Infrared Thermal Imaging as a Rapid Tool for Identifying Water‐Stress Tolerant Maize Genotypes of Different Phenology

The main task of this research was to evaluate canopy temperature and Crop Water Stress Index (CWSI) by assessing genotype variability of maize performance for different water regimes. To that end, three hundred tropical and subtropical maize hybrids with different phenology in terms of date of anthesis were evaluated. The influence of phenology on the change in canopy temperatures and CWSI was not equal during the three dates of measurement. At the end of vegetative growth (82 days after sowing, DAS) and at the blister stage (DAS 97), a high significant difference in temperatures and CWSI (P < 0.001) were obtained between the early‐ and late‐maturity genotypes. During anthesis (DAS 89), phenology had a significant effect (P < 0.01) only for the well‐watered genotypes, while under water‐stress conditions, no differences were found between early and late genotypes in terms of canopy temperature and CWSI. High significant differences (P < 0.001) in stomatal conductance (g_s) between early and late genotypes for different treatments were observed. A relationship (R² = 0.62) between g_s and canopy temperature was obtained. Under a water‐stress canopy, temperature was measured at anthesis, which was negatively correlated with grain yield of the early (r = ?0.55)‐ and late (r = ?0.46)‐maturity genotypes in the water‐stressed condition.     

Breeding for insect resistance in oilseed rape: Challenges,current knowledge and perspectives

Dealing with insect pests is one of the biggest challenges facing the cultivation of oilseed rape (Brassica napus, OSR). Insect pests are usually controlled using insecticides, but the increasing occurrence of insecticide‐resistant populations and the socio‐economic context argue against the sole use of these substances. Plant resistance is a classical and proven alternative crop protection strategy that is the basic tool of integrated pest management. However, no insect‐resistant OSR cultivar is currently available on the market. Here, I review some of the constraints that make phenotyping for insect resistance particularly challenging with OSR and give perspectives to develop this resistance. Some studies have proved that breeding OSR for insect resistance could be achieved, and three strategies have been considered: introducing resistance transgenes into the OSR genome, exploiting natural variation in resistance already present in B. napus and introgressing resistance from other brassicaceous species. The white mustard, Sinapis alba, seems a particularly promising source of resistance against most of the OSR insect pests.     

Fine mapping quantitative trait loci under selective phenotyping strategies based on linkage and linkage disequilibrium criteria

In fine mapping of a large‐scale experimental population where collection of phenotypes are very expensive, difficult to record or time‐demanding, selective phenotyping could be used to phenotype the most informative individuals. Linkage analyses based sampling criteria (LAC) and linkage disequilibrium‐based sampling criteria (LDC) for selecting individuals to phenotype are compared to random phenotyping in a quantitative trait loci (QTL) verification experiment using stochastic simulation. Several strategies based on LAC and LDC for selecting the most informative 30%, 40% or 50% of individuals for phenotyping to extract maximum power and precision in a QTL fine mapping experiment were developed and assessed. Linkage analyses for the mapping was performed for individuals sampled on LAC within families and combined linkage disequilibrium and linkage analyses was performed for individuals sampled across the whole population based on LDC. The results showed that selecting individuals with similar haplotypes to the paternal haplotypes (minimum recombination criterion) using LAC compared to random phenotyping gave at least the same power to detect a QTL but decreased the accuracy of the QTL position. However, in order to estimate unbiased QTL parameters based on LAC in a large half‐sib family, prior information on QTL position was required. The LDC improved the accuracy to estimate the QTL position but not significantly compared to random phenotyping with the same sample size. When applying LDC (all phenotyping levels), the estimated QTL effect were closer to the true value in comparison to LAC. The results showed that the LDC were better than the LAC to select individuals for phenotyping and contributed to detection of the QTL.     

基于四旋翼无人机快速获取大田植株图像的方法及其应用

利用低空无人机获取农田信息,具有实时以及灵活性高、成本低等优势。为快速、精确监测大田规模化种植作物的生长发育状况,以四旋翼无人机为平台,结合数字图像技术,建立快速获取大田烟株中前期图像的方法。结果表明,在天空辐射条件较稳定的条件下,采用较低的飞行高度(如20m)航拍获取田块图像,能够得到清晰的拼接图像和三维重建效果;采用基于决策树的植被分割算法将烟草和非植被部分分割后,得到较高精度的大田植株图像。在此基础上进行大田烟草缺苗数估测,所估算的缺苗数与实测值吻合较好。     

Predicting quantitative host plant resistance against phoma black stem in sunflower

Phoma black stem is an important disease in sunflower, against which no specific management method is currently deployed in France. Relevant phenotyping methods for quantitative resistance are critical for integration of this trait into breeding programmes. Components of resistance associated with physiological resistance, and morphological traits associated with disease escape were measured on 21 sunflower genotypes under growth chamber (on seedlings), greenhouse (on adult plants), and field conditions, together with disease intensity in the field. Potential predictors were first selected for sensitivity and robustness from mixed model anova s. Analyses involving ranking tests and logistic regressions were then performed to identify predictors for field resistance. The identification of predictors for resistance involved analyses conducted in two broad steps: process‐oriented experiments, and epidemic‐oriented experiments. This stepwise approach departs from many studies aimed at identifying predictors for field resistance, which rely mainly on the computation of correlation coefficients between predictors and measured field disease variables. Predictors for quantitative resistance were identified: (i) lesion length and lesion expansion on stems of plants before flowering stage, and (ii) lesion length on first leaf petioles of seedlings. A high number of leaves and tall plants were associated with disease escape. Control genotypes for susceptibility and quantitative resistance were identified, and implications for breeding and improvements were derived from this work.     

Root phenotyping: important and minimum information required for root modeling in crop plants

As plants cannot relocate, they require effective root systems for water and nutrient uptake. Root development plasticity enables plants to adapt to different environmental conditions. Research on improvements in crop root systems is limited in comparison with that in shoots as the former are difficult to image. Breeding more effective root systems is proposed as the “second green revolution”. There are several recent publications on root system architecture (RSA), but the methods used to analyze the RSA have not been standardized. Here, we introduce traditional and current root-imaging methods and discuss root structure phenotyping. Some important root structures have not been standardized as roots are easily affected by rhizosphere conditions and exhibit greater plasticity than shoots; moreover, root morphology significantly varies even in the same genotype. For these reasons, it is difficult to define the ideal root systems for breeding. In this review, we introduce several types of software to analyze roots and identify important root parameters by modeling to simplify the root system characterization. These parameters can be extracted from photographs captured in the field. This modeling approach is applicable to various legacy root data stored in old or unpublished formats. Standardization of RSA data could help estimate root ideotypes.     

胚乳性状测定方法对QTL遗传效应估计的影响

从理论上分析了不正确地基于胚乳性状测定方法的QTL定位方法造成遗传效应估计偏差的原因,并通过计算机模拟验证;同时探讨了胚乳性状测定方法对胚乳性状QTL的遗传效应估计结果的影响,并指出今后胚乳性状QTL定位的研究方向.     

Population structure of Phytophthora infestans in Turkey reveals expansion and spread of dominant clonal lineages and virulence

Late blight, caused by the oomycete Phytophthora infestans, is considered the most important and destructive disease of potato in Turkey. In this study, characterization of 367 isolates of P. infestans obtained from the potato-growing areas of the country was carried out to evaluate the pathogen population structure over the 2017–2019 production seasons. The isolates were characterized by numerous features including mating type, in vitro mefenoxam sensitivity, simple-sequence repeat (SSR) markers, and virulence against a set of potato differential lines. Most isolates were A2 mating type (353 isolates). Also, 68% of isolates were resistant to mefenoxam; the remainder were intermediate in their sensitivity and there were no sensitive isolates. SSR-based genotypic analysis of P. infestans populations showed a low genetic diversity. The 13_A2 clonal lineage predominated with a frequency of 92.1%, followed by 34_A1 (3.3%) and 37_A2 (2.7%). Genotypes 34_A1 and 37_A2 were detected only in 2019. This is the first report of 34_A1 and 37_A2 clonal lineages causing late blight disease of potato in Turkey. The most abundant virulence type was one overcoming resistance genes R1, R2, R3, R4, R6, R7, R10, and R11. These results emphasized that the migration of individuals and the asexual generation of subclonal differences were the main factors driving the population structure of P. infestans in Turkey.     

Using image analysis for quantitative assessment of needle bladder rust disease of Norway spruce

High elevation spruce forests of the European Alps are frequently infected by the needle rust Chrysomyxa rhododendri, a pathogen causing remarkable defoliation, reduced tree growth and limited rejuvenation. Exact quantification of the disease severity on different spatial scales is crucial for monitoring, management and resistance breeding activities. Based on the distinct yellow discolouration of attacked needles, it was investigated whether image analysis of digital photographs can be used to quantify disease severity and to improve phenotyping compared to conventional assessment in terms of time, effort and application range. The developed protocol for preprocessing and analysis of digital RGB images enabled identification of disease symptoms and healthy needle areas on images obtained in ground surveys (total number of analysed images n = 62) and by the use of a semiprofessional quadcopter (n = 13). Obtained disease severities correlated linearly with results obtained by manual counting of healthy and diseased needles for all approaches, including images of individual branches with natural background (R² = 0.87) and with black background (R² = 0.95), juvenile plants (R² = 0.94), and top views and side views of entire tree crowns of adult trees (R² = 0.98 and 0.88, respectively). Results underline that a well‐defined signal related to needle bladder rust symptoms of Norway spruce can be extracted from images recorded by standard digital cameras and using drones. The presented protocol enables precise and time‐efficient quantification of disease symptoms caused by C. rhododendri and provides several advantages compared to conventional assessment by manual counting or visual estimations.