Plant architecture and leaf color are important factors influencing cotton fiber yield. In this study, based on genetic analysis, stem paraffin sectioning, and phytohormone treatments, we showed that the dwarf-red (DR) cotton mutant is a gibberellin-sensitive mutant caused by a mutation in a single dominant locus, designated GhDR. Using bulked segregant analysis (BSA) and genotyping by target sequencing (GBTS) approaches, we located the causative mutation to a ~197-kb genetic interval on chromosome A09 containing 25 annotated genes. Based on gene annotation and expression changes between the mutant and normal plants, GH_A09G2280 was considered to be the best candidate gene responsible for the dwarf and red mutant phenotypes. A 2-nucleotide deletion was found in the coding region of GhDR/GH_A09G2280 in the DR mutant, which caused a frameshift and truncation of GhDR. GhDR is a homolog of Arabidopsis AtBBX24, and encodes a B-box zinc finger protein. The frameshift deletion eliminated the C-terminal nuclear localization domain and the VP domain of GhDR, and altered its subcellular localization. A comparative transcriptome analysis demonstrated downregulation of the key genes involved in gibberellin biosynthesis and the signaling transduction network, as well as upregulation of the genes related to gibberellin degradation and the anthocyanin biosynthetic pathway in the DR mutant. The results of this study revealed the potential molecular basis by which plant architecture and anthocyanin accumulation are regulated in cotton.  

In this study, lambda-cyhalothrin (LC) loaded polyurea microcapsules (MCs) with different particle sizes were fabricated.  All of the MCs showed varying degrees of physical collapse, which was more obvious among those with smaller particle sizes.  MCs with particle sizes of 1.38 μm (MC-S), 5.13 μm (MC-M) and 10.05 μm (MC-L) had shell thicknesses of 39.6, 50.3 and 150.1 nm, respectively.  MCs with smaller particles tended to have significantly faster release profiles, and the MC-S group had much higher bioactivity against Agrotis ipsilon and better foliar affinity on the peanut leaves (indicated by rainfastness) than MC-M and MC-L.  All of the MCs exhibited light-enhanced release profiles and had much slower degradation compared with the emulsifiable concentrate (EC) group, among which MC-L had the slowest degradation.  To generate MCs with both favorable quick efficacy and long-lasting efficacy, binary mixtures of MC-S, MC-M and MC-L were produced by mixing them in pairs at ratios of 2:1, 1:1 and 1:2.  The mixture of MC-S:MC-L at 1:2 showed the best comprehensive efficacy in the peanut foliar spray scenario among the nine tested combinations, and its effective duration was three times longer than that of EC.  Overall, the precise combination of MCs with different particle sizes can regulate the efficacy of pesticide control and serve as a strategy for the better utilization of pesticides.

Soil depth is critical for eco-hydrological modeling, carbon storage calculation and land evaluation.  However, its spatial variation is poorly understood and rarely mapped.  With a limited number of sparse samples, how to predict soil depth in a large area of complex landscapes is still an issue.  This study constructed an ensemble machine learning model, i.e., quantile regression forest, to quantify the relationship between soil depth and environmental conditions.  The model was then combined with a rich set of environmental covariates to predict spatial variation of soil depth and straightforwardly estimate the associated predictive uncertainty in the 140 000 km² Heihe River basin of northwestern China.  A total of 275 soil depth observation points and 26 covariates were used.  The results showed a model predictive accuracy with coefficient of determination (R²) of 0.587 and root mean square error (RMSE) of 2.98 cm (square root scale), i.e., almost 60% of soil depth variation explained.  The resulting soil depth map clearly exhibited regional patterns as well as local details.  Relatively deep soils occurred in low lying landscape positions such as valley bottoms and plains while shallow soils occurred in high and steep landscape positions such as hillslopes, ridges and terraces.  The oases had much deeper soils than outside semi-desert areas, the middle of an alluvial plain had deeper soils than its margins, and the middle of a lacustrine plain had shallower soils than its margins.  Large predictive uncertainty mainly occurred in areas with a lack of soil survey points.  Both pedogenic and geomorphic processes contributed to the shaping of soil depth pattern of this basin but the latter was dominant.  This findings may be applicable to other similar basins in cold and arid regions around the world.

Carex rigescens (Franch.) V. Krecz is a wild turfgrass perennial species in the Carex genus that is widely distributed in salinised areas of northern China.  To investigate genome-wide salt-response gene networks in C. rigescens, transcriptome analysis using high-throughput RNA sequencing on C. rigescens exposed to a 0.4% salt treatment (Cr_Salt) was compared to a non-salt control (Cr_Ctrl).  In total, 57 742 546 and 47 063 488 clean reads were obtained from the Cr_Ctrl and Cr_Salt treatments, respectively.  Additionally, 21 954 unigenes were found and annotated using multiple databases.  Among these unigenes, 34 were found to respond to salt stress at a statistically significant level with 6 genes up-regulated and 28 down-regulated.  Specifically, genes encoding an EF-hand domain, ZFP and AP2 were responsive to salt stress, highlighting their roles in future research regarding salt tolerance in C. rigescens and other plants.  According to our quantitative RT-PCR results, the expression pattern of all detected differentially expressed genes were consistent with the RNA-seq results.  Furthermore, we identified 11 643 simple sequence repeats (SSRs) from the unigenes.  A total of 144 amplified successfully in the C. rigescens cultivar Lüping 1, and 69 of them reflected polymorphisms between the two genotypes tested.  This is the first genome-wide transcriptome study of C. rigescens in both salt-responsive gene investigation and SSR marker exploration.  Our results provide further insights into genome annotation, novel gene discovery, molecular breeding and comparative genomics in C. rigescens and related grass species.

To deal with the global and regional issues including food security, climate change, land degradation, biodiversity loss, water resource management, and ecosystem health, detailed accurate spatial soil information is urgently needed.  This drives the worldwide development of digital soil mapping.  In recent years, significant progresses have been made in different aspects of digital soil mapping.  The main purpose of this paper is to provide a review for the major progresses of digital soil mapping in the last decade.  First, we briefly described the rise of digital soil mapping and outlined important milestones and their influence, and main paradigms in digital soil mapping.  Then, we reviewed the progresses in legacy soil data, environmental covariates, soil sampling, predictive models and the applications of digital soil mapping products.  Finally, we summarized the main trends and future prospect as revealed by studies up to now.  We concluded that although the digital soil mapping is now moving towards mature to meet various demands of soil information, challenges including new theories, methodologies and applications of digital soil mapping, especially for highly heterogeneous and human-affected environments, still exist and need to be addressed in the future.

Abscisic acid (ABA), as one of the foremost signaling molecules in plants, is an important hormone which plays versatile functions in regulating developmental process and adaptive stress process.  A set of introgression lines were previously generated via a backcrossing program using an elite indica cultivar rice Teqing (O. sativa L.) as recipient and an accession of Yuanjiang common wild rice (O. rufipogon Griff.) as donor.  In this study, the previously developed introgression lines were evaluated for ABA sensitivity.  Here we reported that a total of 14 quantitative trait loci (QTLs) associated with ABA sensitivity were identified.  An ABA sensitive introgression line, YIL53, was identified and characterized.  Physiological characterization, including chlorophyll content, malondialdehyde content, soluble sugar content, and stomata movement, demonstrated that YIL53 exhibited the characteristics associated with ABA sensitivity.  Genotypic analysis revealed that YIL53 harbored one QTL related to ABA sensitivity, qASS1-2, which was located on chromosome 1 within one introgressed segment derived from the Yuanjiang common wild rice.  Furthermore, the qASS1-2 was finally narrowed down to a 441-kb region between simple sequence repeats (SSR) marker RM212 and single nucleotide polymorphism (SNP) marker M3 using the segregation population derived from the cross between Teqing and YIL53, and three candidate genes associated with ABA sensitivity were identified using a strategy combined gene expression analysis with QTL mapping.  Identification of the QTLs related to ABA sensitivity and characterization of the ABA sensitive line YIL53 would provide a helpful basis for isolating novel genes related to ABA sensitivity.  

Peanut (Arachis hypogaea L.), an improtant oil crop, usually encounters drought stress in the process of growth and development, especially at pre-flowering stage.  In order to gain insight into the drought tolerance potentials based on osmolyte accumulation and metabolism of proline aspects of peanut, pot experiments were conducted with a split-plot design in Tai’an, Shangdong Province, China in 2013 and 2014.  Pre-flowering drought (PFD) stress and optinum irrigation (control, CK) were served as the main plots and the two peanut cultivars Shanhua 11 and Hua 17 served as sub-plots.  Shanhua 11 was drought-tolerant cultivar and Hua 17 was drought-sensitive.  The content of soluble sugars, soluble protein, free proline and other free amino acids, the activities of enzymes involved in proline metabolism, and malondialdehyde (MDA) content and ion leakage were all investigated in the two cultivars at pre-flowering stage.  Results showed that PFD stress significantly increased the levels of soluble protein, free proline and free amino acid, and increased Δ¹-pyrroline-5-carboxylate synthetase (P-5-CS, EC 2.7.2.11) activity in the leaves of drought-tolerant and drought-sensitive cultivars.  The activity of proline dehydrogenase (proDH) (EC 1.5.99.8) decreased under PFD stress in both cultivars.  The leaves of the tolerant cultivar maintained higher increments of osmolyte levels, lower increments of MDA content and ion leakage, as well as a higher increased proportion of P-5-CS activity and higher inhibited proportion of proDH activity under water stress compared with the drought-sensitive cultivar.  The study suggests that proline accumulation in peanut leaves under PFD can be explained by the higher enhanced activities of P-5-CS and higher inhibition of proDH.  The results will provide useful information for genetic improvement of peanut under drought tolerance.

The highbush blueberry (Vaccinium corymbosum), Duke, was used to construct a de novo transcriptome sequence library and to perform data statistical analysis.  Mega 4, CLC Sequence Viewer 6 software, and quantitative PCR were employed for bioinformatics and expression analyses of the basic helix-loop-helix (BHLH) transcription factors of the sequencing library.  The results showed that 28.38 gigabytes of valid data were obtained from transcriptome sequencing and were assembled into 108 033 unigenes.  Functional annotation showed that 32 244 unigenes were annotated into Clusters of Orthologous Groups (COG) and Gene Ontology (GO) databases, whereas the rest of the 75 789 unigenes had no matching information.  By using COG and GO classification tools, sequences with annotation information were divided into 25 and 52 categories, respectively, which involved transport and metabolism, transcriptional regulation, and signal transduction.  Analysis of the transcriptome library identified a total of 59 BHLH genes.  Sequence analysis revealed that 55 genes of that contained a complete BHLH domain.  Furthermore, phylogenetic analysis showed that BHLH genes of blueberry (Duke) could be divided into 13 sub-groups.  PCR results showed that 45 genes were expressed at various developmental stages of buds, stems, leaves, flowers, and fruits, suggesting that the function of BHLH was associated with the development of different tissues and organs of blueberry, Duke.  The present study would provided a foundation for further investigations on the classification and functions of the blueberry BHLH family.

Pepper (Capsicum annuum. L.) is a widely cultivated vegetable crop worldwide and has the second largest planting area and the first largest vegetable output and value in China.  Pepper root-knot nematode (Meloidogyne spp.) is one of the most serious pests of pepper, which caused huge losses every year.  Previous studies showed that the Me3 gene is resistant to a wide range of Meloidogyne species, including M. arenaria, M. javanica, and M. incognita.  HDA149, a double haploid pepper genotype, harboring the root-knot nematode resistance gene Me3, was used to construct bacterial artificial chromosome library (BAC) via the vector of CopyControl^TM pCC1 in this study.  The library consists of 210 200 BAC clones and is equivalent to 5.3 pepper genomes.  The average insert size is 95 kb, and most of them are 90–120 kb; but the empty clones are less than 3%.  In order to screen the BAC library easily, 550 super pools with 384 BAC clones of each pool were further developed in this study.  Specific primers from Me3 gene locus were used for BAC library screening, and more than 20 positive BAC clones were obtained.  Then the selected positive BAC clones were analyzed by restriction enzyme digestion, BAC-end sequencing, marker development, and new positive BAC clones exploration, respectively.  Finally, the contig with total length of about 300 kb linked to the Me3 locus was constructed based on chromosome walking strategy, which made a solid foundation for the cloning of the important root-knot nematode resistance gene Me3.

Rice (Oryza sativa L.), a tropical and subtropical crop, is susceptible to low temperature stress during seedling, booting, and flowering stages, which leads to lower grain quality levels and decreasing rice yields. Cold tolerance is affected by multiple genetic factors in rice, and the complex genetic mechanisms associated with chilling stress tolerance remain unclear. Here, we detected seven quantitative trait loci (QTLs) for cold tolerance at booting stage and identified one cold tolerant line, SIL157, in an introgression line population derived from a cross between the indica variety Guichao 2, as the recipient, and Dongxiang common wild rice, as the donor. When compared with Guichao 2, SIL157 showed a stronger cold tolerance during different growth stages. Through an integrated strategy that combined QTL-mapping with expression profile analysis, six candidate genes, which were up-regulated under chilling stress at the seedling and booting developmental stages, were studied. The results may help in understanding cold tolerance mechanisms and in using beneficial alleles from wild rice to improve the cold tolerance of rice cultivars through molecular marker-assisted selection.

A rapid and reliable method was developed for analysis of ethephon residues in maize, in combination with the investigation of its dissipation in field condition and stabilities during the sample storage. The residue analytical method in maize plant, maize kernel and soil was developed based on the quantification of ethylene produced from the derivatization of ethephon residue by adding the saturated potassium hydroxide solution to the sample. The determination was carried out by using the head space gas chromatography with flame ionization detector (HS-GC-FID). The limit of quantification (LOQ) of the method for maize plant was 0.05, 0.02 mg kg–1 for maize kernel and 0.05 mg kg–1 for soil, respectively. The fortified recoveries of the method were from 84.6–102.6%, with relative standard deviations of 7.9–3.8%. Using the methods, the dissipation of ephethon in maize plant or soil was investigated. The half life of ethephon degradation was from 0.6 to 3.3 d for plant and 0.7 to 5.7 d for soil, respectively. The storage stabilities of ethephon residues were determined in fresh and dry kernels with homogenization and without homogenization process. And the result showed that ethephon residues in maize kernels were stable under –18°C for 6 mon. The results were helpful to monitor the residue dissipation of ethephon in the maize ecosystem for further ecological risk assessment.

The objective of this study was to determine the relationship between seed yield and other important agronomic traits ofearly-maturing rapeseed as a rotation crop in a double-cropping rice area using Pearson’s correlation coefficient as well asto estimate direct and indirect effects of specific yield component traits on seed yield via path analysis. Nineteen rapeseedgenotypes were grown at ten environments in South China during 2008-2009 and 12 characters were evaluated. Analysisof variance showed that environment had a significant impact on all characters. For most characters the genotype byenvironment interaction was weak and not statistically significant. Simple correlation analysis indicated that the numberof primary branches (PB), number of pods on the main raceme (PR), and number of seeds per pod made significantcontributions to seed yield per plant (SYP), while 1 000-seed weight was negatively correlated with SYP (r=-0.485, P<0.05).Furthermore, number of pods per plant (PP), PB, and PR had the greatest direct effects on SYP. In addition, PP and PB werethe best indicators to predict seed yield in stepwise regression analysis. Finally, yield component differences betweenearly- and medium-maturity varieties were compared; this showed that to improve the seed yield of early varieties, moreemphasis should be given to increase PP, PB, and PR, and reduce plant height and shortening of growth duration inbreeding practice.

Data assimilation in agricultural remote sensing research is of great significance to integrate with remote sensing observations and model simulations for parameters estimation. The present investigation not only designed and realized the Ensemble Kalman Filtering algorithm (EnKF) assimilation by combing the crop growth model (CERES-Wheat) with remote sensing data, but also optimized and updated the key parameters (LAI) of winter wheat by using remote sensing data. Results showed that the assimilation LAI and the observation ones agreed with each other, and the R2 reached 0.8315. So assimilation remote sensing and crop model could provide reference data for the agricultural production.