Knockout of miR396 genes increases seed size and yield in soybean.

Yield improvement has long been an important task for soybean breeding in the world in order to meet the increasing demand for food and animal feed. miR396 genes have been shown to negatively regulate grain size in rice, but whether miR396 family members may function in a similar manner in soybean is unknown. Here, we generated eight soybean mutants harboring different combinations of homozygous mutations in the six soybean miR396 genes through genome editing with clustered regularly interspaced palindromic repeats (CRISPR)/CRISPR-associated nuclease (Cas)12SF01 in the elite soybean cultivar Zhonghuang 302 (ZH302). Four triple mutants (mir396aci, mir396acd, mir396adf, and mir396cdf), two quadruple mutants (mir396abcd and mir396acfi), and two quintuple mutants (mir396abcdf and mir396bcdfi) were characterized. We found that plants of all the mir396 mutants produced larger seeds compared to ZH302 plants. Field tests showed that mir396adf and mir396cdf plants have significantly increased yield in growth zones with relatively high latitude which are suited for ZH302 and moderately increased yield in lower latitude. In contrast, mir396abcdf and mir396bcdfi plants have increased plant height and decreased yield in growth zones with relatively high latitude due to lodging issues, but they are suited for low latitude growth zones with increased yield without lodging problems. Taken together, our study demonstrated that loss-of-function of miR396 genes leads to significantly enlarged seed size and increased yield in soybean, providing valuable germplasms for breeding high-yield soybean.

Quantitative determination of zearalenone in wheat by the CSA-NIR technique combined with chemometrics algorithms.

In the current study, a colorimetric sensor array combined with near-infrared (NIR) spectroscopy was used to quantitatively analyze zearalenone in wheat. The portable NIR spectrometer was used to scan the porphyrin reaction points of the wheat colorimetric sensor and collect spectral data. Subsequently, based on all the NIR spectral data, the two models and three feature selection algorithms are compared, and the best performance model and the best feature variable input are selected. Concurrently, the Kernel-based Extreme Learning Machine (KELM) model optimized by the two parameter optimization algorithms was compared, and the best parameter optimization algorithm was selected. Among all evaluation models, the KELM model optimized by the Competitive Adaptive Reweighted Sampling algorithm combined with the rime optimization algorithm has the best prediction effect. The predicted RP2 is 0.9900, and the root mean square error of prediction (RMSEP) is 18.4610 µg∙kg-1.

Spatiotemporal evolution of seismicity during the cyclic operation of the Hutubi underground gas storage, Xinjiang, China.

Underground gas storages (UGSs) are important large-scale industrial facilities used to bridge the gap between natural gas consumption and supply. The cyclic operation of the UGS may alter the subsurface stresses and local seismicity. We examined seismicity around the Hutubi UGS from 2011 to 2019 using the matched filter technique (MFT) and double-difference location methods. More than 1300 earthquakes were detected with seismicity around the UGS showing a remarkable increase since the start of its operation and showing a clear correlation to seasonal gas production. About 684 detected earthquakes were located, most of them occurred within 6 km of the reservoir. The events can be grouped into two clusters. Both clusters initiated around the gas pressure boundary. The first cluster extinct after the first injection period. While the second cluster diffused upward along a pre-existing fault. We speculate that strain localization caused by non-uniform gas injection contributes to the initiation of seismicity clusters around the UGS, and the trapped crude oil/gas played an important role in the migration of the second surge. The revealed seismicity pattern contributes to a better understanding of the mechanism of induced seismic events and emphasizes the importance of seismic monitoring in the UGS region.