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The utilization of electroporation for delivering CRISPR/Cas9 system components has enabled efficient gene editing in mammalian zygotes, facilitating the development of genome-edited animals. In this study, our research focused on targeting the ACTG1 and MSTN genes in sheep, revealing a threshold phenomenon in electroporation with a voltage tolerance in sheep in vitro fertilization (IVF) zygotes. Various poring voltages near 40 V and pulse durations were examined for electroporating sheep zygotes. The study concluded that stronger electric fields required shorter pulse durations to achieve the optimal conditions for high gene mutation rates and reasonable blastocyst development. This investigation also assessed the quality of Cas9/sgRNA ribonucleoprotein complexes (Cas9 RNPs) and their influence on genome editing efficiency in sheep early embryos. It was highlighted that pre-complexation of Cas9 proteins with single-guide RNA (sgRNA) before electroporation was essential for achieving a high mutation rate. The use of suitable electroporation parameters for sheep IVF zygotes led to significantly high mutation rates and heterozygote ratios. By delivering Cas9 RNPs and single-stranded oligodeoxynucleotides (ssODNs) to zygotes through electroporation, targeting the MSTN (Myostatin) gene, a knock-in efficiency of 26% was achieved. The successful generation of MSTN-modified lambs was demonstrated by delivering Cas9 RNPs into IVF zygotes via electroporation. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is a key variable for monitoring crop growth. Compared with traditional measurement methods, unmanned aerial vehicle (UAV) remote sensing offers a cost-effective and efficient approach for rapidly obtaining crop LAI. Although there is extensive research on rice LAI estimation, many studies suffer from the limitations of models that are only applicable to specific scenarios with unclear applicability conditions. In this study, we selected commonly used RGB and multispectral (Ms) data sources, which contain three channels of color information and five multi-band information, respectively, combined with five different spatial resolutions of data at intervals of 20–100 m. We evaluated the effectiveness of models using single- and multi-feature variables for LAI estimation in rice. In addition, texture and coverage features other than spectra were introduced to further analyze their effects on the inversion accuracy of the LAI. The results show that the accuracy of the model established with multi-variables under single features is significantly higher than that of the model established with single variables under single features. The best results were obtained using the RFR (random forest regression) model, in which the model's R2 is 0.675 and RMSE is 0.886 for multi-feature VIs at 40 m. Compared with the analysis results of Ms and RGB data at different heights, the accuracy of Ms data estimation results fluctuates slightly and is less sensitive to spatial resolution, while the accuracy of the results based on RGB data gradually decreases with the increase in height. The estimation accuracies of both Ms and RGB data were improved by adding texture features and coverage features, and their R2 improved by 9.1% and 7.3% on average. The best estimation heights (spatial resolution) of the two data sources were 40 m (2.2 cm) and 20 m (0.4 cm), with R2 of 0.724 and 0.673, and RMSE of 0.810 and 0.881. This study provides an important reference for the estimation of rice LAI based on RGB and Ms data acquired using the UAV platform. [ABSTRACT FROM AUTHOR]

Soil hydrology seriously affects the prevention of desertification in karst areas. However, water infiltration in the different soil layers of secondary forests and artificial forests in karst areas remains uncertain. This lack of clarity is also the factor that constrains local vegetation restoration. Therefore, monitoring and simulating the priority transport of soil moisture will help us understand the shallow soil moisture transport patterns after artificial vegetation restoration in the local area, providing a reference for more scientific restoration of the ecological environment and enhancement of carbon storage in karst areas. The integration of soil physical property assessments, computed tomography (CT) scanning, dye tracing studies, and HYDRUS-2D modeling was utilized to evaluate and contrast the attributes of soil macropores and the phenomenon of preferential flow across various forestland categories. This approach allowed for a comprehensive analysis of how the soil structure and water movement are influenced by different forest ecosystems and infiltration head simulations (5 mm, 15 mm, 35 mm, and 55 mm) to elucidate the dynamics of water movement across diverse soil types within karst regions, to identify the causes of water leakage due to preferential flow in secondary forests, and to understand the mechanisms of water conservation and reduction in artificial forests adopting a multifaceted approach. This study demonstrated that (1) the soil hydrological capacity of a plantation forest was 20% higher than a natural forest, which may be promoted by the clay content and distribution. (2) Afforestation-enhanced soils in karst regions demonstrate a significant capacity to mitigate the loss of clay particles during episodes of preferential flow and then improve the soil erosion resistance by about 5 times, which can effectively control desertification in karst area. (3) The uniform distribution of macropores in plantation forest soil was conducive to prevent water leakage more effectively than the secondary forest but was incapable of hindering the occurrence of preferential flow. The secondary forest had a very developed preferential flow phenomenon, and soil clay deposition occurred with an increase in depth. (4) Moreover, the results for preferential flow showed that the matrix flow depth did not increase with the increase in water quantity. Short-term and high-intensity heavy rainfall events facilitated the occurrence of preferential flow. Infiltration along the horizontal and vertical directions occurred simultaneously. These results could facilitate a further understanding of the contribution of the plantation to soil amelioration and the prevention of desertification in karst areas, and provide some suggestions for the sustainable development of forestry in karst areas where plantation restoration is an important ingredient. [ABSTRACT FROM AUTHOR]

Accurate and high-throughput maize plant phenotyping is vital for crop breeding and cultivation research. Tassel-related phenotypic parameters are important agronomic traits. However, fully automatic and fine tassel organ segmentation of maize shoots from three-dimensional (3D) point clouds is still challenging. To address this issue, a tassel point cloud segmentation method based on point cloud super voxels clustering and local geometric features was proposed in this study. Firstly, the undirected graph of the maize plant point cloud was established, the edge weights were calculated by using the difference of normal vectors, and the spectral clustering method was used to cluster the point cloud to form multiple super voxel sub-regions. Then, the principal component analysis method was used to find the two end regions of the plant and based on the observation of the straight direction of the bottom stem regions, the top and bottom regions were distinguished by the point cloud linear features. Finally, the tassel points were identified based on the plane local features of the point cloud. The sub-regions of the top region of the plant were classified into leaf regions, tassel regions, and mixed regions by plane local features of the point cloud, the tassel points in the tassel sub-region, and the mixed region were the finally segmented tassel point clouds. In this study, 15 mature maize plants with 3 point cloud densities were tested. Compared with the ground truth segmented manually, the average F1 scores of the tassel segmentation were 0.763, 0.875 and 0.889 when the point cloud density was 0.8/cm, 1.3/cm, and 1.9/cm, respectively. The segmentation accuracy of this method increased with the increase of plant point cloud density. The increase of point cloud density and the number of point clouds mainly affected the calculation results of point cloud plane features in tassel segmentation. When the number of point clouds was small, the top leaf point cloud was relatively sparse. Therefore, the difference between the plane feature of the leaf point and the plane feature of the tassel point was not obvious, which led to the increase of the misclassification of the point cloud. However, the time complexity of the algorithm was O(n3), so the increase in the density and number of point clouds would lead to a significant increase in the running time. Considering the segmentation accuracy and running time, the research obtained the best effect on the mature maize plants with a point cloud density of 1.3/cm and an average number of 15,000. The segmentation F1 score reached 0.875 and the running time was 6.85 s. The results showed that this method could extract tassels from maize plant point cloud, and provided technical support for the research and application of high-throughput phenotyping and three-dimensional reconstruction of maize.

Cellulose was the most abundant biological molecule in nature, as a major component of plant cell wall. Nano cellulose Isolated through integration of cellulose fibers could be used as an adsorbent for wastewater treatment due to is excellent properties. Owing to is high cellulose content and almost without jig- nine in the cell walks, Chlorella was a good raw material for preparing Nano cellulose. In this study, Chlorella-re sexual based TEMPCoxidized cellulose nanofibers (TCNF) were prepared through TEMPC--mediated oxidation processes under gentle mixing without high-energy mechanical treatments. The average daameter of TCNF Ls a¬bout 2 nm, whereas tots average length was about 300 nm, and the carboxyl content is 1.54 moll/g. Moreover, methylene blue (MB) was used as a model dye to measure the adsorption capacity of TCNF. The adsorption capacity is almost saturated when TCNF contacted MB for 80 min, and the adsorption kinetics coincide with the pseudo-secondary kinetics model. The adsorption of TCNF on MB s greatly affected by the pH value, worth a maximum value at pH = 8. The email concentration of MB considerably affects is adsorption on TCNF. Below the INTA! Concentration of 10 mg/g, adsorption of TCNF considerably increases with the increase in the email concentration of MB. And when the concentration is higher than 10 mg/L, the adsorption tends to be saturated. Based on the scorpion isotherms analyses of TCNF, the Langmuir model its best worth the experimental data. Thus, TCNF surfaces are uniform and monolayer adsorption occurred. In conclusion, the preparation of TCNF from Chlorella-residual is a simple and promising scheme for the removal of caiiomc dyes from industrial Wastewater. [ABSTRACT FROM AUTHOR]