T. Kuwagata, M. Nishimori, Hitomi Wakatsuki","doi":"10.2480/AGRMET.D-20-00038","DOIUrl":"https://doi.org/10.2480/AGRMET.D-20-00038","url":null,"abstract":"Rice is the most important cereal crop in Japan, and therefore the impact of projected climate change on its production and quality has been assessed using rice growth models accounting for the effects of rising temperature and atmospheric CO 2 concentration ( [CO 2 ] ) on important growth processes. Recent experimental studies, however, have shown some negative effects of interactions between [CO 2 ] and temperature on yield and quality of rice which were not accounted for by previous impact assessments. This study examined the importance of [CO 2 ] × temperature interactions in the nationwide impacts of climate change on grain yield and quality of rice in Japan by 2100. We introduced new functions accounting for the effects of interactions on yield. Then we adopted the acceleration by elevated [CO 2 ] in the estimation of the occurrence of chalky grains, an indicator of appearance quality of rice. We applied the modified model to Japan at a spatial resolution of 1 km using 10 climate scenarios ( 5 Global Circulation Models × 2 representative concentration pathways [RCPs] ) from 1981 to 2100. The effects of the newly introduced negative effects of [CO 2 ] × temperature were evaluated by comparing simulations with and without the interaction in each scenario. Nationwide production was estimated to decrease by up to 28 % and the percentage of white chalky grains to increase up to 16 % relative to the previous assessment results, especially in RCP8.5, in which larger increases were projected in both temperature and [CO 2 ]. The result suggests that the positive effect of elevated [CO 2 ], which had been expected to offset the negative effect of increased temperature on rice productivity, may be limited in the future, and rice quality degradation may be more severe than predicted previously.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69170291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-01DOI: 10.2480/agrmet.d-21-00005
K. Yoshikawa, K. Takagi, T. Yazaki, T. Hirano, Shintaro Hayakashi, R. Ide, H. Oguma, Yasuo Hirose, J. Kurihara
Liquid crystal tunable filter ( LCTF ) can change the transmissible wavelength by changing the applied voltage to the filter, which enables the drastic increase in the observable wavelength resolution in a small size system and is considered to be a powerful tool for the spectral earth observation from flying units or microsatellites. However, there is limited knowledge about its season-long application for the vegetation monitoring and the prediction of the ecosystem photosynthetic capacity. We compared the seasonal variation of spectral reflectance obtained by a LCTF camera with that obtained by a popular spectral radiometer in a cool-temperate young larch plantation in northern Hokkaido, Japan. Then we tried to find the best normalized difference spectral index ( NDSI ) to explain the seasonal variation of the ecosystem photosynthetic capacity using all pairs of two reflectances observed in the range of wavelength between 500 and 770 nm with 10-nm intervals ( 28 wavelength bands ) by the LCTF. The best NDSI among all combinations ( 28 × 27 ) of two reflectances was NDSI[770, 720] for the maximum gross primary production at light saturation and NDSI[530, 600] for the initial slope of the light-response curve, which reflect the red edge shift owing to the change in the chlorophyll content and relative strength of the light absorbance in the visible red wavelength region compared with that in the green wavelength region, respectively. Predicted daily gross primary production of the plantation using these NDSI agreed well with the observed values. NDSI[530, 600] was better to distinguish each vegetation type of the studied plantation.
{"title":"Exploring a best vegetation index to explain the seasonal variation of a forest photosynthesis using a hyper-spectral camera equipped with liquid crystal tunable filter","authors":"K. Yoshikawa, K. Takagi, T. Yazaki, T. Hirano, Shintaro Hayakashi, R. Ide, H. Oguma, Yasuo Hirose, J. Kurihara","doi":"10.2480/agrmet.d-21-00005","DOIUrl":"https://doi.org/10.2480/agrmet.d-21-00005","url":null,"abstract":"Liquid crystal tunable filter ( LCTF ) can change the transmissible wavelength by changing the applied voltage to the filter, which enables the drastic increase in the observable wavelength resolution in a small size system and is considered to be a powerful tool for the spectral earth observation from flying units or microsatellites. However, there is limited knowledge about its season-long application for the vegetation monitoring and the prediction of the ecosystem photosynthetic capacity. We compared the seasonal variation of spectral reflectance obtained by a LCTF camera with that obtained by a popular spectral radiometer in a cool-temperate young larch plantation in northern Hokkaido, Japan. Then we tried to find the best normalized difference spectral index ( NDSI ) to explain the seasonal variation of the ecosystem photosynthetic capacity using all pairs of two reflectances observed in the range of wavelength between 500 and 770 nm with 10-nm intervals ( 28 wavelength bands ) by the LCTF. The best NDSI among all combinations ( 28 × 27 ) of two reflectances was NDSI[770, 720] for the maximum gross primary production at light saturation and NDSI[530, 600] for the initial slope of the light-response curve, which reflect the red edge shift owing to the change in the chlorophyll content and relative strength of the light absorbance in the visible red wavelength region compared with that in the green wavelength region, respectively. Predicted daily gross primary production of the plantation using these NDSI agreed well with the observed values. NDSI[530, 600] was better to distinguish each vegetation type of the studied plantation.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69170377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-10DOI: 10.2480/agrmet.d-20-00027
K. Murakami, T. Hirota, S. Shimoda, T. Yazaki
Interactions between boundary layer wind and topography form non-uniform air temperature distributions in cold and snow-covered regions. Because of this heterogeneity, spatially interpolated air temperatures sometimes deviate from observed values. To evaluate the quality of spatially interpolated daily mean temperatures (Tint) provided by a 1 km gridded meteorological data service (Ohno et al., 2016), we collected observed temperatures (Tobs) obtained at meteorological observation sites located near farmland in the Tokachi and Okhotsk regions̶in eastern Hokkaido, Japan̶in winter (October-March) and revisited the bias in the interpolated temperatures (dT). The root-mean-square error (RMSE) of Tint obtained at 88 sites was 1.16°C, and the absolute median dT values were greater than 1°C at 14 sites. The variance of dT was greater on cold and calm days, suggesting the involvement of radiative cooling and the accumulation of cold air parcels. To correct Tint by estimating dT at a given site by considering the formation mechanisms of the temperature distributions, we attempted to develop a multimodal machine learning model that had four predictors: surface and boundary layer meteorological data and topographical and geographical features around each site. To analyze the influence of the spatial extent of the topography and geography around each site, we compared models having these predictors with various sizes of the region of interest (ROI). By training the models and applying them to an independent test dataset, it has been shown that bias correction using models with a small topographical ROI (30×30 km or smaller) reduced the RMSE. The RMSE of the test dataset decreased by ~0.1°C via the application of a nested model, suggesting the potential usefulness of the presented approach for locally confined meteorological events. However, the biases were increased at several sites by application of the models, thus implying that further improvement is essential for practical use.
在寒冷和积雪地区，边界层风和地形的相互作用形成了不均匀的气温分布。由于这种异质性，空间插值的气温有时会偏离观测值。为了评估由1公里网格气象数据服务(Ohno et al.， 2016)提供的空间插值日平均温度(Tint)的质量，我们收集了冬季(10月至3月)在日本北海道东部的德立和鄂霍次克地区农田附近的气象观测点获得的观测温度(Tobs)，并重新研究了插值温度(dT)的偏差。88个位点Tint的均方根误差(RMSE)为1.16°C, 14个位点dT的绝对中位数大于1°C。在冷天和无风天，dT的方差更大，表明辐射冷却和冷空气包裹的积累参与了这一过程。为了通过考虑温度分布的形成机制来估计给定站点的dT来纠正Tint，我们试图开发一个多模态机器学习模型，该模型具有四个预测因子:地表和边界层气象数据以及每个站点周围的地形和地理特征。为了分析每个站点周围地形和地理空间范围的影响，我们将具有这些预测因子的模型与不同大小的感兴趣区域(ROI)进行了比较。通过训练模型并将其应用于独立的测试数据集，已经表明使用具有较小地形ROI (30×30 km或更小)的模型进行偏差校正可以降低RMSE。通过应用嵌套模型，测试数据集的RMSE降低了~0.1°C，这表明所提出的方法对局部受限的气象事件可能有用。然而，由于模型的应用，在一些地点的偏差增加了，这意味着进一步的改进对于实际使用是必不可少的。
{"title":"Bias correction for spatially interpolated daily mean air temperature during winter in eastern Hokkaido using multimodal machine learning","authors":"K. Murakami, T. Hirota, S. Shimoda, T. Yazaki","doi":"10.2480/agrmet.d-20-00027","DOIUrl":"https://doi.org/10.2480/agrmet.d-20-00027","url":null,"abstract":"Interactions between boundary layer wind and topography form non-uniform air temperature distributions in cold and snow-covered regions. Because of this heterogeneity, spatially interpolated air temperatures sometimes deviate from observed values. To evaluate the quality of spatially interpolated daily mean temperatures (Tint) provided by a 1 km gridded meteorological data service (Ohno et al., 2016), we collected observed temperatures (Tobs) obtained at meteorological observation sites located near farmland in the Tokachi and Okhotsk regions̶in eastern Hokkaido, Japan̶in winter (October-March) and revisited the bias in the interpolated temperatures (dT). The root-mean-square error (RMSE) of Tint obtained at 88 sites was 1.16°C, and the absolute median dT values were greater than 1°C at 14 sites. The variance of dT was greater on cold and calm days, suggesting the involvement of radiative cooling and the accumulation of cold air parcels. To correct Tint by estimating dT at a given site by considering the formation mechanisms of the temperature distributions, we attempted to develop a multimodal machine learning model that had four predictors: surface and boundary layer meteorological data and topographical and geographical features around each site. To analyze the influence of the spatial extent of the topography and geography around each site, we compared models having these predictors with various sizes of the region of interest (ROI). By training the models and applying them to an independent test dataset, it has been shown that bias correction using models with a small topographical ROI (30×30 km or smaller) reduced the RMSE. The RMSE of the test dataset decreased by ~0.1°C via the application of a nested model, suggesting the potential usefulness of the presented approach for locally confined meteorological events. However, the biases were increased at several sites by application of the models, thus implying that further improvement is essential for practical use.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"76 1","pages":"164-173"},"PeriodicalIF":1.3,"publicationDate":"2020-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44442735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-07DOI: 10.21203/rs.3.rs-86157/v1
Yuanhao Chen, R. Matsuda, K. Fujiwara
BackgroundPhosphor-converted white LEDs (PCW-LEDs) of numerous types with different relative spectral photon-flux-density distributions (SPDs) are commercially available today. Some are regarded as promising light sources for plant factories with artificial lighting. Therefore, some methods must be developed for rapidly selecting appropriate ones from numerous types of PCW-LEDs with relevant evaluation criteria. For rapid determination of leaf net photosynthetic rates (Pn) under dozens of PCW-LED lights with different SPDs, we have developed a rapid and mostly automated Pn-quantification method.ResultsThe method uses a modified LED-artificial sunlight source system (LASS system) and a Pn-measurement system. The modified LASS system includes LEDs of 30 types with different relative SPDs: monochromatic LEDs of 27 types (426–826 nm peak wavelengths) and PCW-LEDs of three types. The system combines the LED lights to produce light with an SPD, which can accurately approximate that of any PCW-LED light at a photosynthetic photon flux density (PPFD) of 150 μmol m−2 s−1. The Pn-quantification method includes two steps: Step 1 – producing the selected PCW-LED lights; Step 2 – using the modified LASS system to supply all the produced lights automatically and successively to an identical leaf and simultaneously measuring Pn using a Pn-measurement system. We produced PCW-LED lights of 30 types at a PPFD of 150 μmol m−2 s−1 within 2.5 h. Then we individually measured the Pn of cos lettuce, red-leaf lettuce, and green-leaf lettuce (Lactuca sativa L.) plants under all produced lights in 16 h per cultivar per repetition. Results show that the mean Pn values of the cos lettuce, red-leaf lettuce, and green-leaf lettuce under the 30 produced lights were, respectively, 7.11–8.02, 5.76–7.11, and 4.83–6.17 μmol m−2 s−1 at 20 days after sowing.ConclusionsA rapid and greatly automated method was developed for successive measurement of Pn under dozens of combined lights, of which each SPD approximated that of the selected PCW-LED lights, within days, which indicates that the method can determine the Pn quickly under numerous PCW-LED lights. Consequently, it contributes to the rapid selection of PCW-LED lights performing high Pn.
{"title":"Rapid and automated leaf net photosynthetic rate determination for numerous phosphor-converted white-LED lights of different spectral distributions","authors":"Yuanhao Chen, R. Matsuda, K. Fujiwara","doi":"10.21203/rs.3.rs-86157/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-86157/v1","url":null,"abstract":"\u0000 BackgroundPhosphor-converted white LEDs (PCW-LEDs) of numerous types with different relative spectral photon-flux-density distributions (SPDs) are commercially available today. Some are regarded as promising light sources for plant factories with artificial lighting. Therefore, some methods must be developed for rapidly selecting appropriate ones from numerous types of PCW-LEDs with relevant evaluation criteria. For rapid determination of leaf net photosynthetic rates (Pn) under dozens of PCW-LED lights with different SPDs, we have developed a rapid and mostly automated Pn-quantification method.ResultsThe method uses a modified LED-artificial sunlight source system (LASS system) and a Pn-measurement system. The modified LASS system includes LEDs of 30 types with different relative SPDs: monochromatic LEDs of 27 types (426–826 nm peak wavelengths) and PCW-LEDs of three types. The system combines the LED lights to produce light with an SPD, which can accurately approximate that of any PCW-LED light at a photosynthetic photon flux density (PPFD) of 150 μmol m−2 s−1. The Pn-quantification method includes two steps: Step 1 – producing the selected PCW-LED lights; Step 2 – using the modified LASS system to supply all the produced lights automatically and successively to an identical leaf and simultaneously measuring Pn using a Pn-measurement system. We produced PCW-LED lights of 30 types at a PPFD of 150 μmol m−2 s−1 within 2.5 h. Then we individually measured the Pn of cos lettuce, red-leaf lettuce, and green-leaf lettuce (Lactuca sativa L.) plants under all produced lights in 16 h per cultivar per repetition. Results show that the mean Pn values of the cos lettuce, red-leaf lettuce, and green-leaf lettuce under the 30 produced lights were, respectively, 7.11–8.02, 5.76–7.11, and 4.83–6.17 μmol m−2 s−1 at 20 days after sowing.ConclusionsA rapid and greatly automated method was developed for successive measurement of Pn under dozens of combined lights, of which each SPD approximated that of the selected PCW-LED lights, within days, which indicates that the method can determine the Pn quickly under numerous PCW-LED lights. Consequently, it contributes to the rapid selection of PCW-LED lights performing high Pn.","PeriodicalId":56074,"journal":{"name":"Journal of Agricultural Meteorology","volume":"1 1","pages":""},"PeriodicalIF":1.3,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48389405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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