Maintaining optimal crop nutritional levels is crucial for maximizing yield and enhancing stress resistance. In addition to the 17 essential nutrients, there are many plant-beneficial elements: silicon, aluminum, selenium, titanium, iodine, vanadium, cobalt, sodium, and rare earth elements. They are not essential for all plants, but some are crucial for specific plant species. However, the mechanisms of action of many beneficial elements are still unclear, and products containing beneficial elements have not been widely accepted and used by the public. This review systematically summarizes the current knowledge of plant-beneficial elements. Most importantly, we offer suggestions for future research on beneficial elements, which include integrating cross-disciplinary and innovative technologies, expanding the scope of application and elemental spies, broadening the spatial and temporal scales of research, incorporating beneficial elements into the soil health evaluation system, and shifting from single to multi-element applications. In the future, research on beneficial elements should be closely centered around “mechanism+application” to meet the ever-increasing demands driven by population growth, improve human health, tackle environmental challenges, and promote rural economic development.

The development of wheat cultivars with improved nitrogen (N), phosphorus (P), and potassium (K) use efficiency is essential for sustainable agriculture. Genetic dissection and identification of causative genes underlying nutrient use efficiency represent a key strategy toward this goal. We conducted an extensive genome-wide association study (GWAS) using a panel of 431 wheat cultivars, identifying 1,659 significant single-nucleotide polymorphisms (SNPs) (LOD>5) through genotyping-by-sequencing. This analysis revealed 534 quantitative trait loci (QTLs) associated with 12 nutrient use efficiency traits across five distinct environments, among which 14 QTLs were consistently detected in at least three environments. Notably, meta-QTL analysis, showed that QTL80 (72.12–74.24 Mb, chr2A), QTL387 (32.88–33.56 Mb, chr6A), and QTL500 (535.53–540.80 Mb, chr7B) exhibit clear co-localization with MQTL-2A-2, MQTL-6A-1, and MQTL-7B-2, respectively. This overlap highlights their robustness across diverse environmental conditions. Within these regions, critical candidate genes - including members of the bZIP transcription factor family and a potassium transporter gene - were identified in relation to nutrient use efficiency. Furthermore, a novel locus, QTL234, was discovered, harboring key candidate genes such as dof zinc finger protein, Ankyrin repeat family protein, and cytochrome P450. To validate the SNP within QTL234 associated with nitrogen harvest index (NHI), we developed a dCAPS marker for AX-109095537. These findings demonstrate the effectiveness of high-resolution SNP-based GWAS in rapidly pinpointing promising candidate genes. They also establish a foundation for large-scale QTL fine mapping, candidate gene validation, and the development of functional markers essential for enhancing nutrient use efficiency in wheat breeding programs.

Structural variation is an important source of genetic variation in wheat and have been important in the evolution of the wheat’s genome. Few studies have examined the relationship between structural variations and agronomy and drought tolerance. The present study identified structural chromosome variations (SCVs) in a doubled haploid (DH) population and backcross introgression lines (BC₅F₃) derived from Jinmai 47 and Jinmai 84 using fluorescence insituhybridization (FISH). There are one simple translocation, 10 present/absent variations (PAVs), and one copy number variation (CNV) between Jinmai 47 and Jinmai 84, which distributed in 10 chromosomes. Eight SCVs were associated with 15 agronomic traits. A PAV recombination occurred on chromosome 2A, which was associated with grain number per spike (GNS). The 1BL/1RS translocation and PAV.2D were associated with significant reductions in plant height, deriving from the effects on LI2-LI4, LI2-LI4 and UI, respectively respectively. PAV.2D was also contributed to an increase of 3.13% for GNS, 1BL/1RS significantly increased spikelet number, grain length (GL), and grain thickness (GT). The effect of PAV.4A.1 on GL, PAV.6A on spike length (SL) and thousand-grain weight (TGW), PAV.6B on SL, GT and TGW were identified and verified. PAVs on chromosomes 2A, 6A, 1D, 2D, and a CNV on chromosome 4B were associated with the drought tolerance coefficients. Additive and interaction effects among SCVs were observed. Many previously cloned key genes and yield-related QTL were found in polymorphic regions of PAV.2B, PAV.2D, and CNV.4B. Altogether, this study confirmed the genetic effect of SCVs on agronomy and drought tolerance, and identification of these SCVs will facilitate genetic improvement of wheat through marker-assisted selection.

Leaf morphology constitutes a key component of the ideotype, and optimal leaf rolling contributes to compact plant architecture. Rapeseed (Brassica napus) is an important oilseed crop; however, the genetic mechanisms underlying leaf shape development remain poorly understood, and corresponding germplasm resources for genetic improvement are limited. In this study, we identified a dominant mutant, INSIDE-ROLLING LEAF1(IRL1), which exhibits inward leaf rolling due to defective mesophyll cell development. The mutant also displays drooping siliques and a semi-dwarf phenotype, accompanied by a reduction of one to two effective branches. Through map-based cloning and functional complementation assays, we confirmed BnaC02G0201100ZSasthe causal gene IRL1. This gene encodes LATERAL ORGAN BOUNDARIES DOMAIN6 (BnaC02.LBD6). The phenotypic alterations in the IRL1mutant result from elevated expression of BnaC02.LBD6, driven by a single nucleotide substitution within a DNA binding site in its promoterregion. Overexpression of BnaC02.LBD6recapitulated the IRL1mutantphenotype, confirming its functional role. Haplotype analysis revealed a rare allelic variant in the BnaC02.LBD6promoter associated with the unique leaf morphology of IRL1. Transcriptomic profiling indicated significant differential expression of genes involved in adaxial–abaxial leaf polarity establishment, secondary metabolic pathways, and hormone signaling networks. Our findings provide novel insights into the genetic regulation of leaf morphogenesis in rapeseed andoffer valuable genetic resources for optimizing plant architecture in breeding programs.

High yield remains the primary objective of peanut breeding. Key yield components, 100-pod weight (HPW), 100-seed weight (HSW), and shelling percentage (SP), are critical determinants of overall productivity. This study aimed to construct a high-density linkage map using resequencing data from recombinant inbred lines (RILs) derived from a cross between ‘Silihong’ (Arachishypogaeavar. fastigiate) and ‘Jinonghei 3’ (A.hypogaeavar. hypogaea). The resulting map comprised 4,499 bins distributed across 20 chromosomes, spanning a total length of 1,712.32 cM with an average inter-marker distance of 0.38 cM. A total of 46 quantitative trait loci (QTLs) were identified across three environments. Major QTLs, including qHPW5.2, qHPW18.1, qSP7.1, qSP8.1, qSP8.2, qSP18.1, and qSP18.2, explained phenotypic variation (PVE) of 12.04, 11.41, 16.53, 24.17, 10.49, 10.82, and 29.89%, respectively. Fourteen QTLs detected across multiple environments were considered stable. Notably, one QTLregion (qHPW7, qHSW7.1, and qSP7) was associated with all three traits, accounting for PVE values of 8.91, 9.04, and 16.53% for HPW, HSW, and SP, respectively. To validate the accuracy of QTL mapping, a genome-wide association study(GWAS) was conducted using the US mini-core collection. Across two environments, 115 single-nucleotide polymorphisms (SNPs) were significantly associated with HPW, HSW, and SP in the association panel. Six SNPs were linked to two traits, explaining an average phenotypic variation of 13.84%. Integration of both mapping populationsrevealed that AX-176802178, detected on chromosome 7 in the association panel and associated with SP, was located within the confidence interval of QTL qSP7defined by the recombined inbred lines (RIL) population. Furthermore, three KASP markers were developed and validated in peanut landraces and cultivated varieties. These findings provide valuable insights into the genetic architecture underlying HPW, HSW, and SP, and offer useful molecular tools for marker-assisted selection in peanut breeding programs.

Lodging is a primary factor limiting rice grain yield. Achieving synergistic improvements in grain yield and nitrogen use efficiency (NUE) without increasing lodging risk has been a global research priority. In this study, two rice cultivars-Yongyou 2640 (indica–japonicahybrid rice) and Jinxiangyu 1 (inbred japonicarice)-were evaluated in field experiments conducted over two growing seasons. Six nitrogen management strategies were implemented: no nitrogen (T1), conventional urea (T2), controlled-release nitrogen (CRN) (T3), reduction of CRN (T4), CRN combined with single basal application of conventional urea (T5), and CRN combined with split applications of conventional urea (T6). Compared with T2, the integrated nitrogen strategies (T5 and T6) increased NUE by 4.89–5.69% and grain yield by 3.41–4.65%. These treatments also enhanced structural integrity of the second basal internode, evidenced by increased carbohydrate content, internode breaking strength, epidermal silicon layer thickness, number of large and small vascular bundles, and thickness of both parenchymatous and mechanical tissues. Concurrently, internode length, bending moment, and lodging index were reduced. Collectively, these findings indicate that integrating CRN with conventional urea improves morphological, mechanical, physicochemical, and anatomical properties of the second basal internode, thereby enhancing stem strength and enabling high yield and NUE without compromising lodging resistance.

The rice ratooning system has attracted increasing attention in southern China due to its low carbon emissions and high yield potential. However, the net carbon budget and underlying mechanisms remain unclear. Three rice cropping systems were established in this trial experiment conducted from 2021 to 2022 in Fuzhou (25°05´N, 119°13´E), Southeast China: ratooning rice (RR: MC+RSR) patternfor rice ratooning, single-cropping rice (LR₁), and double-cropping rice (DC: ER+LR₂). The closed static dark box gas collection, dry matter determination, life cycle assessment (LCA) etc. approaches were utilized to investigate the mechanism of “high carbon fixation–low emissions” mechanism in RR. A comprehensive assessment was conducted across multiple dimensions, including crop yield, greenhouse gas (GHG) emissions, carbon and nitrogen footprints, resource use efficiency, carbon sequestration capacity, and carbon budget balance. Results showed that the average daily yield of ratoon season rice (RSR) across RR treatments from 2021 to 2022 was 28.21–47.40% higher than that of the main crop (MC) and LR₁, and the average daily yield of RR was 13.50–27.76% higher than DC. This yield advantage was attributed to a 32.32–39.26% increase in the allocation of ¹³C-labeled photosynthetic products (includingnon-structural carbohydrates, NSCs) to panicle organs, and a 21.77–43.51% reduction in allocation to underground roots and soil. Furthermore, the average daily global warming potential (GWP) was 16.44kg CO₂-eq ha^–1for RR, 24.99kg CO₂-eq ha^–1for LR₁, and 21.32 kg CO₂-eq ha^–1for DC. Specifically, the average daily GWP of ratoon rice was 34.21% lower than that of LR₁and 22.90% lower than double-cropping rice. Similarly, the average daily greenhouse gas intensity (GHGI) of ratoon rice was 62.28% lower than LR₁and 28.96% lower than double-cropping rice. In terms of carbon and nitrogen footprints, the ratoon rice system exhibited average daily values of 34.54kg CO₂-eq ha^–1and 0.47kg N ha^–1, respectively. In comparison, LR₁had values of 45.63kg CO₂-eq ha^–1and 0.49kg N ha^–1, while double-cropping rice showed 43.38kg CO₂-eq ha^–1and 0.53kg N ha^–1. These values represent reductions of 24.30% in carbon footprint and 4.28% in nitrogen footprint relative to LR₁, and 20.38 and 11.45% relative to double-cropping rice, respectively. Moreover, the averageannual carbon budget surplus across systems was 22,380.01kg CO₂-eq ha^–1for ratoon rice (MC+RSR), 11,228.54kg CO₂-eq ha^–1for LR₁, and 23,772.15kg CO₂-eq ha^–1for DC. Consequently, the resource utilization efficiency of the RR was 24.42 and 47.50% higher than that of single-cropping and double-cropping systems, respectively. Average daily economic returns also increased by 32.71 and 80.75%, respectively. These findings provide a robust theoretical foundation and practical guidance for advancing agricultural carbon neutrality technologies and ensuring food security.

In maize production, the development of density-tolerant and lodging-resistant varieties has made dense planting an effective strategy for achieving high and stable yields, with superior hybrids serving as a prerequisite for successful high-density cultivation. However, the photosynthetic mechanisms underlying improved density tolerance in maize hybrids released across different eras in China remain unclear. This study investigates 40years of breeding progress toward enhanced photosynthetic traits under varying planting densities and elucidates the physiological and ecological bases of improved density tolerance in maize hybrids. A three-year field experiment was conducted from 2019 to 2021 to compare eight major Chinese hybrids from four decadal cohorts under three planting densities: 45,000 (D1), 67,500 (D2), and 90,000 (D3) plants ha⁻¹. At high density (D3), modern hybrids exhibited a more optimal canopy architecture and superior leaf photosynthetic performance compared to older hybrids, despite a slight reduction in specific leaf nitrogen. Notably, modern hybrids (2000s) were able to maintain higher net photosynthetic rates and photosynthetic nitrogen use efficiency (PNUE) at D3, resulting in the highest grain yield (GY), which was 118.47% greater than that of older hybrids (1970s). Leaf area duration after anthesis, total chlorophyll content, key photosynthetic enzyme activities, and maximumquantum efficiency of PSII photochemistry were all positively correlated with GY. Among these, PNUE showed the strongest correlation with grain yield and thus represents a key indicator for optimizing maize hybrids. Based on these findings, breeders should continue selecting hybrids under high-densityand suboptimal conditions, focusing on optimizing population architecture and enhancing photosynthetic capacity while fine-tuning leaf nitrogen status to develop high-yielding, density-tolerant hybrids capable of sustaining long-term increases in maize grain yield.