Idealizing inflorescence architecture to enhance rice yield potential for feeding nine billion people in 2050

In recent years, a large number of salterns have been converted into rice fields in the coastal region of Jiangsu Province, Eastern China. The high spatial heterogeneity of soil salinity has caused large within-field variabilities in grain yield of rice. The identification of low-yield areas within a field is an important initial step for precision farming. While optical satellite remote sensing can provide valuable information on crop growth and yield potential, the availability of cloud-free optical image data is often hampered by unfavorable weather conditions. Synthetic aperture radar (SAR) offers an alternative due to its nearly day-and-night and all-weather capability in data acquisition. Given the free data access of the Sentinels, this study aimed at developing a Sentinel-1A-based SAR index for rice yield estimation. The proposed SAR simple difference (SSD) index uses the change of the Sentinel-1A backscatter in vertical-horizontal (VH) polarization between the end of the tillering stage and the end of grain filling stage (SSDVH). A strong exponential relationship has been identified between the SSDVH and rice yield, producing accurate yield estimation with a root mean square error (RMSE) of 0.74 t ha−1 and a relative error (RE) of 7.93%.

Download Full-text

Genotypic difference in canopy diffusive conductance measured by a new remote-sensing method and its association with the difference in rice yield potential

Plant Cell & Environment ◽

10.1111/j.1365-3040.2005.01445.x ◽

2006 ◽

Vol 29 (4) ◽

pp. 653-660 ◽

Cited By ~ 45

Author(s):

TAKESHI HORIE ◽

SHOJI MATSUURA ◽

TOSHIYUKI TAKAI ◽

KOUHEI KUWASAKI ◽

AKIHIRO OHSUMI ◽

...

Keyword(s):

Remote Sensing ◽

Rice Yield ◽

Yield Potential ◽

Genotypic Difference ◽

The Difference

Download Full-text

Identification and physiological analyses of a locus for rice yield potential across the genetic background

Journal of Experimental Botany ◽

10.1093/jxb/eri267 ◽

2005 ◽

Vol 56 (420) ◽

pp. 2745-2753 ◽

Cited By ~ 24

Author(s):

Ken Ishimaru ◽

Takayuki Kashiwagi ◽

Naoki Hirotsu ◽

Yuka Madoka

Keyword(s):

Genetic Background ◽

Rice Yield ◽

Yield Potential

Download Full-text

Simulating genotypic strategies for increasing rice yield potential in irrigated, tropical environments

Field Crops Research ◽

10.1016/s0378-4290(96)01044-1 ◽

1997 ◽

Vol 51 (1-2) ◽

pp. 5-17 ◽

Cited By ~ 64

Author(s):

P.K. Aggarwal ◽

M.J. Kropff ◽

K.G. Cassman ◽

H.F.M. ten Berge

Keyword(s):

Rice Yield ◽

Yield Potential ◽

Tropical Environments

Download Full-text

Management of Meloidogyne graminicola and yield of upland rice in South-Luzon, Philippines

Nematology ◽

10.1163/156854103773040781 ◽

2003 ◽

Vol 5 (6) ◽

pp. 879-884 ◽

Cited By ~ 38

Author(s):

Imelda Soriano ◽

Georges Reversat

Keyword(s):

Rice Yield ◽

Upland Rice ◽

Rice Crop ◽

Yield Potential ◽

Root Knot Nematode ◽

Short Life ◽

Meloidogyne Graminicola ◽

Asian Rice ◽

Rice Yields ◽

Single Rice

AbstractMeloidogyne graminicola, the rice root-knot nematode, has become a constraint on Asian rice production due to rice cropping intensification and increasing scarcity of water. This work relates to the assessment of crop rotation, fallow and nematicide treatments in naturally infested fields to manage M. graminicola populations and prevent yield losses. One or two consecutive crops of cowpea or seasons of fallow before a rice crop lowered nematode populations and improved rice yield by 30-80%. Methyl bromide was used to determine yield potential and almost eradicated the nematode, trebling rice yield. Carbofuran improved yield of the first rice crop but did not affect the second rice crop. Due to its short life cycle, M. graminicola populations were similar after only a single rice crop and after three consecutive crops. It is recommended that, to ensure higher rice yields, M. graminicola populations should be maintained at low density by non-host crop rotations or fallows, ideally for two seasons before planting rice.

Download Full-text

Genome-wide association study and Mendelian randomization analysis provide insights for improving rice yield potential

Scientific Reports ◽

10.1038/s41598-021-86389-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jing Su ◽

Kai Xu ◽

Zirong Li ◽

Yuan Hu ◽

Zhongli Hu ◽

...

Keyword(s):

Association Study ◽

Genetic Basis ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Rice Yield ◽

Genome Wide Association ◽

Yield Potential ◽

Genome Wide ◽

Component Traits ◽

Effect On Yield

AbstractRice yield per plant has a complex genetic architecture, which is mainly determined by its three component traits: the number of grains per panicle (GPP), kilo-grain weight (KGW), and tillers per plant (TP). Exploring ideotype breeding based on selection for genetically less complex component traits is an alternative route for further improving rice production. To understand the genetic basis of the relationship between rice yield and component traits, we investigated the four traits of two rice hybrid populations (575 + 1495 F1) in different environments and conducted meta-analyses of genome-wide association study (meta-GWAS). In total, 3589 significant loci for three components traits were detected, while only 3 loci for yield were detected. It indicated that rice yield is mainly controlled by minor-effect loci and hardly to be identified. Selecting quantitative trait locus/gene affected component traits to further enhance yield is recommended. Mendelian randomization design is adopted to investigate the genetic effects of loci on yield through component traits and estimate the genetic relationship between rice yield and its component traits by these loci. The loci for GPP or TP mainly had a positive genetic effect on yield, but the loci for KGW with different direction effects (positive effect or negative effect). Additionally, TP (Beta = 1.865) has a greater effect on yield than KGW (Beta = 1.016) and GPP (Beta = 0.086). Five significant loci for component traits that had an indirect effect on yield were identified. Pyramiding superior alleles of the five loci revealed improved yield. A combination of direct and indirect effects may better contribute to the yield potential of rice. Our findings provided a rationale for using component traits as indirect indices to enhanced rice yield, which will be helpful for further understanding the genetic basis of yield and provide valuable information for improving rice yield potential.

Download Full-text

Genetic Basis of Relationship Between Yield and its Component Traits in Rice Revealed by Genome-Wide Association and Mendelian Randomization Study

10.21203/rs.3.rs-28492/v1 ◽

2020 ◽

Author(s):

Jing Su ◽

Kai Xu ◽

Chao Wu ◽

Zirong Li ◽

Zhongli Hu ◽

...

Keyword(s):

Genetic Basis ◽

Mendelian Randomization ◽

Rice Yield ◽

Genome Wide Association ◽

Yield Potential ◽

Genome Wide ◽

Component Traits ◽

Selection For ◽

Ideotype Breeding ◽

Effect On Yield

Abstract BackgroundRice yield has a complex genetic architecture, which mainly determined by its three component traits: the number of grains per panicle (GPP), kilo-grain weight (KGW) and tillers per plant (TP). Exploring ideotype breeding based on selection for genetically less complex component traits is an alternative route for further improving rice production. Thus, it is important that studying the genetic basis of relationship between rice yield and component traits and clarifying the effects of each component trait on yield. Main textIn this study, we carried out meta-analyses of genome-wide association study (Meta-GWAS) with two population (575 + 1495 F1) in different environment for yield and its three component traits in rice. Totally, 3589 significant loci for three components traits were detected, while only 3 significant loci for yield were detected. It indicated that rice yield is mainly controlled by minor-effect loci and hardly to be identified. Selecting quantitative trait locus (QTL)/gene affected component traits to further enhance yield is recommended. A Mendelian randomization (MR) design was adopted to further estimate the causal relationship between rice yield and its component traits. Both GPP (Beta=0.086, 95% CI: 0.030~0.141, P=0.003) and TP (Beta=1.865, 95% CI: 1.035~2.694, P<0.0001) has a positive causal relationship with yield, but no significant relationship between KGW and yield (Beta=0.456, 95% CI: -0.119~1.031, P=0.120) was observed. Additionally, TP (Beta=1.865) has a greater effect on yield than GPP (Beta=0.086). Four significant loci for TP and GPP with indirect effect on yield were identified. Pyramiding superior alleles of the four loci revealed improved yield. A combination of direct and indirect effects may better contribute to the yield potential of rice.ConclusionsOur results suggested rice production would improve by ideotype breeding based on selection for GPP and TP. By studying the nature and strength of the relationship between yield and its components, provide genetic insights for further improving rice yield potential.

Download Full-text