Crop Science最新文献

Clonal evaluation trials of cassava (Manihot esculenta Crantz), where the main selection of this crop takes place, are usually carried out in multiple environments. This study investigated the influence of genotype–environment (GE) interaction on selection and how to explore genetic information across environments in a mixed model approach by modeling different genetic covariance structures. Approximately 240 cassava clones were assessed in an augmented block design during the 2020/2021 growing season in Brazil. The unstructured model was the best suited and used to investigate several strategies of selection. The predicted genetic gains based on individual analyses varied greatly among environments (5.52%–12.62% for root yield; 1.00%–6.09% for dry matter content; and 4.01%–9.42% for dry matter yield), although the clones mean was similar. Moreover, most of the selected clones in each environment outperformed the best check (>80%), except for root yield and dry matter yield in one environment. By multi-environment analysis, greater local gains were detected in each environment (means of 16.87% for root yield, 5.56% for dry matter content, and 17.27% for dry matter yield) and for mean heritability (0.52 for root yield, 0.76 for dry matter content, and 0.55 for dry matter yield). The coincidence of clones selected by individual and multi-environment analyses was 64% for root yield, 73% for dry matter content, and 66% for dry matter yield. The best scenario for selection is when all environments are considered simultaneously, for which regional genetic gains of 16.71% were predicted for root yield, 5.40% for dry matter content, and 17.06% for dry matter yield.

Daniel W. Sweeney, Travis E. Rooney, Jason G. Walling, Mark E. Sorrells

This erratum corrects the following:

Table S3 contains two errors. Table S3 states that for marker AlaAT_L214F, the Allele-2 forward primer (ending in C) is the dormant allele, but it should state that it is the non-dormant allele. Morex is non-dormant and has a C at position 642 on the sequence. Incorrect non-dormant and dormant alleles were reported for MKK3_E165Q. The non-dormant allele was published as A and the dormant allele as T. The correct non-dormant allele for MKK3_E165Q is G and the dormant allele is C, matching the forward primers provided for this marker. An updated Table S3 is provided.

Correspondence

Mark E. Sorrells, Plant Breeding and Genetics Section, School of Integrative Plant Sciences, Cornell University, Ithaca, NY 14853, USA. Email: [email protected]

With the increasing demands for crop yield and production mechanization, improvement of plant architecture is getting more imperative in cotton. In the present study, we investigated the plant height (PH) and the node of first fruiting branch (NFFB) of 719 upland cotton accessions in six different environments. We used the 10,511 high-quality single nucleotide polymorphisms (SNPs) to perform single-locus and multi-locus genome-wide association study (GWAS). As many as 278 associated SNPs were identified, 142 by the mixed linear model (MLM) in the single-locus model and 192 by six multi-locus models. A total of 42 SNPs were identified in at least four environment-traits or methods, of which 28 SNPs were significantly associated with PH, 22 were significantly associated with NFFB, and eight were co-associated with the two traits. Notably, most of loci were novel besides i33922Gh located in the reported QTL for PH. Furthermore, we identified nine promising candidate genes, among which the three genes Gh_D03G0738, Gh_D10G2028, and Gh_D05G3600 contained non-synonymous SNP mutation. The accessions with alleles of the mutations resulted in significant phenotypic differences. The expression of these genes showed significant differences between short-PH and high-PH varieties. Moreover, overexpression of Gh_D03G0738 led to reduction of PH in Arabidopsis. These results provided insights into genetic basis of plant architecture in cotton.

With the increasing severity of climate change, drought has become a global issue that seriously restricts the development and production of crops. Maize (Zea mays L.) is one of the major food crops in the world. Therefore, the demand for drought-tolerant maize varieties has been rapidly increasing in the market. Recent studies have found that late embryogenesis abundant (LEA) proteins are involved in plant responses to various osmotic stresses such as drought and salt stress. Thus, we hypothesized that LEA genes may provide similar stress tolerance abilities in maize. We isolated ZmMGL3 of the LEA gene family and developed transgenic maize plants overexpressing ZmMGL3 using Agrobacterium-mediated transformation. Then, we conducted physiological and biochemical evaluations of the transgenic maize plants exposed to drought stress. Under drought stress (10% polyethylene glycol 6000), the transgenic maize plants showed improved germination rate, seed vigor, radicle length, root length at the seedling stage, and wilting degree after drought and rewatering compared to the wild-type plants. The transgenic plants also accumulated more catalase, superoxide dismutase, peroxidase, hydrogen peroxide, and superoxide radicals compared to the wild-type plants. These results indicate that ZmMGL3 enhances drought resistance in maize plants by reducing the content of reactive oxygen species in the leaves and can be used as a candidate gene for the development of drought-tolerant maize varieties.

Agricultural markets remain major issue downgrading root and tuber crop farmers who form the mainstream of the agricultural producers in Malawi. Recent evidence however reveals that orange-fleshed sweet potato (OFSP) (Ipomea batatas) is currently being sold in produce markets along with the non-orange varieties, sometimes in differentiated form in Malawi. The main objective of this study was to examine factors affecting market participation of sweet potato farmers in southern region of Malawi. Using a double-hurdle model, this paper analyzed both the factors affecting farmer decision to participate and the extent/intensity of participation in market. The first tier of the double hurdle focused on decision to participate in the market using probit model and the second tier addressed factors affecting intensity of participation using truncated normal regression model. The paper used data collected from 360 farmers in southern districts of Malawi. Out of 360, 146 farmers had grown OFSP in the season preceding the survey. Double hurdle results indicate that farm size, output, age of a farmer (household head), and early maturing trait significantly determined decision to participate in the market. Further, results on intensity of participation indicate that access to market training, farm size, asset value, and output positively determined the intensity and negatively determined by distance to main market and gender of a farmer (household head). Based on the research findings, higher output levels and early maturing trait were found to increase smallholder farmer market participation. It is therefore recommended that strategies aimed at increasing household capacity to produce surplus produce through market tailored extension messages and productivity enhancement technologies could be highly effective in fostering smallholders' participation in commercial markets. Again, enhanced capacity building of research institutions to breed sweet potato varieties based on market demand is pivotal for increased market participation. Furthermore, research suggests that improving smallholder farmers' access to market price information, asset value, and farm size can help increase their intensity in the market. Therefore, it is critical for policymakers to holistically comprehend these socioeconomic factors in order to address the issue of smallholder farm households' decisions about market participation and the degree to which they participate.

Two species of potato cyst nematodes (PCNs), Globodera rostochiensis (Woll.) and Globodera pallida (Stone), threaten potato (Solanum tuberosum L.) production worldwide. PCNs are remarkably persistent in soil and can reduce potato yield significantly. The most sustainable approach to PCN control is deploying resistant cultivars. This review focuses on the knowledge needed to conduct a successful PCN resistance breeding program, including identifying resistance sources in wild species, introgressing them into cultivated potato, and sifting through clones to identify a marketable potato.

Crop yield is influenced by environmental, genotype, and management factors. This study focuses on the environmental and genotype factors, specifically the concept of mega-environments, where similar crop varieties thrive due to similar environmental conditions, and cultivar intensity, a cultivar's favorable reaction to improved growing conditions, in cultivar recommendation for winter wheat in Poland. The research aims to evaluate the potential of using cultivar intensity as a tool for cultivar recommendation and investigate the influence of dataset size on model performance. The study utilizes a dataset of winter wheat grain yield data collected over six seasons from 19 experimental stations in Poland. Various models are compared using prediction measures, such as correlation coefficient, root mean square error, and mean absolute percentage error. The results show that models combining mixed analysis of variance and linear regression perform best in terms of yield prediction, followed by models using only regression. Models based on cultivar mean in the region exhibit lower prediction ability. The impact of dataset size on prediction accuracy is found to vary depending on the model and prediction measure used. The findings highlight the importance of considering dataset size when assessing model performance and emphasize the need for reliable data in cultivar recommendation. The outcomes of this study contribute to the understanding of cultivar recommendation strategies and provide insights into the use of cultivar intensity and dataset size optimization for reliable and accurate recommendations.

Root system architecture (RSA) plays a central role in water and nutrient acquisition in plants. Plasticity and genetic variation in RSA can be used as an adaptive strategy to optimize plant performance under variable environments. We quantified phenotypic variation for seedling RSA among 44 diverse pea (Pisum sativum L.) genotypes, including breeding lines and germplasm accessions, grown under controlled conditions for 14 days using two-dimensional hydroponic root imaging. Root image analysis revealed significant genotypic variability among the lines for all root traits, namely root length (RL), root diameter (RD), root volume, root surface area, number of tips, network width (NW), network depth (ND), and network convex area. Significant positive correlations were observed among the evaluated root traits, ranging from 0.5 to 0.9. Pea lines were ranked based on estimated means for root traits, with lines E20, F1, and F8 showing high rankings, while E4 and F5 received low rankings for most traits. To associate root traits with nitrogen (N) fixation and field agronomic performance, we performed redundancy analysis (RDA). The quantified root traits accounted for significant variation in the agronomic traits (R² = ∼30%, p < 0.001). RDA showed a positive association between lodging susceptibility and root system NW and between plant height and root system ND. RD was positively associated with grain yield and N fixation. N fixation was positively associated with the number of lateral roots. The findings of this study indicate that variation for seedling root traits in pea could aid selection for N fixation and other important agronomic traits.

Sweet corn (Zea mays L.) cultivars must meet stringent quality standards to be accepted in the marketplace. Breeding for eating-quality traits, such as sweetness, typically involves taste ratings or quantification of carbohydrate content. Total soluble solids (TSS) content is used as a proxy for sweetness in many fruit crops. Using a diallel of near-isogenic corn lines for sugary1, shrunken2, waxy1, and wild-type (WT) endosperm types, a combining ability analysis for carbohydrate traits and TSS content determined the relationship of these traits over three harvest dates. Variation existed for total sugar, sucrose, glucose, fructose, total polysaccharides, and starch content within and across endosperm types and harvest dates, but strong correlations with TSS content were present only when assessed across all endosperm types. Strong similarities existed among WT, waxy1, and sugary1 near-isogenic lines for general combining ability for carbohydrate traits, while shrunken2 near-isogenic lines had different desirable combiners. Line C40 was a desirable general combiner for carbohydrate traits among WT, waxy1, and sugary1 endosperm types, while Ia5125, P39, and Ia453 were desirable general combiners for shrunken2 endosperm. This experiment also determined that TSS content is not a useful trait in sweet corn breeding for quality traits.