Ensuring the income stability of relocated households is essential for advancing rural revitalization and achieving common prosperity.  While existing research has explored the impact of digital technology on income, few studies have addressed how digital technology use affects income stability.  To fill this gap, based on survey data from relocated households in 16 counties across 8 provincial-level regions in China, this study examines the impact of digital technology use on the income stability of relocated households using Ordinary Least Squares (OLS) and Propensity Score Matching (PSM).  The results show that digital technology use improves both income and income stability, with stronger effects at higher levels of use.  This impact is driven by better access to information acquisition and enhanced human capital.  Additionally, digital technology helps stabilize the income of households facing downward volatility.  The income stabilizing effect is particularly significant among relocated households in central regions, rural resettlement areas, and those with higher education levels.  Furthermore, digital literacy amplifies the positive impact of digital technology on income stability.  These findings offer valuable insights for policymakers aiming to promote digital technology use to ensure the income stability of relocated households and foster common prosperity.

Motivated by growing concerns about excessive agrochemical use and the resulting environmental pollution in China, this study explores the importance of online agricultural information for chemical fertilizer and pesticide use decisions among grain farmers.  In particular, we focus on the functional agricultural information used for productive purposes for smallholders.  Based on a survey dataset of 1,833 family farms across five Chinese provinces, we employ a propensity score matching (PSM) approach to estimate treatment effects of online agricultural information.  The results reveal that online acquisition of agricultural information does not reduce the expenses of chemical fertilizers and pesticides in our sample; rather, the opposite is true.  The use of online agricultural information significantly increased agrochemical expenses, particularly among smallholders.  Within our sample region, the limited evolution of online information content and the inherent challenges faced by smallholder farmers are the major barriers to the beneficial effects of online agricultural information in reducing agrochemical use.  Our findings emphasize the need for targeted interventions and educational efforts to bridge the knowledge gaps of smallholders.  Furthermore, there is a need to raise awareness among information providers to ensure that their recommendations avoid encouraging overdoses of agrochemicals.  In addition, enhancing farmers’ digital literacy will be a future task of development policy.

Goats (Capra hircus) provide a rich source of products, such as meat, milk, and wool, and are important domestic animals in many parts of the world.  Goats were one of the first domesticated livestock species during the late Neolithic period, approximately 11,000 years ago, in the Fertile Crescent.  In the past decades, genomic studies of goats have provided insight into their domestication and genetic basis of economically important traits.  This review outlines the latest advancements that have been made in reference to domestication and genetic improvement of production traits such as meat and carcass quality, reproduction, milk, cashmere, and functional traits such as environmental adaptation and disease-resistance.  Genomic research is entering a new era with the availability of graphical pan-genomics and telomere-to-telomere (T2T) gap-free genome assembly, which will extend our understanding of domestication and molecular mechanistic dissection of economic traits in goats.  We provide new perspectives and future directions for genomics and suggest how the ever-increasing multi-omics dataset will facilitate future studies and molecular breeding in goat.

Seed germination, which initiates the plant life cycle, exhibits high sensitivity to salt stress, a significant environmental factor limiting rice production.  Brassinosteroid (BR), a growth-promoting phytohormone, mitigates various stresses including salt, drought, and extreme temperatures in rice.  However, the mechanisms by which BR alleviates salt stress during seed germination remain inadequately characterized.  This study demonstrates that seed-specific overexpression of OsDWF4, a rate-limiting gene in BR biosynthesis, enhances rice germination.  The DWF4-OX lines, which increase endogenous BR content in seeds, promote germination under salt stress, corroborating results obtained through exogenous BR application.  Antioxidant enzyme analyses demonstrate that BR enhances the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT).  Metabolomic analysis reveals that BR mitigates salt stress primarily through the biosynthesis of phenylpropanoids and secondary metabolites.  Transcriptomic analysis indicates that both endogenous and exogenous BR share five co-regulated target genes and utilize a common biosynthetic pathway for stilbenoids, diarylheptanoids, and gingerols.  These findings confirm BR's capacity to enhance seed germination under salt stress and identify several BR-mediated targets for developing salt-tolerant rice varieties suitable for direct seeding cultivation.

Wheat (Triticum aestivum L.) quality is a major focus of wheat breeding, which is influenced by multiple factors. The Huang-Huai wheat region, one of the main wheat-producing areas in China, provides favourable conditions for cultivating wheat cultivars with strong-gluten and medium-strong-gluten. In this study, a systematic assessment of seven crucial quality traits and important genetic loci (Glu-1 and Sec-1) in 436 wheat cultivars in the Huang-Huai wheat region of China by principal component analysis (PCA) and fuzzy comprehensive evaluation (FCE) methods showed that the stability time (ST), stretch area (SA), and maximum resistance (MAXR) were identified as three key factors, which significantly influenced wheat quality. Glu-1 and Sec-1 primarily impacted these three traits and subsequently influenced wheat quality. Compared to Glu-A1 and Glu-B1, Glu-D1 has a more significant impact on the comprehensive evaluation value D, principal components PC1-PC3, and the main traits ST, SA and MAXR of PC1. Wheat cultivars carrying the high-molecular-weight glutenin subunit (HMW-GS) Dx5+Dy10 exhibited a notable improvement in ST, SA, and MAXR traits compared with those carrying HMW-GS Dx2+Dy12, suggesting that Dx5+Dy10 may enhance wheat quality by improving ST, SA, and MAXR. By combining the results of D value, GYT (genotype by yield×trait) index, and HMW-GS score, 20 high-quality and high yield wheat cultivars were identified, which can be used as elite parents for wheat quality breeding.

Cadmium (Cd) contamination in wheat farmland is increasing at an alarming rate, posing threats to food security and public health.  Breeding and utilizing wheat varieties characterized by low Cd accumulation levels constitute an effective strategy in the battle against wheat Cd contamination.  The adoption of molecular marker-assisted approaches can greatly expedite the selection and enhancement of wheat varieties with low Cd accumulation.  Nonetheless, research concerning the genes associated with wheat cadmium accumulation remains scarce.  In this study, a high-density 660K SNP array was employed for conducting a genome-wide association study (GWAS) on the grain Cd concentration (GCdC), bioconcentration factor (BCF) and translocation factor (TF) in 175 wheat germplasms.  The findings revealed 401 significant SNPs identified across three diverse environments.  Linkage disequilibrium analysis revealed 30 core quantitative trait loci (QTLs) capable of reliably modulating wheat Cd accumulation phenotypes.  Through gene annotation, transcriptomics, and gene molecular features, four candidate genes (TraesCS7B02G000200, TraesCS4A02G035900, TraesCS4A02G040900, and TraesCS5D02G564000) were identified as potential constituents in the biological process of wheat Cd accumulation.  Furthermore, six wheat germplasms exhibiting low grain Cd accumulation were isolated, and two kompetitive allele specific PCR (KASP) markers conducive to breeding selection were developed.  These findings provide valuable genetic resources for cultivating wheat with low Cd accumulation and establish a foundation for understanding the molecular mechanisms underlying low Cd accumulation in wheat.  The candidate genes and KASP markers elucidated in this research have potential for effective use in genetic enhancement and marker-assisted selection in the breeding of wheat with low Cd accumulation.

Peanut (Arachis hypogaea L.) is an important oil and edible protein crop.  Its fatty acid composition not only influences the quality of peanut oil but also impacts flavor, shelf life, and consumer health.  Peanut oil is comprised of approximately 80% oleic acid (C18:1) and linoleic acid (C18:2), 10% palmitic acid (C16:0), and the remaining 10% includes stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0).  To unravel the genetic foundation of fatty acid content and delve into QTL localization, high-density SNP microarrays were used to genotype the RIL population of ‘SunOleic 97R’ × ‘NC94022’.  A genetic linkage map was constructed with 3,141 SNP markers, covering a total genetic distance of 3,051.81 cM.  Sixty quantitative trait loci (QTLs) associated with fatty acids were distributed in 11 linkage groups, with phenotypic variance explained (PVE) ranging from 1.37 to 44.92%.  Notably, the QTLs qFAT_A05.1 and qFAT_A08.1 are multiple-effect loci contributing to various fatty acid compositions.  Moreover, 15 haplotypes for the QTLs qFAT_A05.1 and qFAT_A08.1 were identified through genotyping 178 peanut germplasms.  Haplotype analysis in a natural population confirmed the close relationship of the QTLs with the contents of oil, oleic acid, lignoceric acid, palmitic acid and behenic acid.  This study serves as a valuable reference for selecting improved peanut genotypes with superior oil quality and desirable fatty acid composition.

Vegetable soybean ((Glycine max (L.) Merr.), commonly referred to as edamame, holds significant agricultural importance in China as a legume vegetable harvested at the pod-filling stage (R6).  The visual appeal of vegetable soybeans is crucial for consumer preference and marketability, and it depends on factors such as pod length, pod width, and pod color.  This study cultivated 264 vegetable soybeans in Nanjing, Huai’an, and Nantong, Jiangsu Province, China to assess pod traits using PlantPhenoM, a system for pod phenotypic identification and analysis.  The results revealed a variability range of 8.64 to 30.00% in appearance quality traits among the vegetable soybeans.  Leveraging phenotypic data and employing a genome-wide association study (GWAS) identified 525 SNPs significantly linked to the appearance quality traits in different regions.  In addition, five candidate genes (Glyma.04G004700, Glyma.15G051600, Glyma.18G225700, Glyma.18G225900, and Glyma.18G272300) associated with target traits were identified, and KASP markers for S04_372771 (pod length), S18_51477324 (pod width), and S18_55553200 (pod color) were developed.  This study offers valuable insights for breeding superior vegetable soybean varieties and lays the groundwork for exploring candidate genes and molecular markers related to appearance and quality traits in vegetable soybeans.

The change in leaf color during the later reproductive period of rice is directly related to photoassimilate accumulation and nutrient reuse, and it ultimately affects grain filling and yield.  This study aimed to explore an assessment model that depicts the leaf color change process, and extract parameters that can precisely distinguish differences in leaf color changes among different treatments and varieties.  A total of 31 rice varieties were selected as the field experiment materials in 2019 and 2023.  The SPAD values of the flag, 2nd and 3rd leaves were measured after heading, and they were normalized to the leaf color index (CI).  A functional model for the variation of leaf CI with time (t) in the late reproductive stage of rice was established based on CI=at²+bt+c, and seven color change parameters were extracted for the quantitative comparison and assessment of leaf color changes, including three time related parameters for color change (onset time, T₀; midpoint time, T₅₀; and color change duration, T₁₀₀); one leaf color index (final value of CI, CI_f); and three parameters related to the color change rate (the rate during T₀−T₅₀, R₁; the rate during T₅₀−T₁₀₀, R₂; and the mean color change rate, R_m).  In 2023, Chunyou 927 (CY927) with a dark leaf color and Yongyou 1540 (YY1540) with a normal leaf color were used as materials, and three N fertilizer amounts were applied to explore the effects of N fertilizer on the leaf color change process through the established assessment system.  The T₀ of the flag leaf was delayed by 2.6−3.0 d compared to the 2nd and 3rd leaves.  The CI_f of the flag leaf was 12.12 and 21.15% higher than those of 2nd and 3rd leaves, respectively.  In addition, the R₁, R₂ and R_m of the 3rd leaf were 10.75–19.82%, 17.99–20.09% and 18.23–11.61% higher than the flag and 2nd leaves, respectively.  Rice yield was significantly positively correlated with T₀, positively correlated with T₅₀ and T₁₀₀, and negatively correlated with R₁, R₂ and R_m.  The average T₀, T₅₀, and T₁₀₀ of rice varieties with yields higher than 8,000 kg ha⁻¹ were 6.8, 22.2, and 31.8 d, respectively, with a CI_f of 0.563 and an R_m of 0.015 d^–1.  N applications delayed T₀ by 4.5–6.2 d, reduced R_m by 30.06–32.33%, and increased CI_f by 35.78–39.69%.  The established leaf color change model and extracted parameters quantitatively depicted the leaf color change process during the later reproductive period.  They also effectively distinguished the differences in leaf color change among leaf positions, rice varieties and N treatments.  This approach is valuable for selecting and cultivating high-yield and nutrient-efficient rice varieties, as well as for analyzing the underlying mechanisms.

In the face of agricultural labor shortages, reducing labor and costs in rice production while meeting demand or increasing yield is crucial for sustainable agricultural development.  Using crop straw boards and raising seedlings at a high-density can reduce labor demand and enhance rice yield.  This study investigated the effects of seeding density and transplanting age on tillering patterns, panicle formation rates, and yield to determine the optimal cultivation practices for maximizing rice yield.  Two-year field experiments were conducted in Sihong County, Jiangsu Province, China, using the japonica rice variety Nanjing 5718.  Five seeding densities (150–350 g/tray) and four transplanting ages (10–25 days) were evaluated to assess their impacts on tillering patterns, panicle formation rates, and yield.  Innovative crop straw boards were employed to enhance planting efficiency and reduce dependence on soil for raising seedlings.  This approach also lessened tillage layer destruction, promoting sustainable practices.  The results indicated that increasing seeding density significantly altered tillering and panicle formation patterns by reducing the occurrence and panicle formation rates of lower-position tillers.  Although the occurrence of middle- and high-position tillers increased, the overall number of panicles per hill decreased, especially at higher densities, negatively affecting yield.  Reducing the transplanting age promoted the emergence and panicle formation of lower-position tillers, thus mitigating these negative effects.  Specifically, compared to traditional methods (150 g/tray, 20-day seedlings), the higher seeding density (300 g/tray) and reduced transplanting age (15-day seedlings) increased total panicle number by 3.79–4.73% and yield by 3.38–5.05%.  Combining higher seeding densities with reduced transplanting ages offers significant advantages over conventional practices by enhancing resource utilization and improving tillering efficiency.  These findings provide actionable recommendations for optimizing rice cultivation practices and contribute to sustainable agricultural development.