Paddy rice mapping is crucial for cultivation management,yield estimation,and food security.Guangdong,straddling tropics and subtropics,is a major rice-producing region in China.Mapping paddy rice in Guangdong is esse...Paddy rice mapping is crucial for cultivation management,yield estimation,and food security.Guangdong,straddling tropics and subtropics,is a major rice-producing region in China.Mapping paddy rice in Guangdong is essential.However,there are 2 main difficulties in tropical and subtropical paddy rice mapping,including the lack of high-quality optical images and differences in paddy rice planting times.This study proposed a paddy rice mapping framework using phenology matching,integrating Sentinel-1 and Sentinel-2 data to incorporate prior knowledge into the classifiers.The transplanting periods of paddy rice were identified with Sentinel-1 data,and the subsequent 3 months were defined as the growth periods.Features during growth periods obtained by Sentinel-1 and Sentinel-2 were inputted into machine learning classifiers.The classifiers using matched features substantially improved mapping accuracy compared with those using unmatched features,both for early and late rice mapping.The proposed method also improved the accuracy by 6.44%to 16.10%compared with 3 other comparison methods.The model,utilizing matched features,was applied to early and late rice mapping in Guangdong in 2020.Regression results between mapping area and statistical data validate paddy rice mapping credibility.Our analysis revealed that thermal conditions,especially cold severity during growing stages,are the primary determinant of paddy rice phenology.Spatial patterns of paddy rice in Guangdong result from a blend of human and physical factors,with slope and minimum temperature emerging as the most important limitations.These findings enhance our understanding of rice ecosystems’dynamics,offering insights for formulating relevant agricultural policies.展开更多
Glabrous rice exhibits glabrous leaves and hulls because neither of these structures have trichomes on their surfaces. Glabrous rice varieties have become an important germplasm resource in the rice industry because t...Glabrous rice exhibits glabrous leaves and hulls because neither of these structures have trichomes on their surfaces. Glabrous rice varieties have become an important germplasm resource in the rice industry because they have considerable packaging efficiency and can reduce skin itching and dust during harvesting, drying, and packing （Shim et al., 2012; Zhang et al., 2012）.展开更多
Previous study indicated that the thermo-sensitive genic malesterile(TGMS)gene in rice was regulated by temperature.TGMS rice plays an important role in hybrid rice production,because the application of the TGMS syste...Previous study indicated that the thermo-sensitive genic malesterile(TGMS)gene in rice was regulated by temperature.TGMS rice plays an important role in hybrid rice production,because the application of the TGMS system in two-line breeding is laborsaving,timesaving,simple,inexpensive,efficient,and eliminating the limitations of the cytoplasmic male sterility(CMS)system.'AnnongS'is the first discovered and deeply studied TGMS rice lines in China.'AnnongS-1'and'Y58S',two derivatives of TGMS line AnnongS,were both controlled by a single recessive gene named tms5,which was genetically mapped on chromosome 2.In this study,three populations('AnnongS-1'×'Nanjing11','Y58S'×'Q611',and'Y58S'×'Guanghui122')were developed and used for the molecular fine mapping of the tms5 gene.By analyzing recombination events in the sterile individuals using a total of 125 probes covering the tms5 region,the tms5 gene was physically mapped to a 19-kb DNA fragment between two markers 4039-1 and 4039-2,which were located on the BAC clone AP004039.After the construction of the physical map between two markers 4039-1 and 4039-2,a member(ONAC023)of the NAC(NAM-ATAF-CUC-related)gene family was identified as the candidate gene of the tms5 gene.展开更多
Plant leaves play a significant role in photosynthesis. Normal chloroplast development is critical for plant growth and yield performance. Defect of the chlorophyll in chloroplasts may cause abnormal leaf colors, such...Plant leaves play a significant role in photosynthesis. Normal chloroplast development is critical for plant growth and yield performance. Defect of the chlorophyll in chloroplasts may cause abnormal leaf colors, such as yellow, white, or stripe. Chloroplasts have their own genomes encoding for about 100 genes that are essential for plastid protein synthesis and photosynthesis （Kanno and Hirai, 1993; Sato et al., 1999）. Moreover, over 3000 proteins encoded by plant nuclear genomes target to the chloroplasts and participate in the chloroplast development and/or photosynthesis. Hitherto, a number of plant genes, which encode for enzymes involved in chlorophyll biosynthetic pathways,展开更多
Rice is one of the most consumed staple food plants around the world, and its plant architecture is very important to improve the grain yield （Zhang et al., 2008）. Plant height, leaf angle, tiller number and angle, ...Rice is one of the most consumed staple food plants around the world, and its plant architecture is very important to improve the grain yield （Zhang et al., 2008）. Plant height, leaf angle, tiller number and angle, and uniformity of panicle layer all can have strong effects on grain yield （Wang and Li, 2008）. During the long history of domestication, rice has been selected to develop uniform tiller height architecture that ensures panicle layer uniformity and ease of harvesting （Ma et al., 2009）, and is largely determined by the synchronic culm elongation.展开更多
Leaves play a key role in photosynthesis in rice plants. The premature senescence of such plants directly reduces the accumulation of photosynthetic products and also affects yield and grain quality significantly and ...Leaves play a key role in photosynthesis in rice plants. The premature senescence of such plants directly reduces the accumulation of photosynthetic products and also affects yield and grain quality significantly and negatively. A novel premature senescence mutant, mps1（mid-late stage premature senescence 1）, was identified from a mutant library consisting of ethyl methane sulfonate（EMS） induced descendants of Jinhui 10, an elite indica restorer line of rice. The mutant allele, mps1, caused no phenotypic differences from the wild type（WT）, Jinhui 10, but drove the leaves to turn yellow when mutant plants grew to the tillering stage, and accelerated leaf senescence from the filling stage to final maturation. We characterized the agronomic traits, content of photosynthetic pigments and photosynthetic efficiency of mps1 and WT, and fine-mapped MPS1. The results showed that the MPS1-drove premature phenotype appeared initially on the leaf tips at the late tillering stage and extended to the middle of leaves during the maturing stage. Compared to the WT, significant differences were observed among traits of the number of grains per panicle（–31.7%） and effective number of grains per panicle（–38.5%） of mps1 individuals. Chlorophyll contents among the first leaf from the top（Top 1st）, the second leaf from the top（Top 2nd） and the third leaf from the top（Top 3rd） of mps1 were significantly lower than those of WT（P〈0.05）, and the levels of photosynthetic efficiency from Top 1st to the forth leaf from the top（Top 4th） of mps1 were significantly lower than those of WT（P〈0.01）. Results from the genetic analysis indicated that the premature senescence of mps1 is controlled by a recessive nuclear gene, and this locus, MPS1 is located in a 37.4-kb physical interval between the markers Indel145 and Indel149 on chromosome 6. Genomic annotation suggested eight open reading frames（ORFs） within this physical region. All of these results will provide informative references for the further researches involving functional analyses and molecular mechanism exploring of MPS1 in rice.展开更多
This paper introduces ENVISAT ASAR data application on rice field mapping in the Fuzhou area, using multi-temporal ASAR dual polarization data acquired in 2005. The procedure for ASAR data processing here includes dat...This paper introduces ENVISAT ASAR data application on rice field mapping in the Fuzhou area, using multi-temporal ASAR dual polarization data acquired in 2005. The procedure for ASAR data processing here includes data calibration, image registration, speckle reduction and conversion of data format from amplitude to dB for backscatter. The backscatter of rice increases with the rice growing stages, which was much different from other land covers. Based on image difference techniques, 6 schemes were designed with ASAR different temporal and polarization data for rice field mapping. Difference images between images in the early period of rice crop and growing or ripening period, are more suitable for rice extraction than those difference images between different polarizations in the same date. The most accurate result of late rice extraction was achieved based on the difference of HH polarization data acquired in October and August. Therefore, for rice field mapping, the temporal information is more important than polarization information. The data during the early growing season of rice is very important for high accuracy rice mapping.展开更多
Reliable estimation of region-wide rice yield is vital for food security and agricultural management.Field-scale models have increased our understanding of rice yield and its estimation under theoretical environmental...Reliable estimation of region-wide rice yield is vital for food security and agricultural management.Field-scale models have increased our understanding of rice yield and its estimation under theoretical environmental conditions.However,they offer little infor-mation on spatial variability effects on farm-scale yield.Remote Sensing(RS)is a useful tool to upscale yield estimates from farm scales to regional levels.Much research used RS with rice models for reliable yield estimation.As several countries start to operatio-nalize rice monitoring systems,it is needed to synthesize current literature to identify knowledge gaps,to improve estimation accuracies,and to optimize processing.This paper critically reviewed significant developments in using geospatial methods,imagery,and quantitative models to estimate rice yield.First,essential characteristics of rice were discussed as detected by optical and radar sensors,band selection,sensor configuration,spatial resolution,mapping methods,and biophysical variables of rice derivable from RS data.Second,various empirical,process-based,and semi-empirical models that used RS data for spatial estimation of yield were critically assessed-discussing how major types of models,RS platforms,data assimilation algorithms,canopy state variables,and RS variables can be integrated for yield estimation.Lastly,to overcome current constraints and to improve accuracies,several possibilities were suggested-adding new modeling modules,using alternative canopy variables,and adopting novel modeling approaches.As rice yields are expected to decrease due to global warming,geospatial rice yield estimation techniques are indispensable tools for climate change assessments.Future studies should focus on resolving the current limitations of estimation by precise delineation of rice cultivars,by incorporating dynamic harvesting indices based on climatic drivers,using innovative modeling approaches with machine learning.展开更多
Dwarf mutants are the crucial resources for molecular biology research and rice breeding. Here, a rice mutant, dwarf and deformed flower3（ddf3）, was identified in tissue culture of Oryza sativa cv. Dongjin. Compared...Dwarf mutants are the crucial resources for molecular biology research and rice breeding. Here, a rice mutant, dwarf and deformed flower3（ddf3）, was identified in tissue culture of Oryza sativa cv. Dongjin. Compared with wild type, the ddf3 mutant exhibited severe dwarfism, a greater number of tillers and significantly decreased fertility. In addition, leaf length, panicle length, and grain length, were significantly shorter. All internodes of ddf3 were shorter than those of wild type, and histological analysis revealed that internode cell elongation was significantly inhibited in ddf3. In the ddf3 mutant, pollen activity was significantly decreased, and the development of most stigmas was abnormal. Genetic analysis indicated that the ddf3 mutant phenotypes are controlled by a single or tightly linked nuclear genes. Using an F2 mapping population generated from a cross between ddf3 and Yangdao 6（9311）, the DDF3 gene was mapped to a 45.21-kb region between insertion-deletion（In Del） markers M15 and M16 on the long arm of chromosome 7. Sequencing revealed a 13.98-kbdeletion in this region in the ddf3 mutant genome that resulted in the complete or partial deletion of ZF（DHHC type zinc finger protein）, EP（expressed protein）, and FH2（actin-binding FH2 domain-containing protein） genes. Quantitative RT-PCR analyses revealed that in wild type, the transcript levels of FH2 were almost the same in all organs, while ZF was mainly expressed in the panicle, and no expression of EP was detected in any organ. Based on these results, ZF and FH2 could be potential DDF3 candidate genes involved in the regulation of rice morphology and flower organ development. Our work has laid the foundation for future functional analysis of these candidate genes and has provided a profitable gene resource for rice breeding for increased fertility in the future.展开更多
In August 1992, the State S&T Commission(SSTC) of China announced that China would launch a Rice Genome Program, a counterpart to the US Program of Human Genome, in a bid to decipher the genetic code of rice at th...In August 1992, the State S&T Commission(SSTC) of China announced that China would launch a Rice Genome Program, a counterpart to the US Program of Human Genome, in a bid to decipher the genetic code of rice at the molecular level and then apply the obtained results to the cultivation of improved strains of the crop.展开更多
The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia,using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a sh...The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia,using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period.Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season(June–October),followed by a fallow during the rabi season(November–February).These cropland areas are not suitable for growing rabi-season rice due to their high water needs,but are suitable for a short-season(≤3 months),low water-consuming grain legumes such as chickpea(Cicer arietinum L.),black gram,green gram,and lentils.Intensification(double-cropping)in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands.Several grain legumes,primarily chickpea,are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region.The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers:(a)rice crop is grown during the primary(kharif)crop growing season or during the north-west monsoon season(June–October);(b)same croplands are left fallow during the second(rabi)season or during the south-east monsoon season(November–February);and(c)ability to support low water-consuming,short-growing season(≤3 months)grain legumes(chickpea,black gram,green gram,and lentils)during rabi season.Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season,because the moisture/water demand of these crops is too high.The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index(NDVI)time series for one year(June 2010–May 2011)of Moderate Resolution Imaging Spectroradiometer(MODIS)data,using spectral matching techniques(SMTs),and extensive field knowledge.Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics.The producers’and users’accuracies of the cropland fallow classes were between 75%and 82%.The overall accuracy and the kappa coefficient estimated for rice classes were 82%and 0.79,respectively.The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia,with 88.3%in India,0.5%in Pakistan,1.1%in Sri Lanka,8.7%in Bangladesh,1.4%in Nepal,and 0.02%in Bhutan.Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.展开更多
Paddy rice agriculture is practiced in both rain-fed and irrigated ecosystems in the Philippines.However,small farms are prevalent in the region,and current satellite-based mapping techniques do not distinguish betwee...Paddy rice agriculture is practiced in both rain-fed and irrigated ecosystems in the Philippines.However,small farms are prevalent in the region,and current satellite-based mapping techniques do not distinguish between the two ecosystems at farm scales.This study developed an approach to rapidly map irrigated and rain-fed paddy rice in Iloilo,Philippines at 10 m resolutions using Google Earth Engine.This approach used an ensemble of classifiers based on time-series vegetation indices to produce dry and wet seasonal maps for the entire province.Results showed a predominance of rain-fed rice areas in both seasons,with irrigated rice making up only onefourth of the total rice area.The overall accuracy was achieved at 68%for the dry season and 75%for the wet season based on ground-acquired points and very high-resolution imagery.The two types of paddies were classified at accuracies up to 87%.Furthermore,the land cover maps showed a strong agreement with the municipal statistics.The resultant maps complement current official statistics and demonstrate the prowess of phenology-based mapping to create paddy inventories in a timely manner to inform food security and agricultural policies.展开更多
The present study was conducted to identify quantitative trait loci （QTLs） for leaf size traits in IR64 introgression lines （INLs）. For this purpose, selected F2 populations derived from crosses between recurrent ...The present study was conducted to identify quantitative trait loci （QTLs） for leaf size traits in IR64 introgression lines （INLs）. For this purpose, selected F2 populations derived from crosses between recurrent parent IR64 and its derived INLs, unique for leaf length and leaf width, were used to confirm QTLs. A total of eight QTLs, mapped on three chromosomes, were identified for the four leaf size traits in six F2 populations. A QTL for leaf length, qLLnpt-1, in HKL69 was identified around simple sequence repeat （SSR） marker RM3709 on chromosome 1. Two QTLs for flag leaf length, qFLLnpt-2 and qFLLnpt-4, in HFG39 were indentified on chromosomes 2 and 4, respectively. For flag leaf width, a QTL, qFLWnpt-4, in HFG39 was identified around RM17483 on chromosome 4. While another QTL for flag leaf width, qFLWnpt-1, in HFG27 was identified around RM3252 on chromosome 1. A QTL for leaf width, qLWnpt-2, in HKL75 was identified around RM7451 on chromosome 2. For leaf width, two QTLs, qLWnpt-4a, qLWnpt-4b, in HKL48 and HKL99 were identified around RM7208 and RM6909, respectively on chromosome 4. Results from this study suggest the possibilities to use marker-assisted selection and pyramiding these QTLs to improve rice water productivity.展开更多
Historic maps showing the temporal distribution of rice fields are important for precision agriculture,irrigation optimisation,forecasting crop yields,land use management and formulating policies.However,mapping rice ...Historic maps showing the temporal distribution of rice fields are important for precision agriculture,irrigation optimisation,forecasting crop yields,land use management and formulating policies.However,mapping rice felds using traditional ground surveys is impractical when high cost,time and labour requirements are considered,and the availability of such detailed records is limited.Although satellite remote sensing appears to be a viable solution,conventional segmentation and classification methods with spectral bands are often unable to contrast the distinct characteristics between rice fields and other vegetation classes.To this end,we explored a novel,Google Earth Engine(GEE)based multiindex random forest(RF)classification approach to map rice fields over two decades.Landsat images from 2000 to 2020 of two Sri Lankan rice cultivation districts were extracted from GEE and a multi-index RF classification algorithm was applied to distinguish the rice fields.The results showed above 80%accuracy for both training and validation,when compared against high spatial resolution Google Earth imagery.In essence,multi-index sampling and RF together synergised the compelling classifcation accuracy by effectively capturing vegetation,water(ponding)and soil characteristics unique to the rice felds using a single-click approach.The maps developed in this study were further compared against the MODIS land cover type product(MCD12Q1)and the corresponding superior statistics on rice fields demonstrated the robustness of the proposed approach.Future work seeking effective index combinations is recommended,and this approach can potentially be extended to other crop analyses elsewhere.展开更多
基金supported in part by the National Key R&D Program of China under grant 2022YFB3903402in part by the National Natural Science Foundation of China under grant 42222106in part by the National Natural Science Foundation of China under grant 61976234.
文摘Paddy rice mapping is crucial for cultivation management,yield estimation,and food security.Guangdong,straddling tropics and subtropics,is a major rice-producing region in China.Mapping paddy rice in Guangdong is essential.However,there are 2 main difficulties in tropical and subtropical paddy rice mapping,including the lack of high-quality optical images and differences in paddy rice planting times.This study proposed a paddy rice mapping framework using phenology matching,integrating Sentinel-1 and Sentinel-2 data to incorporate prior knowledge into the classifiers.The transplanting periods of paddy rice were identified with Sentinel-1 data,and the subsequent 3 months were defined as the growth periods.Features during growth periods obtained by Sentinel-1 and Sentinel-2 were inputted into machine learning classifiers.The classifiers using matched features substantially improved mapping accuracy compared with those using unmatched features,both for early and late rice mapping.The proposed method also improved the accuracy by 6.44%to 16.10%compared with 3 other comparison methods.The model,utilizing matched features,was applied to early and late rice mapping in Guangdong in 2020.Regression results between mapping area and statistical data validate paddy rice mapping credibility.Our analysis revealed that thermal conditions,especially cold severity during growing stages,are the primary determinant of paddy rice phenology.Spatial patterns of paddy rice in Guangdong result from a blend of human and physical factors,with slope and minimum temperature emerging as the most important limitations.These findings enhance our understanding of rice ecosystems’dynamics,offering insights for formulating relevant agricultural policies.
基金supported by the grants from the National Natural Science Foundation of China(Nos.31025017 and30971763)the National High-tech R&D Program of China(863 Program)(No.2012AA101101)
文摘Glabrous rice exhibits glabrous leaves and hulls because neither of these structures have trichomes on their surfaces. Glabrous rice varieties have become an important germplasm resource in the rice industry because they have considerable packaging efficiency and can reduce skin itching and dust during harvesting, drying, and packing （Shim et al., 2012; Zhang et al., 2012）.
文摘Previous study indicated that the thermo-sensitive genic malesterile(TGMS)gene in rice was regulated by temperature.TGMS rice plays an important role in hybrid rice production,because the application of the TGMS system in two-line breeding is laborsaving,timesaving,simple,inexpensive,efficient,and eliminating the limitations of the cytoplasmic male sterility(CMS)system.'AnnongS'is the first discovered and deeply studied TGMS rice lines in China.'AnnongS-1'and'Y58S',two derivatives of TGMS line AnnongS,were both controlled by a single recessive gene named tms5,which was genetically mapped on chromosome 2.In this study,three populations('AnnongS-1'×'Nanjing11','Y58S'×'Q611',and'Y58S'×'Guanghui122')were developed and used for the molecular fine mapping of the tms5 gene.By analyzing recombination events in the sterile individuals using a total of 125 probes covering the tms5 region,the tms5 gene was physically mapped to a 19-kb DNA fragment between two markers 4039-1 and 4039-2,which were located on the BAC clone AP004039.After the construction of the physical map between two markers 4039-1 and 4039-2,a member(ONAC023)of the NAC(NAM-ATAF-CUC-related)gene family was identified as the candidate gene of the tms5 gene.
基金supported by a grant from Ministry of Science and Technology of China (No. 2012AA10A303)
文摘Plant leaves play a significant role in photosynthesis. Normal chloroplast development is critical for plant growth and yield performance. Defect of the chlorophyll in chloroplasts may cause abnormal leaf colors, such as yellow, white, or stripe. Chloroplasts have their own genomes encoding for about 100 genes that are essential for plastid protein synthesis and photosynthesis （Kanno and Hirai, 1993; Sato et al., 1999）. Moreover, over 3000 proteins encoded by plant nuclear genomes target to the chloroplasts and participate in the chloroplast development and/or photosynthesis. Hitherto, a number of plant genes, which encode for enzymes involved in chlorophyll biosynthetic pathways,
基金supported by funds from the National Transgenic Major Program Grants(No.2009ZX08009-022B)
文摘Rice is one of the most consumed staple food plants around the world, and its plant architecture is very important to improve the grain yield （Zhang et al., 2008）. Plant height, leaf angle, tiller number and angle, and uniformity of panicle layer all can have strong effects on grain yield （Wang and Li, 2008）. During the long history of domestication, rice has been selected to develop uniform tiller height architecture that ensures panicle layer uniformity and ease of harvesting （Ma et al., 2009）, and is largely determined by the synchronic culm elongation.
基金supported by grants from the National Natural Science Foundation of China(31371597)the Fundamental Research Funds for the Central Universities,Ministry of Education of China(XDJK2014C147)the Chongqing Key Laboratory Capacity Upgrade Program of China(cstc-2014pt-sy80001)
文摘Leaves play a key role in photosynthesis in rice plants. The premature senescence of such plants directly reduces the accumulation of photosynthetic products and also affects yield and grain quality significantly and negatively. A novel premature senescence mutant, mps1（mid-late stage premature senescence 1）, was identified from a mutant library consisting of ethyl methane sulfonate（EMS） induced descendants of Jinhui 10, an elite indica restorer line of rice. The mutant allele, mps1, caused no phenotypic differences from the wild type（WT）, Jinhui 10, but drove the leaves to turn yellow when mutant plants grew to the tillering stage, and accelerated leaf senescence from the filling stage to final maturation. We characterized the agronomic traits, content of photosynthetic pigments and photosynthetic efficiency of mps1 and WT, and fine-mapped MPS1. The results showed that the MPS1-drove premature phenotype appeared initially on the leaf tips at the late tillering stage and extended to the middle of leaves during the maturing stage. Compared to the WT, significant differences were observed among traits of the number of grains per panicle（–31.7%） and effective number of grains per panicle（–38.5%） of mps1 individuals. Chlorophyll contents among the first leaf from the top（Top 1st）, the second leaf from the top（Top 2nd） and the third leaf from the top（Top 3rd） of mps1 were significantly lower than those of WT（P〈0.05）, and the levels of photosynthetic efficiency from Top 1st to the forth leaf from the top（Top 4th） of mps1 were significantly lower than those of WT（P〈0.01）. Results from the genetic analysis indicated that the premature senescence of mps1 is controlled by a recessive nuclear gene, and this locus, MPS1 is located in a 37.4-kb physical interval between the markers Indel145 and Indel149 on chromosome 6. Genomic annotation suggested eight open reading frames（ORFs） within this physical region. All of these results will provide informative references for the further researches involving functional analyses and molecular mechanism exploring of MPS1 in rice.
基金Supported by the Fujian Science and Technology Project(No.2006I0018,No.2009I0014)
文摘This paper introduces ENVISAT ASAR data application on rice field mapping in the Fuzhou area, using multi-temporal ASAR dual polarization data acquired in 2005. The procedure for ASAR data processing here includes data calibration, image registration, speckle reduction and conversion of data format from amplitude to dB for backscatter. The backscatter of rice increases with the rice growing stages, which was much different from other land covers. Based on image difference techniques, 6 schemes were designed with ASAR different temporal and polarization data for rice field mapping. Difference images between images in the early period of rice crop and growing or ripening period, are more suitable for rice extraction than those difference images between different polarizations in the same date. The most accurate result of late rice extraction was achieved based on the difference of HH polarization data acquired in October and August. Therefore, for rice field mapping, the temporal information is more important than polarization information. The data during the early growing season of rice is very important for high accuracy rice mapping.
基金This work is supported by New Zealand Ministry of Foreign Affairs and Trade PhD Scholarship and the University of Auckland’s Postgraduate Research Student SupportMinistry of Foreign Affairs and Trade,New Zealand,University of Auckland.
文摘Reliable estimation of region-wide rice yield is vital for food security and agricultural management.Field-scale models have increased our understanding of rice yield and its estimation under theoretical environmental conditions.However,they offer little infor-mation on spatial variability effects on farm-scale yield.Remote Sensing(RS)is a useful tool to upscale yield estimates from farm scales to regional levels.Much research used RS with rice models for reliable yield estimation.As several countries start to operatio-nalize rice monitoring systems,it is needed to synthesize current literature to identify knowledge gaps,to improve estimation accuracies,and to optimize processing.This paper critically reviewed significant developments in using geospatial methods,imagery,and quantitative models to estimate rice yield.First,essential characteristics of rice were discussed as detected by optical and radar sensors,band selection,sensor configuration,spatial resolution,mapping methods,and biophysical variables of rice derivable from RS data.Second,various empirical,process-based,and semi-empirical models that used RS data for spatial estimation of yield were critically assessed-discussing how major types of models,RS platforms,data assimilation algorithms,canopy state variables,and RS variables can be integrated for yield estimation.Lastly,to overcome current constraints and to improve accuracies,several possibilities were suggested-adding new modeling modules,using alternative canopy variables,and adopting novel modeling approaches.As rice yields are expected to decrease due to global warming,geospatial rice yield estimation techniques are indispensable tools for climate change assessments.Future studies should focus on resolving the current limitations of estimation by precise delineation of rice cultivars,by incorporating dynamic harvesting indices based on climatic drivers,using innovative modeling approaches with machine learning.
基金supported by the National Natural Science Foundation of China (31560350 and 31760350)the Science and Technology Program of Jiangxi, China (20171ACF60018)
文摘Dwarf mutants are the crucial resources for molecular biology research and rice breeding. Here, a rice mutant, dwarf and deformed flower3（ddf3）, was identified in tissue culture of Oryza sativa cv. Dongjin. Compared with wild type, the ddf3 mutant exhibited severe dwarfism, a greater number of tillers and significantly decreased fertility. In addition, leaf length, panicle length, and grain length, were significantly shorter. All internodes of ddf3 were shorter than those of wild type, and histological analysis revealed that internode cell elongation was significantly inhibited in ddf3. In the ddf3 mutant, pollen activity was significantly decreased, and the development of most stigmas was abnormal. Genetic analysis indicated that the ddf3 mutant phenotypes are controlled by a single or tightly linked nuclear genes. Using an F2 mapping population generated from a cross between ddf3 and Yangdao 6（9311）, the DDF3 gene was mapped to a 45.21-kb region between insertion-deletion（In Del） markers M15 and M16 on the long arm of chromosome 7. Sequencing revealed a 13.98-kbdeletion in this region in the ddf3 mutant genome that resulted in the complete or partial deletion of ZF（DHHC type zinc finger protein）, EP（expressed protein）, and FH2（actin-binding FH2 domain-containing protein） genes. Quantitative RT-PCR analyses revealed that in wild type, the transcript levels of FH2 were almost the same in all organs, while ZF was mainly expressed in the panicle, and no expression of EP was detected in any organ. Based on these results, ZF and FH2 could be potential DDF3 candidate genes involved in the regulation of rice morphology and flower organ development. Our work has laid the foundation for future functional analysis of these candidate genes and has provided a profitable gene resource for rice breeding for increased fertility in the future.
文摘In August 1992, the State S&T Commission(SSTC) of China announced that China would launch a Rice Genome Program, a counterpart to the US Program of Human Genome, in a bid to decipher the genetic code of rice at the molecular level and then apply the obtained results to the cultivation of improved strains of the crop.
基金supported by two CGIAR Research Programs:Dryland Cereals,Grain legumes and WLE.The research was also supported by the global food security support analysis data at 30 m project(GFSAD30http://geography.wr.usgs.gov/science/croplands/https://croplands.org/)funded by the NASA MEaSUREs[grant number:NNH13AV82I](Making Earth System Data Records for Use in Research Environments)funding obtained through NASA ROSES solicitation as well as by the Land Change Science(LCS),Land Remote Sensing(LRS),and Climate Land Use Change Mission Area Programs of the U.S.Geological Survey(USGS).
文摘The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia,using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period.Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season(June–October),followed by a fallow during the rabi season(November–February).These cropland areas are not suitable for growing rabi-season rice due to their high water needs,but are suitable for a short-season(≤3 months),low water-consuming grain legumes such as chickpea(Cicer arietinum L.),black gram,green gram,and lentils.Intensification(double-cropping)in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands.Several grain legumes,primarily chickpea,are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region.The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers:(a)rice crop is grown during the primary(kharif)crop growing season or during the north-west monsoon season(June–October);(b)same croplands are left fallow during the second(rabi)season or during the south-east monsoon season(November–February);and(c)ability to support low water-consuming,short-growing season(≤3 months)grain legumes(chickpea,black gram,green gram,and lentils)during rabi season.Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season,because the moisture/water demand of these crops is too high.The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index(NDVI)time series for one year(June 2010–May 2011)of Moderate Resolution Imaging Spectroradiometer(MODIS)data,using spectral matching techniques(SMTs),and extensive field knowledge.Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics.The producers’and users’accuracies of the cropland fallow classes were between 75%and 82%.The overall accuracy and the kappa coefficient estimated for rice classes were 82%and 0.79,respectively.The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia,with 88.3%in India,0.5%in Pakistan,1.1%in Sri Lanka,8.7%in Bangladesh,1.4%in Nepal,and 0.02%in Bhutan.Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.
基金Ministry of Foreign Affairs and Trade,New ZealandUniversity of Auckland.
文摘Paddy rice agriculture is practiced in both rain-fed and irrigated ecosystems in the Philippines.However,small farms are prevalent in the region,and current satellite-based mapping techniques do not distinguish between the two ecosystems at farm scales.This study developed an approach to rapidly map irrigated and rain-fed paddy rice in Iloilo,Philippines at 10 m resolutions using Google Earth Engine.This approach used an ensemble of classifiers based on time-series vegetation indices to produce dry and wet seasonal maps for the entire province.Results showed a predominance of rain-fed rice areas in both seasons,with irrigated rice making up only onefourth of the total rice area.The overall accuracy was achieved at 68%for the dry season and 75%for the wet season based on ground-acquired points and very high-resolution imagery.The two types of paddies were classified at accuracies up to 87%.Furthermore,the land cover maps showed a strong agreement with the municipal statistics.The resultant maps complement current official statistics and demonstrate the prowess of phenology-based mapping to create paddy inventories in a timely manner to inform food security and agricultural policies.
文摘The present study was conducted to identify quantitative trait loci （QTLs） for leaf size traits in IR64 introgression lines （INLs）. For this purpose, selected F2 populations derived from crosses between recurrent parent IR64 and its derived INLs, unique for leaf length and leaf width, were used to confirm QTLs. A total of eight QTLs, mapped on three chromosomes, were identified for the four leaf size traits in six F2 populations. A QTL for leaf length, qLLnpt-1, in HKL69 was identified around simple sequence repeat （SSR） marker RM3709 on chromosome 1. Two QTLs for flag leaf length, qFLLnpt-2 and qFLLnpt-4, in HFG39 were indentified on chromosomes 2 and 4, respectively. For flag leaf width, a QTL, qFLWnpt-4, in HFG39 was identified around RM17483 on chromosome 4. While another QTL for flag leaf width, qFLWnpt-1, in HFG27 was identified around RM3252 on chromosome 1. A QTL for leaf width, qLWnpt-2, in HKL75 was identified around RM7451 on chromosome 2. For leaf width, two QTLs, qLWnpt-4a, qLWnpt-4b, in HKL48 and HKL99 were identified around RM7208 and RM6909, respectively on chromosome 4. Results from this study suggest the possibilities to use marker-assisted selection and pyramiding these QTLs to improve rice water productivity.
文摘Historic maps showing the temporal distribution of rice fields are important for precision agriculture,irrigation optimisation,forecasting crop yields,land use management and formulating policies.However,mapping rice felds using traditional ground surveys is impractical when high cost,time and labour requirements are considered,and the availability of such detailed records is limited.Although satellite remote sensing appears to be a viable solution,conventional segmentation and classification methods with spectral bands are often unable to contrast the distinct characteristics between rice fields and other vegetation classes.To this end,we explored a novel,Google Earth Engine(GEE)based multiindex random forest(RF)classification approach to map rice fields over two decades.Landsat images from 2000 to 2020 of two Sri Lankan rice cultivation districts were extracted from GEE and a multi-index RF classification algorithm was applied to distinguish the rice fields.The results showed above 80%accuracy for both training and validation,when compared against high spatial resolution Google Earth imagery.In essence,multi-index sampling and RF together synergised the compelling classifcation accuracy by effectively capturing vegetation,water(ponding)and soil characteristics unique to the rice felds using a single-click approach.The maps developed in this study were further compared against the MODIS land cover type product(MCD12Q1)and the corresponding superior statistics on rice fields demonstrated the robustness of the proposed approach.Future work seeking effective index combinations is recommended,and this approach can potentially be extended to other crop analyses elsewhere.
