Abstract False‐green kyllinga (FGK; Kyllinga gracillima Miq.) is a warm‐season perennial weed in the Cyperaceae family. Our objective was to determine the potential for FGK to establish from seed in turfgrass. Replicated field experiments were conducted in Kentucky bluegrass (Poa pratensis L.) mowed at 6 cm. FGK was seeded at 5 or 500 kg ha−1, and smooth crabgrass [Digitaria ischaemum (Schreb.) Schreb. Ex Muhl.] was seeded at 500 kg ha−1. Turf was managed under either low or high input programs to generate swards of different density. Low‐input turfgrass received 25 kg N ha−1 annually, while high‐input turfgrass received 200 kg N ha−1 annually along with preventative fungicide applications. FGK establishment from seed was reduced more by turfgrass inputs than smooth crabgrass. Smooth crabgrass cover in September of both experiments was >93% and not affected by turfgrass inputs. When FGK was seeded at 500 kg ha−1, cover in September was higher in low input (57% in Run 1, 59% in Run 2) than in high input turf (36% in Run 1, 18% in Run 2). When FGK was seeded at the lower rate of 5 kg ha−1, cover in Run 1 was higher in the low input (14%) than high input turf (2%), but FGK cover was similar between input levels in Run 2, with 4 and 1% cover in the low and high input plots, respectively. FGK successfully overwintered in this study, with cover increasing during the second summer of growth. Although FGK is less competitive as a seedling than smooth crabgrass, its perennial life cycle allows it to increase weed cover over time.

Abstract Kentucky bluegrass (KB) (Poa pratensis L.) is an excellent cool‐season turfgrass sod option because of its rhizomatous growth habit. There are known growth and other characteristics differences among cultivars, but little is known about the differences in germination and establishment speed, as well as differences in rhizome and sod production for turfgrass practitioners. Therefore, the objectives were to investigate the influence of 19 KB cultivars on germination and establishment speed and sod production characteristics through replicated field and controlled‐environment experiments at Kansas State University. Faster‐germinating KB cultivars reached 50% germination and 50% establishment within <8 and <23 days, respectively, compared to slower cultivars reaching 50% germination and 50% establishment in ≥9 and ≥24 days, respectively. However, fast germination speed did not always predict fast field establishment speed. Greenhouse experiments revealed differences in the number of rhizomes and total rhizome length among cultivars. Field experiments measured sod strength (maximum tensile load to tear sod [Newtons] and required work to tear sod [N‐m]) at three harvests of 9, 10, and 13 months after planting. There were sod strength differences among KB cultivars, which ranged from ∼22 to 38 N‐m of required work to tear sod and 389 to 568 N of maximum tensile load to tear sod. While KB classification systems assist in describing other KB traits (i.e., color, density, growth, and stress tolerances), they were not consistent in predicting differences in germination or establishment speed, as well as rhizome characteristics in the greenhouse or sod production differences for sod producers.

Abstract Using soil cover residues from previous crops through integrated systems has proven effective in driving changes in soil properties with nutrient cycling, promoting higher grain production. However, there is still a need to investigate the changes that different cultivation arrangements of these management systems can influence on soybean productivity. The aim was to compare conventional soybean cultivation methods with integrated systems in a tropical region over 2 years and how these systems affect desiccation efficiency, biomass decomposition, carbon/nitrogen ratio, nutrient cycling, as well as soybean productivity. An experimental area, under a block design with three replications, with conventional soybean cultivation system with soybean cultivated over crop residues produced by a previous integration of maize, three cultivars of Panicum maximum (Tamani, Quenia, and Zuri guinea grasses), and pigeon pea, arranged in monoculture and triple intercropping, it was implemented in Latossolo Vermelho Acriférrico typical, Goiás, Brazil. The results indicated that Tamani and Quenia guinea grasses, along with pigeon pea, exhibited higher desiccation efficiency in both monoculture and intercropping. The previous integration of maize with Panicum cultivars and pigeon pea increased soil coverage and maximized nutrient cycling, resulting in increasing productivity gains by approximately 39.8% compared to soybean cultivation without biomass covering the soil. These results highlight the importance of considering nutrient cycling and decomposition rates in fertilization strategies to increase the sustainability of systems. Therefore, integrated systems, which combine grasses and legumes, represent a promising and efficient strategy for agricultural production systems.

Abstract Kernza intermediate wheatgrass (IWG) [Thinopyrum intermedium (Host) Barkworth & D.R. Dewey] is a promising perennial grain and forage crop, but experiences grain yield decline, potentially due to limited nitrogen (N) and stand overcrowding. We evaluated the effects of N fertilization and stand thinning on grain and forage yield, weed biomass, thousand‐kernel weight (TKW), and harvest index (HI). We used a full factorial design with N rates of 0, 75, and 150 kg N ha−1 and thinning intensities of 0%, 25%, 38%, or 50% stand density reduction via banded herbicide at two locations in Wisconsin over 2 years. Fertilization and thinning did not interact. Grain yields increased with N fertilization except at Madison in Year 2. At Lancaster, grain yield increased from 293 with no N to 497 and 701 kg ha−1 with 75 and 150 kg N ha−1, respectively, across years. At Madison, grain yield increased only in Year 1. Forage mass also increased with N at both sites except Madison in Year 2. At Lancaster, forage mass ranged from 4016 to 6500 kg ha−1 across years and N rates. TKW and HI increased with N at both sites, except at Madison in Year 2. Weed biomass was unaffected by treatments. Thinning had no effect on grain yield at Lancaster in Year 1, but in Year 2, grain yield increased from 368 to 505 kg ha−1 with 50% thinning. These results suggest that applying 75 kg N ha−1 is important for maintaining IWG productivity and that thinning can help sustain grain yield in older stands.

Abstract The drive to increase seed yield in soybean [Glycine max (L.) Merr.] has traditionally overshadowed the exploration of biomass partitioning and the compositional characteristics of plant residue traits such as leaves, petioles, stems, and pods. The exploration of biomass partitioning and the compositional characteristics of plant residue traits in soybean provide insights into plant nutrient allocation strategies that can be utilized to increase crop productivity and improve management practices for maximizing yields and sustainability. Recognizing this gap, our study aimed to investigate the variability in these traits across 32 genetically diverse soybean genotypes cultivated over 2 years in central Iowa. Through detailed collection and analysis of vegetative parts at critical growth stages (R1, R4, and R8), we assessed both biomass traits and their chemical compositional characteristics, focusing on soybean residue traits to enhance soil health and their importance in soybean cropping systems. We present broad sense heritability estimates for accumulated (R8) organ biomass (0.61–0.87) and residue carbon nitrogen composition (0.74) in soybeans. The large variation and high heritability suggest breeding strategies to optimize variety development via biomass and residue traits. Utilizing the Agriculture Production Systems sIMulator, we conducted a sensitivity analysis to evaluate the impact of soybean residue quality on soil nutrient cycling and its effects on the subsequent maize [Zea mays L.] crop. The study underscores the importance of soybean residue management, emphasizing the need for integrated approaches in breeding and agricultural practices that utilize the genetic diversity of these traits.

Abstract Preharvest sprouting (PHS), the initiation of mature grain germination on the mother plant when wheat ( Triticum aestivum L.) gets wet before harvest, is a major cause of elevated post‐harvest alpha‐amylase in wheat grain. Alpha‐amylase digests starch to support seedling growth during germination. However, excessive starch digestion by alpha‐amylase reduces its pasting capacity in flour/water mixtures leading to collapsed cakes, sticky noodles, and bread with sticky crumb. Elevated alpha‐amylase can also result from cool temperatures during grain filling, either due to a developmental problem called late maturity alpha‐amylase (LMA) or premature germination under moist conditions termed vivipary. PHS tolerance was mapped to 53 quantitative trait loci (QTL), including 16 of high significance (logarithm of the odds > 7.5), in a spring wheat panel previously used for association mapping of LMA. When vivipary assays were performed on a panel subset, vivipary, LMA, and PHS were significantly correlated with each other. This is interesting given that the PHS and vivipary phenotypes assayed were visible germination, whereas the LMA phenotype assayed was alpha‐amylase activity. While there are LMA susceptible lines that are PHS tolerant and vice versa, this suggests that overlapping genetic mechanisms may govern tolerance in this population. Indeed, Five PHS QTL had a significant effect of LMA phenotype in the same population Qs2‐1A , Qs20‐3B , Qs31‐5A , Qs39‐5D , and Qs42‐6A . Breeding programs may be able to use such QTL to select for both PHS and LMA tolerance. The more significant and reproducible PHS QTL identified are good candidates for marker development and cloning efforts.

Abstract Prediction‐based breeding reshapes plant genetic improvement by prioritizing the predictive ability of models over causal interpretation. This review examines recent advances in the use of tools such as genomic selection, high‐throughput phenotyping, multi‐omics integration, and enviromics to enhance genetic gain and improve the efficiency of breeding programs. Predictive models, while powerful, rely on validation within the genetic and environmental domains represented in the training set, with evident risks when extrapolated to unrelated scenarios. Traditional approaches such as marker‐assisted selection and genome‐wide association study remain limited for quantitative traits, reinforcing the need for prediction‐oriented models. Moreover, the expansion of omics data sources, although capturing greater biological complexity, must be accompanied by rigorous validation practices to avoid fragile interpretations. Stochastic simulations are a strategic tool for testing selection schemes, optimizing training populations, anticipating overfitting risks, reducing costs, and guiding decisions based on prospective scenarios. This review also highlights the importance of ensuring independence between calibration and prediction, focusing on practical accuracy evaluation, and prioritizing operational utility over mechanistic explanation. In summary, prediction‐based breeding is a core strategy for modernizing breeding programs, connecting computational tools, high‐dimensional data, and pragmatic decision‐making to deliver consistent results.

Abstract The aim of this research was to assess the natural resistance of traditional maize (Zea mays L.) varieties cultivated in Espírito Santo, Brazil, to Spodoptera frugiperda. Additionally, the study aimed to investigate the leaf structures, chemicals, biochemicals, and cellular factors associated with this resistance, with the ultimate goal of identifying promising varieties for genetic breeding. The evaluation included a total of 77 traditional maize varieties, along with four commercial varieties cultivated throughout Brazil. The experiment followed a randomized complete block design with three replications, and the plots consisted of three rows, each 3 m in length and spaced 1.0 m apart, with the central row representing the useful area of the plot. Traditional varieties exhibiting low herbivory by S. frugiperda underwent antixenosis tests for feeding and oviposition. Leaf samples were subjected to histology and microscopy tests. Out of the field tests, eight maize varieties displayed no evidence of S. frugiperda attacks, suggesting either natural resistance or antixenosis by the pest. Antixenosis analysis identified variety Cativerde 02 with minimal herbivory by S. frugiperda, comparable to the negative control, the transgenic hybrid Feroz Viptera 3 (Syngenta), known for its resistance to the pest. Histological and microscopy analyses revealed distinct chemical elements in the traditional Cativerde 02 compared to the controls, and the presence of silica crystals in this variety suggested a potential protective mechanism against herbivory.

Abstract Nixtamalization moisture content, a measure of the quantity of water absorbed during the nixtamalization of a grain, has a large impact on the end‐quality of masa‐based products. An application to predict nixtamalization moisture content from raw inbred and hybrid maize (Zea mays L.) grain was recently developed, but its utility in a breeding context has not been assessed. Here, important breeding considerations such as partitioning of variation, genetic architecture, and relationship with yield were assessed in diverse maize hybrids (n = 560), modern commercial hybrids (n = 10), and historically high‐acreage hybrids (n = 15) grown in up to three environments across 2 years. This study demonstrated that nixtamalization moisture content is heavily influenced by growing conditions, but sufficient genetic variance is present to allow breeders to make gains from selection. There was not a substantial correlation between nixtamalization moisture content and yield, suggesting breeders can select for both traits without negatively impacting either trait. Both additive and dominant genetic action was observed, and genomic prediction was able to predict nixtamalization moisture content in hybrids with an average Spearman's rank correlation coefficient between 0.253 and 0.451 and a root mean square error between 0.00579 and 0.00691. The findings suggest that nixtamalization moisture content can be selected for early in breeding generations, allowing breeders to develop improved food‐grade maize germplasm without negatively impacting yield.