Regulation of Leaf Angle Protects Photosystem I under Fluctuating Light in Tobacco Young Leaves

Fluctuating light is a typical light condition in nature and can cause selective photodamage to photosystem I (PSI). The sensitivity of PSI to fluctuating light is influenced by the amplitude of low/high light intensity. Tobacco mature leaves are tended to be horizontal to maximize the light absorption and photosynthesis, but young leaves are usually vertical to diminish the light absorption. Therefore, we tested the hypothesis that such regulation of the leaf angle in young leaves might protect PSI against photoinhibition under fluctuating light. We found that, upon a sudden increase in illumination, PSI was over-reduced in extreme young leaves but was oxidized in mature leaves. After fluctuating light treatment, such PSI over-reduction aggravated PSI photoinhibition in young leaves. Furthermore, the leaf angle was tightly correlated to the extent of PSI photoinhibition induced by fluctuating light. Therefore, vertical young leaves are more susceptible to PSI photoinhibition than horizontal mature leaves when exposed to the same fluctuating light. In young leaves, the vertical leaf angle decreased the light absorption and thus lowered the amplitude of low/high light intensity. Therefore, the regulation of the leaf angle was found for the first time as an important strategy used by young leaves to protect PSI against photoinhibition under fluctuating light. To our knowledge, we show here new insight into the photoprotection for PSI under fluctuating light in nature.

Stability analysis of rice (Oryza sativa L.) under different micro-environments

The present research was undertaken to evaluate 32 rice genotypes for grain yield and its attributing traits under three micro-environments like., direct seeded condition (E-I), transplanting at spacing of 15 x 15 cm (E-II) and 25 x 15 cm (E-III). Adopting the Eberhart and Russell (1966) model, stability analysis of variance revealed significant differences among the genotypes for days to 50% flowering, days to maturity, plant height, panicle length, number of grains per panicle and flag leaf angle. Stability parameters for grain yield per plant indicated that the genotypes Rewa 1329-4-26-1, Rewa 1326-11-67-2 and Rewa 1326-16-1 had regression coefficient less than one and mean value higher than average mean this depicted that these genotypes have wider adaptability and suitability for all micro- environments and the genotypes Rewa 1329-4-123-11, Rewa 1328-18-16 and Rewa 1326-3-34-4 had regression coefficient less than one and deviation from regression around zero were identified as highly stable and best suited for poor management practices like, direct seeded condition.

A Random Forest Algorithm for Retrieving Canopy Chlorophyll Content of Wheat and Soybean Trained with PROSAIL Simulations Using Adjusted Average Leaf Angle

Canopy chlorophyll content (CCC) is an important indicator for crop-growth monitoring and crop productivity estimation. The hybrid method, involving the PROSAIL radiative transfer model and machine learning algorithms, has been widely applied for crop CCC retrieval. However, PROSAIL’s homogeneous canopy hypothesis limits the ability to use the PROSAIL-based CCC estimation across different crops with a row structure. In addition to leaf area index (LAI), average leaf angle (ALA) is the most important canopy structure factor in the PROSAIL model. Under the same LAI, adjustment of the ALA can make a PROSAIL simulation obtain the same canopy gap as the heterogeneous canopy at a specific observation angle. Therefore, parameterization of an adjusted ALA (ALAadj) is an optimal choice to make the PROSAIL model suitable for specific row-planted crops. This paper attempted to improve PROSAIL-based CCC retrieval for different crops, using a random forest algorithm, by introducing the prior knowledge of crop-specific ALAadj. Based on the field reflectance spectrum at nadir, leaf area index, and leaf chlorophyll content, parameterization of the ALAadj in the PROSAIL model for wheat and soybean was carried out. An algorithm integrating the random forest and PROSAIL simulations with prior ALAadj information was developed for wheat and soybean CCC retrieval. Ground-measured CCC measurements were used to validate the CCC retrieved from canopy spectra. The results showed that the ALAadj values (62 degrees for wheat; 45 degrees for soybean) that were parameterized for the PROSAIL model demonstrated good discrimination between the two crops. The proposed algorithm improved the CCC retrieval accuracy for wheat and soybean, regardless of whether continuous visible to near-infrared spectra with 50 bands (RMSE from 39.9 to 32.9 μg cm−2; R2 from 0.67 to 0.76) or discrete spectra with 13 bands (RMSE from 43.9 to 33.7 μg cm−2; R2 from 0.63 to 0.74) and nine bands (RMSE from 45.1 to 37.0 μg cm−2; R2 from 0.61 to 0.71) were used. The proposed hybrid algorithm, based on PROSAIL simulations with ALAadj, has the potential for satellite-based CCC estimation across different crop types, and it also has a good reference value for the retrieval of other crop parameters.

Kajian Sifat Kuantitatif Galur F2 Tanaman Jagung di Lahan Kering

This study was aimed to determine the average of leaf angle, yield and harvest age of each F2 line compared to the two parents respectively. In addition, we also want to evaluate the coefficient of genetic diversity and heritability of the three traits. The experiment was designed in a randomized block design with a total treatment of 20 populations, namely 16 F2 lines and 4 parents. Each treatment was repeated 3 times, so that 60 experimental units were obtained. The experimental data were analyzed by analysis of variance at the 5 percent significance level and further tests using the Least Significant Difference at the same significance level. The results showed that the F2 P8IS x T1NK7328 (R16), F2 P8IS x T1NK7328 (R18) lines, and the F2 P8IS x NK212 (R4) lines, had leaf angles same as each parent of the first hybrid/hybrid offspring (T1NK7328 and NK212) and smaller than the Sinta Unram. The harvest time of the three F2 lines was classified as super early. Yield (weight of dry seeds per plot) of F2 P8IS x T1NK7328 (R16), F2 P8IS x T1NK7328 (R18) lines, were the same as both parents and F2 P8IS x NK212 (R4) lines, higher than Sinta Unram; but the same as the hybrid parent (NK212). Coefficient of genetic diversity of yield is high; medium for harvest time and low for leaf angle. Heritability in broad sense is classified as high, obtained at harvest time and yield; while the heritability of leaf angle is low. The three F2 lines can be used as basic population material for subsequent breeding activities. Key words: hybridization; Sinta Unram; yield; leaf angle

3D reconstruction identifies loci linked to variation in angle of individual sorghum leaves

Selection for yield at high planting density has reshaped the leaf canopy of maize, improving photosynthetic productivity in high density settings. Further optimization of canopy architecture may be possible. However, measuring leaf angles, the widely studied component trait of leaf canopy architecture, by hand is a labor and time intensive process. Here, we use multiple, calibrated, 2D images to reconstruct the 3D geometry of individual sorghum plants using a voxel carving based algorithm. Automatic skeletonization and segmentation of these 3D geometries enable quantification of the angle of each leaf for each plant. The resulting measurements are both heritable and correlated with manually collected leaf angles. This automated and scaleable reconstruction approach was employed to measure leaf-by-leaf angles for a population of 366 sorghum plants at multiple time points, resulting in 971 successful reconstructions and 3,376 leaf angle measurements from individual leaves. A genome wide association study conducted using aggregated leaf angle data identified a known large effect leaf angle gene, several previously identified leaf angle QTL from a sorghum NAM population, and novel signals. Genome wide association studies conducted separately for three individual sorghum leaves identified a number of the same signals, a previously unreported signal shared across multiple leaves, and signals near the sorghum orthologs of two maize genes known to influence leaf angle. Automated measurement of individual leaves and mapping variants associated with leaf angle reduce the barriers to engineering ideal canopy architectures in sorghum and other grain crops.

Retrieval of Leaf Area Index by Linking the PROSAIL and Ross-Li BRDF Models Using MODIS BRDF Data

Canopy structure parameters (e.g., leaf area index (LAI)) are key variables of most climate and ecology models. Currently, satellite-observed reflectances at a few viewing angles are often directly used for vegetation structure parameter retrieval; therefore, the information content of multi-angular observations that are sensitive to canopy structure in theory cannot be sufficiently considered. In this study, we proposed a novel method to retrieve LAI based on modelled multi-angular reflectances at sufficient sun-viewing geometries, by linking the PROSAIL model with a kernel-driven Ross-Li bi-directional reflectance function (BRDF) model using the MODIS BRDF parameter product. First, BRDF sensitivity to the PROSAIL input parameters was investigated to reduce the insensitive parameters. Then, MODIS BRDF parameters were used to model sufficient multi-angular reflectances. By comparing these reference MODIS reflectances with simulated PROSAIL reflectances within the range of the sensitive input parameters in the same geometries, the optimal vegetation parameters were determined by searching the minimum discrepancies between them. In addition, a significantly linear relationship between the average leaf angle (ALA) and the coefficient of the volumetric scattering kernel of the Ross-Li model in the near-infrared band was built, which can narrow the search scope of the ALA and accelerate the retrieval. In the validation, the proposed method attains a higher consistency (root mean square error (RMSE) = 1.13, bias = −0.19, and relative RMSE (RRMSE) = 36.8%) with field-measured LAIs and 30-m LAI maps for crops than that obtained with the MODIS LAI product. The results indicate the vegetation inversion potential of sufficient multi-angular data and the ALA relationship, and this method presents promise for large-scale LAI estimation.

Trait Association and Prediction Through Integrative K-mer Analysis

Genome-wide association study (GWAS) with single nucleotide polymorphisms (SNPs) has been widely used to explore genetic controls of phenotypic traits. Here we employed an GWAS approach using k-mers, short substrings from sequencing reads. Using maize cob and kernel color traits, we demonstrated that k-mer GWAS can effectively identify associated k-mers. Co-expression analysis of kernel color k-mers and pathway genes directly found k-mers from causal genes. Analyzing complex traits of kernel oil and leaf angle resulted in k-mers from both known and candidate genes. Evolution analysis revealed most k-mers positively correlated with kernel oil were strongly selected against in maize populations, while most k-mers for upright leaf angle were positively selected. In addition, phenotypic prediction of kernel oil, leaf angle, and flowering time using k-mer data showed at least a similarly high prediction accuracy to the standard SNP-based method. Collectively, our results demonstrated the bridging role of k-mers for data integration and functional gene discovery.

Morphological characterization of 3 potential lines Cempo Ireng black rice result of Gamma-Ray irradiation

Gamma-ray irradiation on Cempo Ireng can lead to the variation of morphological characteristics; hence, morphological characterization is necessary to determine changes in potential lines. This research aimed to characterize the potential lines as one of the requirements for proposing plant variety release and add black rice genetic diversity information. The research was carried out in the rice fields of Pakahan Village, Jogonalan, Klaten in January-June 2020 with the arrangement of potential lines 8,13 and 44 of M6 in a row. In total 30 plants were selected randomly for each potential line and observed 19 morphological characters. Data analysis was carried out descriptively and qualitatively with the Chi-Square test. The results showed that gamma-ray irradiation affects the characters of leaf angle, auricle color, ligule color, leaf-blade color, leaf surface, panicle type, grain color, apiculus color, and rice length. Potential line 8 had different characteristics compared to non-irradiated Cempo Ireng in the characters of auricle color, leaf-blade color, leaf width, panicle length, grain width, rice length, and rice width, while on potential lines 13 and 44 occur in the characters of the leaf surface and panicle length.

Identification of Genetic Loci for Sugarcane Leaf Angle at Different Developmental Stages by Genome-Wide Association Study

Background Sugarcane (Saccharum spp.) is an efficient crop mainly used for sugar and bioethanol production. High yield and high sucrose of sugarcane is always the fundamental demands in sugarcane growth worldwide. Leaf angle and size of sugarcane can be attributed to planting density, which was associated with yield. In this study, we performed Genome-Wide Association Studies (GWAS) in a panel of 216 sugarcane core parents and their derived lines (natural population) to determine the genetic basis of leaf angle and key candidate genes at seedling, elongation and maturity stage. Results A total of 288 significant associated loci of sugarcane leaf angle at different developmental Stages were identified by GWAS. Among them, one key locus and eleven loci was identified in all three stages and two stages, respectively. Overall, 4089 genes were located in the confidence interval of significant loci, among which 3892 genes were functionally annotated. Finally, thirteen core parents and their derivatives tagged with SNPs were selected for Marker-assisted selection (MAS). Conclusion These candidate genes are mainly related to MYB transcription factors, auxin response factors, serine/threonine-protein kinases, etc. The are directly or indirectly associated with leaf angle in sugarcane. This research provided a large number of novel genetic resources for the improvement of leaf angles and simultaneously to high yield and high bioethanol production.