Excessive nitrogen and insufficient calcium could significantly impact peanut yields. This study investigated the effects of nitrogen and calcium fertilizers on nutrient absorption, utilization, and yield; experiments were conducted using the peanut cultivar from Xianghua 2008 in a split-plot arrangement with two calcium fertilizer levels (Ca₀: 0 and Ca₁: 568 kg CaO ha⁻¹) in the main plots and six nitrogen fertilizer gradients (N₀: 0, N_45.0: 45.0, N_90.0: 90.0, N_112.5: 112.5, N_135.0: 135.0, and N_157.5: 157.5 kg N ha⁻¹) in subplots between 2015 and 2016 in Changsha, China. We examined the impact of different rates of calcium and nitrogen fertilizers on the net photosynthetic rate (Pn), agronomic traits, dry matter quality, yield and yield composition, nutrient accumulation, and distribution. The combined application of calcium and nitrogen fertilizers significantly affected the yield and yield components, Pn, main stem height, dry matter, and nutrient accumulation. Under the same calcium level, nitrogen application significantly increased the main stem height and Pn and promoted the accumulation of dry matter and nutrients in the plant, particularly in the kernel. Under the same nitrogen treatment, calcium significantly increased Pn and promoted the accumulation of dry matter, calcium, and magnesium. The pod yield increased gradually with an increasing nitrogen application rate (0–112.5 kg ha⁻¹) and peaked at N_112.5, increasing by 52.3–138.0% compared with N₀. However, excessive nitrogen application (N > 112.5 kg ha⁻¹) decreased the pod yield. Under different nitrogen fertilizer levels, calcium application increased pod yields by 11.5–29.6% by promoting Pn, nutrient uptake, accumulation in the individual plant, and nutrient accumulation in the kernel. Therefore, this study suggested that adjusting the calcium (568 kg ha⁻¹) and nitrogen (112.5 kg ha⁻¹) fertilizer rates significantly improved peanut growth and productivity by enhancing photosynthetic efficiency and nutrient accumulation in calcium-deficient acidic red soil.

The leaf area index (LAI) is a crucial metric for indicating crop development in the field, essential for both research and the practical implementation of precision agriculture. Unmanned aerial vehicles (UAVs) are widely used for monitoring crop growth due to their rapid, repetitive capture ability and cost-effectiveness. Therefore, we developed a non-destructive monitoring method for peanut LAI, combining UAV vegetation indices (VI) and texture features (TF). Field experiments were conducted to capture multispectral imagery of peanut crops. Based on these data, an optimal regression model was constructed to estimate LAI. The initial computation involves determining the potential spectral and textural characteristics. Subsequently, a comprehensive correlation study between these features and peanut LAI is conducted using Pearson’s product component correlation and recursive feature elimination. Six regression models, including univariate linear regression, support vector regression, ridge regression, decision tree regression, partial least squares regression, and random forest regression, are used to determine the optimal LAI estimation. The following results are observed: (1) Vegetation indices exhibit greater correlation with LAI than texture characteristics. (2) The choice of GLCM parameters for texture features impacts estimation accuracy. Generally, smaller moving window sizes and higher grayscale quantization levels yield more accurate peanut LAI estimations. (3) The SVR model using both VI and TF offers the utmost precision, significantly improving accuracy (R² = 0.867, RMSE = 0.491). Combining VI and TF enhances LAI estimation by 0.055 (VI) and 0.541 (TF), reducing RMSE by 0.093 (VI) and 0.616 (TF). The findings highlight the significant improvement in peanut LAI estimation accuracy achieved by integrating spectral and textural characteristics with appropriate parameters. These insights offer valuable guidance for monitoring peanut growth.

The application of nitrogen fertilizer is crucial to the growth and biological nitrogen fixation of peanut, especially in the seedling stage where nodules have not yet formed. However, it is still uncertain how much initial nitrogen fertilizer should be applied to promote peanut root growth, nodule formation, and biological nitrogen fixation (BNF). There, a 2-year pot experiment was conducted using Huayu 22 (HY22, large-grain cultivar) and Huayu 39 (HY39, small-grain cultivar) as experimental materials to research the effects of different initial nitrogen fertilizer application rates on peanut root growth (root weight, root length, root mean diameter, root activity) and biological nitrogen fixation capacity (nodule number, nodule weight, biological nitrogen fixation, and nitrogen fixation potential per plant). N₀, as control, four initial nitrogen fertilizer application rates were established: 15 kg·hm⁻² (N₁₅), 30 kg·hm⁻² (N₃₀), 45 kg·hm⁻² (N₄₅), and 60 kg·hm⁻² (N₆₀). The present results showed that the nodule number, nodule dry weight, nitrogenase activity, and biological nitrogen fixation of the HY22 cultivar under the N₁₅ treatment were higher compared to those under other treatments over the two growing seasons. In addition, the cultivar of HY39 treated with the N₁₅ treatment also increased the nitrogen fixation potential per plant and BNF relative to other treatments. Although the application of 60 kg·hm⁻² nitrogen increased the root surface area and root volume, it decreased the nitrogenase activity, nodule dry weight, and nitrogen fixation potential per plant of HY22 and HY39 varieties in both growing seasons. Above all, an initial nitrogen application of 15 kg·hm⁻² may be the optimal treatment for promoting peanut nodule formation and biological nitrogen fixation.

The dual challenges of global climate change and reductions in the amount of arable land represent growing threats to the stability of global human populations. Efforts to further optimize cropping systems to maximize yields while minimizing greenhouse gas emissions in limited land areas have thus emerged as a focus in modern agriculture. Cereal-intercropping management strategies may represent a promising approach to simultaneously addressing both of these challenges in China. We aimed at comprehensively assessing changes in yield, carbon footprint, and net ecosystem economic benefit when transitioning from maize/peanut monoculture to intercropping in a field-scale study in an effort to aid in the development of low-carbon intercropping systems that do not have an adverse impact on Chinese grain yields. Beginning in June of 2018, a randomized complete block design with three treatments was used to initiate this study: (1) peanut monoculture (P), (2) maize monoculture (M), and (3) maize/peanut intercropping (MP). We compared yield, greenhouse gas emissions, carbon footprint and net ecosystem economic benefit. Results over four years showed that the land equivalent ratio associated with MP was greater than 1. All three of these cropping systems were net CO₂ and N₂O sources as well as net CH₄ sinks, with MP generating significantly (p < 0.05) lower N₂O and CO₂ flux as well as smaller seasonal N₂O and CO₂ emissions relative to M. MP additionally reduced the carbon footprint associated with this cropping system by 11.11–31.65% and 30.37–43.62% relative to M and P, respectively. Consistently, MP treatment resulted in respective 70.69% and 26.25% net ecosystem economic benefit (NEEB) increases relative to the M and P conditions while simultaneously enhancing energy use efficiency. In summary, MP systems have potential economic benefit with lower environmental risk alternative to traditional peanut or maize monocropping systems. Converting from peanut or maize monocropping systems to MP systems practices contributed to improved farmland use efficiency, clean production and increased farmers’ income in an agricultural system.

Rhizobia form symbiotic relationships with legumes, fixing atmospheric nitrogen into a plant-accessible form within their root nodules. Nitrogen fixation is vital for sustainable soil improvements in agriculture. Peanut (Arachis hypogaea) is a leguminous crop whose nodulation mechanism requires further elucidation. In this study, comprehensive transcriptomic and metabolomic analyses were conducted to assess the differences between a non-nodulating peanut variety and a nodulating peanut variety. Total RNA was extracted from peanut roots, then first-strand and second-strand cDNA were synthesized and purified. After sequencing adaptors were added to the fragments, the cDNA libraries were sequenced. Our transcriptomic analysis identified 3362 differentially expressed genes (DEGs) between the two varieties. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that the DEGs were mainly involved in metabolic pathways, hormone signal transduction, secondary metabolic biosynthesis, phenylpropanoid biosynthesis, or ABC transport. Further analyses indicated that the biosynthesis of flavonoids, such as isoflavones, flavonols, and flavonoids, was important for peanut nodulation. A lack of flavonoid transport into the rhizosphere (soil) could prevent rhizobial chemotaxis and the activation of their nodulation genes. The downregulation of AUXIN-RESPONSE FACTOR (ARF) genes and lower auxin content could reduce rhizobia’s invasion of peanut roots, ultimately reducing nodule formation. Auxin is the major hormone that influences the cell-cycle initiation and progression required for nodule initiation and accumulates during different stages of nodule development. These findings lay the foundation for subsequent research into the nitrogen-fixation efficiency of peanut nodules.

Peanut (Arachis hypogaea L.) is one of the most important crops for oil and protein production. The unique characteristic of peanut is geocarpy, which means that it blooms aerially and the peanut gynophores (pegs) penetrate into the soil, driving the fruit underground. In order to fully understand this phenomenon, we investigated the dynamic proteomic and phosphoproteomic profiling of the pegs aerially and underground in this study. A total of 6859 proteins and 4142 unique phosphoproteins with 10,070 phosphosites were identified. The data were validated and quantified using samples randomly selected from arial pegs (APs) and underground pegs (UPs) by parallel reaction monitoring (PRM). Function analyses of differentially abundant proteins (DAPs) and differentially regulated phosphoproteins (DRPPs) exhibited that they were mainly related to stress response, photosynthesis, and substance metabolism. Once the pegs successfully entered the soil, disease-resistant and stress response proteins, such as glutathione S-transferase, peroxidase, and cytochrome P450, significantly increased in the UP samples in order to adapt to the new soil environment. The increased abundance of photosynthesis-associated proteins in the UP samples provided more abundant photosynthetic products, which provided the preparation for subsequent pod development. Phosphoproteomics reveals the regulatory network of the synthesis of nutrients such as starch, protein, and fatty acid (FA). These results provide new insights into the mechanism, indicating that after the pegs are inserted into the soil, phosphorylation is involved in the rapid elongation of the pegs, accompanied by supplying energy for pod development and preparing for the synthesis of metabolites during pod development following mechanical stimulation and darkness.