Phenotyping peanut cultivars with contrasting responses to pod rot pathogens

doi:10.21203/rs.3.rs-2269767/v1

Download PDF

Short Report

Phenotyping peanut cultivars with contrasting responses to pod rot pathogens

https://doi.org/10.21203/rs.3.rs-2269767/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

In recent years, soil-borne diseases including pod rot have become increasingly rampant with climate change, causing serious yield and quality losses to peanut. Resistance breeding is considered an effective measure for pod rot management. Nine peanut cultivars with various degrees of resistance were used to study leaf/shell anatomical and shell biochemical features, main agronomic traits and leaf spot disease ratings in relation to pod rot score. All four anatomical features, viz., leaf palisade cell number, cell width, index and shell lignin staining area, were negatively correlated with peanut pod rot score at 0.01 levels. However, a robust association between shell lignin content and pod rot score was not established. Given the stable and strong correlation between these anatomical features and pod rot scores and high heritability estimates of these features, the pre-existing resistance may be identified even in the absence of disease. This study provided useful selection indicators for screening for resistance to pod rot in peanut. Association analysis of peanut pod rot resistance is being carried out at our laboratory using several natural populations phenotyped in multiple environments. Particular attention will be paid to the relationship between resistance and these indicators from a genetic perspective.

Groundnut

Pod breakdown

Heritability

Correlation analysis

Anatomy

Leaf

Shell

Peanut (Arachis hypogaea L.) is a major cash crop cultivated worldwide that can be crushed for cooking oil and more importantly, processed into a variety of food products, as whole pods, whole seeds, peanut butter and as food ingredients. Peanut pod rot, formerly known as peanut pod breakdown, caused mainly by Pythium myriotylum Drechs., Rhizoctonia solani Kuhn, and Fusarium solani (Mart.) Sacc.(Porter et al. 1997), has become increasingly prevalent with climate change, and may incur large quality and yield losses. In Huanghuaihai region, the main peanut producer of China, all the three causal pathogens were reported, with F. solani and P. myriotylum predominating (Chi et al. 2016; Yu et al. 2019, 2020b; Lu et al. 2022). Studies demonstrated that prophylactic calendar-based applications at early pegging phase had a lower risk of segregation 2 kernels at harvest compared to threshold-based fungicide application, and should therefore be recommended (Wheeler et al. 2016). Recently, some fungicides were tested in the laboratory and in pot culture with 96.8% Fudioxonil having the highest average control efficacy (56.25%) (Yu et al. 2020a). However, the most convenient and economically viable measure would be the adoption of disease resistant cultivars in pod rotting prone field (Yu et al. 2020b).

In the USA, Early Runner, Florunner, Floriglant and NC 17 showed consistent resistance to infection by pod breakdown pathogens P. myriotylum and R. solani in field conditions (Porter et al. 1975). Toalson and NC 8c were identified as having resistance to P. myriotylum and R. solani pod rot and Pythium pod rot, respectively (Wang and Zhang 2013). In Taiwan, totally 1242 peanut cultivars/lines were screened for pod rot resistance in field. Among them, four Valencia type entries (VAl11, VAl14, VA220, VA221) and 1 Virginia bunch genotype (VB186) were relatively resistant (Yang et al. 2002). In mainland China, related studies commenced only recently. From a natural disease nursery for pod rot in Hebei province, 2 genotypes with high resistance (Grifl4051, PI 502111), 6 with resistance, and 32 with medium resistance were identified from a total of 116 peanut germplasm accessions (He et al. 2018). Likewise, in Shandong province, 2 genotypes with high resistance (Yuhanghua 7, Huayu 9115), 12 with medium resistance were found in 76 entries (Yu et al. 2020a). In Henan province, from 27 peanut cultivars/lines, 1 with high resistance (Yuhanghua 7), 3 with resistance, and 7 with medium resistance were identified (Lu et al. 2021); in a separate study, four with high resistance (Huayu 9623, Huayu 9624, Puhua 66, Jihua 9), one with resistance were obtained from 31 peanut cultivars/lines (Mr. Linchang Yang, personal communication). These findings provided a basis for an in-depth exploration of possible association between pod rot resistance and other traits in peanut.

The present study aimed to find out if anatomical characteristics of leaflets and shells do have some relations with peanut pod rot disease response as an earlier study indicated (Godoy et al. 1985), and if some shell biochemical components, agronomic characters and leaf spot disease ratings are associated with pod rot reaction and, where possible, to estimate broad-sense heritability of these traits, to contribute to the genetic improvement of multiple traits in peanut centered on resistance to pod rot.

Peanut cultivars

Nine peanut cultivars, including 3 with high resistance (Yuhanghua 7, Huayu 9624, Huayu 9623), 3 with medium resistance (Anhua 6, Huayu 958 and Huayu 9510), and 3 susceptible genotypes (Zhengnonghua 23, Huayu 917 and Huayu 51), were used in this study (Table 1).

Table 1

Pod rot scores and leaf palisade anatomical and shell biochemical features of the 9 peanut cultivars
Cultivar	Pod rot score	Leaf palisade anatomical feature			Shell lignin staining area (µm²/µm)	Shell biochemical feature (%)
Cultivar	Pod rot score	No. of cells/mm	Cell width (µm)	Index	Shell lignin staining area (µm²/µm)	Lignin	Hemicellulose	Cellulose
Yuhanghua 7	0	103.33a	8.97AB	927.44A	214.68A	15.23	13.60	5.51
Huayu 9624	0	93.33ab	10.21A	959.97A	182.59B	15.07	13.27	4.73
Huayu 9623	0	80.00bcd	10.35A	833.72AB	151.32CD	15.70	14.30	4.40
Anhua 6	0	83.33abc	8.80AB	731.98ABC	152.91C	14.73	13.33	5.32
Huayu 958	1	80.00bcd	7.44BC	601.26ABC	136.60CDE	15.77	13.73	4.99
Huayu 9510	1	73.33bc	8.31BC	608.90ABC	149.13CD	13.13	12.53	4.94
Zhengnonghua 23	2	70.00bc	7.50BC	522.60BC	124.99DE	13.27	14.07	4.77
Huayu 917	2	66.67c	7.05C	474.74BC	110.32E	14.77	15.00	5.71
Huayu 51	3	63.33c	6.94C	439.28C	114.71E	13.67	13.03	4.81
Within each column, the figures followed by the same uppercase letter were not significantly different at 0.01 probability level, and those followed by the same lowercase letter were not significantly different at 0.05 probability level.

Peanut cultivation, management, investigation and harvesting arrangements

The study was conducted at Shandong Peanut Research Institute Laixi Experimental Station. Peanuts were sown on May 13, 2022, under film mulch. Routine agronomic practices were followed (Wan 2003). Chemicals were sprayed to control insect pests, whereas no fungicides were used for disease management. Investigations on plant height, lodging, peg strength, leaf spots, and pod rot were made on September 5, 2022. Peanuts were harvested two days later (on September 7, 2022).

Sampling for studies on leaf and shell anatomy and shell biochemistry

For each cultivar, three mature pods, identified by the hull scrape method (Williams and Drexler 1981), were sampled on August 12 (92 days after sowing, DAS) to investigate sclerenchymatous mesocarps with phloroglucinol staining method.

To study the anatomy of peanut leaflets, the basal leaflet of the first leaf on the lower branches of each cultivar were sampled on August 18, 2022 (98 DAS). A section of the leaflet about 3 mm wide was further cut off in the middle of the leaflet, perpendicular to the medrib. Three replicates were made for each cultivar. Shells from mature peanut pods (Williams and Drexler 1981) were sampled on the same day to determine their lignin, cellulose and semi-cellulose content, and for each cultivar, three replicates of 10 g each were made.

Paraffin sectioning

Fresh tissues were fixed in FAA (formalin-aceto-alcohol) fixative for more than 24h. Thereafter, the tissue was removed from the fixative and trimmed flat with a scalpel in a fume hood. Trimmed tissue and its corresponding label were placed in a dehydration box.

The dehydration box was put in a Donatello Dehydrator (DIAPATH, Italy) for dehydration in a gradient alcohol sequence, followed by clearing and subsequent paraffin infiltration. The tissue was subjected to a series of treatments: 75% alcohol for 4h, 85% alcohol for 2h, 90% alcohol for 2h, 95% alcohol for 1h, absolute ethanol I for 30min, absolute ethanol II for 30min, alcoholic benzene for 5-10min, xylene (Sinopharm chemical reagent Co., Ltd., China) I for 5-10min, xylene II for 5-10min, 65°molten paraffin I 1h, 65°molten paraffin II 1h, 65°molten paraffin III 1h.

The paraffin-infiltrated tissue was then embedded using a RM2016 embedding machine (Wuhan Junjie Electronics Co., Ltd., China). Melted paraffin was first put into the embedding frame, and before the paraffin solidified, the tissue was removed from the dehydration box and placed into the embedding frame according to the requirements of the embedding surface and affixed with the corresponding label. The paraffin was cooled at -20°on a JB-L5 Frozen Platform (Wuhan Junjie Electronics Co., Ltd., China) and after the paraffin got solidified, the paraffin block was removed from the embedding frame and trimmed.

The trimmed paraffin block was cooled on the − 20°C Frozen Platform, and afterwards the cooled paraffin block was sectioned on a Leica RM 2016 Pathology slicer (Shanghai Leica Instruments Co., Ltd., China) at a thickness of 3 µm. The sections were floated on 40°C warm water in a KD-P organizer (Zhejiang Jinhua Kedi Instruments Co., Ltd., China) to flatten the tissue, and were picked up with a glass slide and baked in a 60°C GFL-230 Oven (Tianjin Lai Bo Rui Instruments Co. Ltd., China). After the water got dried and the paraffin was melted, the sections were removed and stored at room temperature for further use.

Section staining and microscopic examination

Peanut leaflet tissue

In turn the paraffin slides were placed into dewaxing clearing solution I (Servicebio, China) for 20min, dewaxing clearing solution II for 20min, absolute ethanol (Sinopharm Chemical Reagent Co., Ltd., China) I for 5min, absolute ethanol II for 5min, and 75% alcohol for 5min, followed by washing with tap water.

The slides were transferred into a plant safranine staining solution (Servicebio, China) and stained for 2h, and slightly washed with tap water to remove excess dye. The slides were then put into 50%, 70% and 80% gradient alcohols for 3-8s each in turn.

The sections were placed into a plant fast green staining solution (Servicebio, China) and stained for 6-20s. Dehydration was performed with three absolute ethanol treatments.

The sections were cleared in xylene for 5min, and mounted in neutral gum (Sinopharm chemical reagent Co., Ltd., China).

Anatomical observations were made under a Nikon Eclipse E100 Upright optical microscope (Nikon, Japan). Image acquisition was performed using a Nikon DS-U3 Imaging system (Nikon, Japan). Number of palisade cells within a length of 200 µm was counted with 3 replicates. Palisade cell width with 3 replicates was recorded. Index = Number of palisade cells/µm × Palisade cell width (µm) (Godoy et al. 1985).

Peanut shell tissue

The procedure for section dewaxing was the same as described above. After dewaxing and tap water washing, the sections were stained in a phloroglucinol C (Servicebio, China) solution for 5s, washed with water and air dried.

The tissues were enclosed with a histochemical pen, covered with an appropriate amount of a phloroglucinol B (Servicebio, China) solution using a Pasteur pipet, stained for 30s, and an appropriate amount of phloroglucinol A (Servicebio, China) solution was added on the tissue with another clean pipette and blew to mix evenly, and the tissue was stained for 2min.

After removal of part of the staining solution with a pipette, the section was sealed with a coverslip, and photos were taken within 3 min to avoid color fade. Shell lignin staining area every 500µm long was measured 9 times for each cultivar.

Measurement of main agronomic characters and disease and lodging rating

Data including main stem height, 100-pod weight, 100-seed mass, and shelling percentage were collected following the procedure described by Yu (2008). For each cultivar, four mature pods from the first nodes of the cotyledonary branches were chosen for peg strength measurement using a tensiometer (HandPI HP-50, China).

Chlorophyll content in the two apical leaflets on the third branch of peanut plants was measured quantitatively using a SPAD-502 chlorophyll meter (Konica Minolta, Japan). Two plants of each cultivar were measured, and the average of 2 SPAD readings was recorded.

Near infrared spectroscopy (NIRS) was used to predict the content of major fatty acids (oleic, linoleic and palmitic acids, as a percentage of total), oil, protein and total soluble sugars (TSS) in sun-dried bulk kernel samples (Wang and Zhang 2013). Each sample was measured three times, and the averages were used in analysis.

Leaf spot disease and pod rot severity, and lodging status were scored separately on a 0–3 scale, where 0 = free of symptom, 1 = slight, 2 = medium, and 3 = severe. Specifically, for leaf spots, 0 = no disease lesions, 1 = 0 < leaf lesion area ≤ 25%, 2 = 25%< leaf lesion area ≤ 50%, 3 = leaf lesion area > 50%; for pod rot, 0 = no rotten pods, 1 = 0 < rotten pods ≤ 25%, 2 = 25%<rotten pods ≤ 50%, 3 = rotten pods > 50%; for lodging status, 0 = no lodging, 1 = 0 < lodging plants ≤ 25%, 2 = 25%<lodging plants ≤ 50%, 3 = lodging plants > 50%.

Shell biochemical assay

Lignin, hemicellulose and cellulose content in peanut shells was determined by wet chemistry methods .

Statistical analysis

Analysis of variance and multiple comparisons based on Duncan’s multiple range method (DMRT), broad-sense heritability estimation and correlation analysis were performed using the DPS 14.50 package.

Association of leaf and shell anatomical traits with peanut pod rot resistance

The 9 cultivars with contrasting responses to pod rot disease showed remarkable difference in leaf and shell anatomy. As shown in Fig. 1, the leaf palisade cells were arranged in a compact manner, in contrast to the sparse arrangement in the susceptible cultivar. As illustrated in Fig. 2, phloroglucinol-stained sclerenchymatous mesocarp was thicker in the resistant genotype, while it was much thinner in the susceptible cultivar.

For quantitative indicators, significant differences in leaf palisade cell number, cell width and index were detected at 0.05, 0.01 and 0.01 probability levels, respectively, whereas there were no statistically significant differences in shell lignin, hemicellulose and cellulose content among the peanut cultivars (Table 1).

In 2022, during peanut growth period, our experimental farm received unexpected heavy rains. Pod rot severity of each entry was therefore checked by careful visual inspection. Scores of the 9 cultivars were listed in Table 1. Both Pearson correlation coefficients and Spearman rank correlation coefficients between the pod rot scores and leaf/shell anatomical and shell biochemical features were calculated, based on averages and individual measurements (Table 2). All the 4 anatomical traits were negatively correlated with pod rot scores at 0.01 level, and the absolute values of the 8 rank correlation coefficients related to anatomical indicators, ranging from 0.6745 to 0.9487, were all higher than those of the corresponding Pearson correlation coefficients (0.6452–0.9078). Only two (-0.3820 and − 0.3924) of the four correlation coefficients (Pearson and Spearman) between shell lignin content and pod rot score were significant at 0.05 level. Shell hemicellulose and cellulose content had no significant relationships with pod rot score (Table 2).

Table 2

Relationships between leaf/shell anatomical and shell biochemical features and pod rot scores, and broad-sense heritability estimates
Parameter	Leaf palisade anatomical feature			Shell lignin staining area (µm²/µm)	Shell biochemical feature (%)
Parameter	No. of cells (cells/mm)	Cell width (µm)	Index	Shell lignin staining area (µm²/µm)	Lignin	Semi-cellulose	Cellulose
Average-based Pearson correlation coefficient	-0.8387**	-0.8599**	-0.9078**	-0.7953*	-0.5968	0.0959	0.0376
Average-based Spearman rank correlation coefficient	-0.9262**	-0.9135**	-0.9487**	-0.9223**	-0.4919	0.0264	0.1142
Per measurement-based Pearson correlation coefficient	-0.6452**	-0.7916**	-0.7716**	-0.6794**	-0.3820*	0.0550	0.0251
Per measurement-based Spearman rank correlation coefficient	-0.6745**	-0.8679**	-0.8367**	-0.7400**	-0.3924*	0.0029	0.0777
Average-based broad-sense heritability (%)	69.33	92.00	82.96	88.59	-	-	-
Per measurement-based broad-sense heritability (%)	42.97	79.31	61.87	72.14	-	-	-
Correlation coefficients marked with an asterisk or double asterisks were significant at 0.05 or 0.01 level, respectively.

Heritability estimates of leaf and shell anatomical features

Broad-sense heritability estimates of the 4 anatomical traits varied from 69.33%-92.00% (average basis) and 42.79%-79.31% (per measurement basis) (Table 2).

Main agronomic characters, leaf spot disease ratings and their relationships to pod rot score

The peanut cultivars tested significantly differed in leaf SPAD reading, peg strength, and kernel biochemical composition data at 0.01 probability levels (Table 3).

Table 3

Main agronomic characters and leaf spot disease rating of the 9 peanut cultivars
Cultivar	Main stem height (cm)	Leaf SPAD reading	Leaf spot disease score	Lodging	Peg strength (N)	Pod and seed character			Kernel biochemical composition (%)
Cultivar	Main stem height (cm)	Leaf SPAD reading	Leaf spot disease score	Lodging	Peg strength (N)	100-pod weight (g)	100-seed mass(g)	Shelling percentage (%)	Oleic acid	Linoleic acid	Palmitic acid	Oil	Protein	TSS
Yuhanghua 7	67	32.05C	3	3	6.46C	136.95	51.72	67.48	52.38D	29.22B	10.83BC	45.63C	26.28BC	8.48A
Huayu 9624	55	33.70BC	2	0	8.37BC	212.22	102.00	76.98	82.24AB	3.11E	6.66F	50.64A	26.70 BC	7.49B
Huayu 9623	57	35.30BC	2	2	10.87AB	226.67	84.98	73.91	83.53A	2.30E	6.40F	51.19A	25.71C	7.50B
Anhua 6	55	36.65B	3	3	14.28A	187.09	65.83	69.22	50.47DE	30.52B	11.19B	48.14B	24.68C	8.42AB
Huayu 958	83	43.75A	2	3	8.66BC	249.31	90.99	69.62	79.34B	5.93D	6.74EF	51.60A	28.23B	6.28C
Huayu 9510	78	42.65A	3	3	7.91BC	201.23	67.49	62.94	48.51E	33.85A	11.79A	48.54B	26.68BC	8.27AB
Zhengnonghua 23	40	32.00C	2	2	12.92A	182.27	79.89	72.82	50.27DE	30.02B	10.72C	45.78C	30.59A	8.48A
Huayu 917	50	28.05D	2	2	8.12BC	244.78	91.68	64.47	80.45AB	5.83D	7.18E	50.39A	26.65BC	7.50B
Huayu 51	50	33.25BC	2	2	6.21C	184.64	68.26	71.15	70.41C	14.10C	8.60D	47.44B	26.31BC	8.28AB
Within each column, the figures followed by the same uppercase letter were not significantly different at 0.01 probability level.

Correlation coefficients between the 14 traits and pod rot score were calculated and shown in Table 4. Of them, only two were significant (at 0.05 level). Kernel protein content was negatively correlated with pod rot score on a per measurement basis (Pearson correlation coefficient was 0.3882, and Spearman rank correlation coefficient was 0.4271) at 0.05 level (Table 4).

Table 4

Relationships between main agronomic characters and pod rot scores, and broad-sense heritability estimate
Parameter	Main stem height	Leaf SPAD reading	Leaf spot disease score	Lodging	Peg strength	Pod and seed character			Kernel biochemical composition
Parameter	Main stem height	Leaf SPAD reading	Leaf spot disease score	Lodging	Peg strength	100-pod weight	100-seed mass	Shelling percentage	Oleic acid	Linoleic acid	Palmitic acid	Oil	Protein	TSS
Average-based Pearson correlation coefficient	-	-0.2445	-	-	-0.2606	-	-	-	0.0210	-0.0090	0.0009	-0.2241	0.4316	0.0980
Average-based Spearman rank correlation coefficient	-	-0.3615	-	-	-0.3338	-	-	-	-0.2460	0.1581	0.1054	-0.1933	0.4480	0.0791
Per measurement-based Pearson correlation coefficient	-0.3525	-0.2417	-0.4472	0	-0.2212	0.1060	0.0250	-0.1996	0.0210	-0.0090	0.0009	-0.2187	0.3882*	0.0901
Per measurement-based Spearman rank correlation coefficient	-0.4916	-0.2995	-0.4330	-0.1876	-0.2178	-0.0176	0.1493	-0.1845	-0.1844	0.1708	0.1029	-0.2009	0.4271*	0.0796
Average-based broad-sense heritability (%)	-	98.62	-	-	85.04	-	-	-	99.69	99.76	99.75	97.78	89.51	91.77
Per measurement-based broad-sense heritability (%)	-	95.98	-	-	65.45	-	-	-	99.09	99.28	99.26	93.63	73.98	78.80
Correlation coefficients marked with an asterisk were significant at 0.05 level.

Heritability estimates of leaf SPAD reading, peg strength, and kernel biochemical composition

Broad-sense heritability estimates of the 8 traits were in the range of 65.45%-99.28% (per measurement basis) and 85.04%-99.76% (average basis) (Table 4).

In the report by Godoy et al. (1985), six peanut genotypes, TxAG-3 (most resistant), Toalson and PI 341885 (moderately resistant), Starr (slightly resistant to R. solani) and Florunner and Golden I (susceptible), were compared for their leaf anatomical traits, and there was a decreasing trend in certain indicators (palisade cell number, cell width and index) from high disease resistance to disease susceptibility. As the disease reactions of the peanut entries were not quantified, no correlation analysis could be made. Godoy et al. (1985) highlighted the importance of lignin-stained regions in disease resistance mechanism, but limited themselves to descriptive comparisons, again without quantification. This made it impossible to compare the tightness of the relationship between individual traits and pod rot scores. They introduced an “index” parameter of the product of palisade cell number and cell width, which seemingly had a better discrimination power. It could be seen from our study that the absolute value of the average-based correlation coefficient between index and pod rot score was indeed higher than that between palisade cell number or cell width and pod rot score.

In the present study, all the four anatomical features, viz., leaf palisade cell number, cell width, index and shell lignin staining area, were negatively correlated with peanut pod rot score at 0.01 levels, supporting the findings of Godoy et al. (1985). However, robust associations between shell lignin content or kernel protein content and pod rot score were not established. Resistance may be related to both lignin distribution and content. Other traits, inclusive of shell hemicellulose and cellulose content and kernel oleic, linoleic and palmitic acid, oil and TSS content, main stem heigh, leaf SPAD reading, leaf spot disease score, lodging, peg strength and 100-pod weight, 100-seed mass and shelling outturn, were not correlated with pod rot disease reaction. This means that genetic improvement in these traits would have no significant impact on pod rot resistance. In other words, breeding for pod rot resistance in peanut may have no negative effects on these traits.

Heritability was considered high if it was greater than 40%, medium if it was between 20% and 40%, and low if it was less than 20%. Broad-sense heritability estimates for the four anatomical features in this study were high. High heritability indicated that heredity played a major role and there was a high potential for genetic improvement of the target trait(s). Given the stable and strong correlation between these anatomical features and pod rot scores, the pre-existing resistance may be identified even in the absence of disease. Association analysis of peanut pod rot resistance using several natural populations phenotyped under multiple environments at our laboratory is underway. Special attention will be paid to the relationship between resistance and these indicators from a genetic perspective. Hopefully, the output of this study will help facilitate the exploration of pod rot resistance mechanisms in peanut and breeding for disease resistance.

Declaration of competing interest

The authors declare that they have no competing interests.

Data availability

Data will be available upon request.

Acknowledgments

Sincere thanks are due to the ﬁnancial support from Mining Stress Tolerant Early Maturing Peanut Genetic Resources and Breeding Processing Type Peanut Varieties in Xinjiang (2022A02008-3), Taishan Industry Leading Talents Special Fund (LJNY201808), Guangdong Program for Science & Technology Plan (2020B020219003), China Agricultural Research System (CARS-13), and Agricultural Science & Technology Innovation Project of Shandong Academy of Agricultural Sciences (CXGC2022A03).

Chi YC, Xu ML, Yang JG et al (2016) First report of Rhizoctonia solani causing peanut pod rot in China. Plant Dis 100:1008–1008. https://doi.org/10.1094/PDIS-07-15-0840-PDN
Godoy R, Smith OD, Taber RA, Pettit RE (1985) Anatomical traits associated with pod rot resistance in peanut. Peanut Sci 12:77–82. https://doi.org/10.3146/pnut.12.2.0008
He M, Liu Y, Cui S et al (2018) Evaluation of peanut germplasm resources resistance to pod rot. J Plant Genet Resour 19:780–789
Lu L, Hua F, Shen X et al (2021) Identification of peanut cultivars resistant to pod rot disease in Anyang region.Agric Sci Technol Bull156–158
Lu L, Hua F, Wang Y (2022) Identification and occurrence dynamics of peanut pod rot pathogens in Neihuang, Anyang.Seed Ind Guide38–42
Porter DM, Garren KH, van Schaik PH (1975) Pod breakdown resistance in peanuts. Peanut Sci 2:15–18. https://doi.org/10.3146/i0095-3679-2-1-4
Porter DM, Rodriguez-Kabana R, Smith DH, Subrahmanyam P (1997) Compendium of Peanut Disease, Second edition. APS Press, St. Paul, Minnesota, USA
Wan SB (2003) Peanut Cultivation Science in China. Shanghai Sci & Tech Press, Shanghai, China
Wang CT, Zhang JC (2013) Peanut Genetic Improvement. Shanghai Sci & Tech Press, Shanghai, China
Wheeler T, Russell S, Anderson M et al (2016) Management of peanut pod rot II: Comparison of calendar and threshold-based fungicide timings. Crop Prot 87:13–18. https://doi.org/10.1016/j.cropro.2016.04.011
Williams EJ, Drexler JS (1981) A non-destructive method for determining peanut pod maturity. Peanut Sci 8:134–141. https://doi.org/10.3146/i0095-3679-8-2-15
Yang K-H, Tsaus W-L, Shieh G-J et al (2002) Screening the peanut (Arachis hypogaea L.) germplasm for resistance to pod rot disease. J Agricultural Res China 51:12–19
Yu J, Li Y, Xu M et al (2020a) Evaluation of resistance of different peanut varieties to peanut pod rot. Chin J Oil Crop Sci 42:681–686
Yu J, Wu J, Xu M et al (2020b) Fungicides screening for management of peanut pod rot caused by Pythium myriotylum. Chin J Oil CroP Sci 42:121–126
Yu J, Xu M, Liang C et al (2019) First report of Pythium myriotylum associated with peanut pod rot in China. Plant Dis 103:1794–1794. https://doi.org/10.1094/PDIS-02-19-0321-PDN
Yu SL (2008) Peanut Cultivars in China and their Genealogy. Shanghai Sci & Tech Press, Shanghai, China

Download PDF

Version 1

posted

You are reading this latest preprint version

Phenotyping peanut cultivars with contrasting responses to pod rot pathogens

Status:

Version 1

Abstract

Figures

Introduction

Material And Methods

Statistical analysis

Results And Analysis

Conclusions And Discussion

Declarations

References

Status:

Version 1