Soil is a heterogeneous medium that exhibits considerable variability in both spatial and temporal dimensions. Proper management of field variability using variable-rate fertilization (VRF) techniques is essential to maximize crop input–output ratios and resource utilization. Implementing VRF technology on a localized scale is recommended to increase crop yield, decrease input costs, and reduce the negative impact on the surrounding environment. This study assessed the agronomic and environmental viability of implementing VRF during the cultivation of summer maize using an on-the-go detector of soil total nitrogen (STN) to detect STN content in the test fields. A spatial delineation approach was then applied to divide the experimental field into multiple management zones. The amount of fertilizer applied in each zone was determined based on the sensor-detected STN. The analysis of the final yield and economic benefits indicates that plots that adopted VRF treatments attained an average summer maize grain yield of 7275 kg ha⁻¹, outperforming plots that employed uniform-rate fertilization (URF) treatments, which yielded 6713 kg ha⁻¹. Through one-way ANOVA, the yield p values of the two fertilization methods were 6.406 × 10⁻¹⁵, 5.202 × 10⁻¹⁵, 2.497 × 10⁻¹⁵, and 3.199 × 10⁻¹⁵, respectively, indicating that the yield differences between the two fertilization methods were noticeable. This led to an average yield increase of 8.37% ha⁻¹ and a gross profit margin of USD 153 ha⁻¹. In plots in which VRF techniques are utilized, the average nitrogen (N) fertilizer application rate is 627 kg ha⁻¹. In contrast, in plots employing URF methods, the N fertilizer application rate is 750 kg ha⁻¹. The use of N fertilizer was reduced by 16.4%. As a result, there is a reduction in production costs of USD 37.5 ha⁻¹, achieving increased yield while decreasing the amount of applied fertilizer. Moreover, in plots where the VRF method was applied, STN was balanced despite the reduced N application. This observation can be deduced from the variance in summer maize grain yield through various fertilization treatments in a comparative experiment. Future research endeavors should prioritize the resolution of particular constraints by incorporating supplementary soil data, such as phosphorus, potassium, organic matter, and other pertinent variables, to advance and optimize fertilization methodologies.

Soil fertility is critical for crop production. However, conventional uniform fertilization often causes over-application, leading to resource waste and pollution. Variable-rate fertilization (VRF) is a core precision agriculture technology for optimizing nutrient use. Nevertheless, current VRF equipment suffers from inefficient soil nutrient prediction, limited precision and low intelligence. This study develops a mobile bivariate fertilizer applicator integrating a spectral detection system, a mechanical system and a control system. The equipment breaks through the traditional fixed combination mode of motor speed and gate opening degree in conventional bivariate fertilization devices. The vehicle-mounted spectral sensor offers greater mobility and field-deployment capability than portable spectral detection devices. The self-designed mechanical structure incorporates an external groove wheel fertilizer discharger and a disc plow, enhances field efficiency and prevents optical fiber twisting. The Raspberry Pi 4B-based control system implements a three-level precision enhancement mechanism that includes experimental calibration, data screening, and polynomial regression. This process involves collecting raw data from stepwise univariate experiments, eliminating data segments with abnormal uniformity, and employing response surface methodology to establish a bivariate interaction model. An average accuracy of 98.09% and a fertilizer discharge range of 0.0430–0.2055 kg/s are maintained across the operational range of 40% to 100% for both rotational speed and opening degree. The bivariate combination algorithm overcomes traditional fixed-parameter selection mode, and the system addresses the shortcomings of existing VRF systems in terms of integration, accuracy, efficiency, and robustness.

Strigolactones (SLs) are carotenoid-derived phytohormones with numerous regulatory functions in plant growth, development and stress adaptation. While their roles in symbiotic associations and abiotic stress tolerance are well documented, their contribution to postharvest disease resistance remains poorly understood. In this study, sweet cherries were treated with a range of SL concentrations (0-2 μM) or Tis-108 (an inhibitor of SL biosynthesis) and subsequently inoculated with Botrytis cinerea. An SL concentration of 0.1 μM markedly suppressed gray mold as evidenced by reduced disease incidence, lesion diameter and fungal biomass relative to control, while Tis-108 exacerbated the infection. Multi-omics analyses revealed pronounced upregulation of genes involved in phenylalanine, tyrosine and tryptophan biosynthesis, phenylpropanoid biosynthesis and flavonoid biosynthesis. In particular, the rate-limiting enzymes of the phenylpropanoid pathway, including PAL, C4H and 4CL, exhibited the greatest transcriptional and enzymatic upregulation. Consistent with this, 0.1 μM SL treatment substantially enhances the accumulation of total phenolics, flavonoids and major individual phenolic compounds (such as catechin, epicatechin, rutin and chlorogenic acid, etc.), alongside enhanced activities of pathogenesis-related chitinase and β-1,3-glucanase. Collectively, these results demonstrate that SLs act as positive regulators of induced defense in postharvest sweet cherries through coordinated reprogramming of phenylpropanoid-derived secondary metabolism. This study offers novel mechanistic insights into SL-mediated defense modulation, suggesting promising applications of SL in enhancing fruit quality, extending shelf life, and reducing postharvest losses.

Strigolactones (SLs) are carotenoid-derived phytohormones that regulate plant growth, development, and stress adaptation. Although SL-related regulation of plant immunity has been increasingly recognized, its role in postharvest disease resistance remains largely unexplored. In this study, postharvest cherries were treated with different concentrations (0, 0.01, 0.1, 0.5, 1, 1.5, and 2 μM) of rac-GR24, a synthetic SL analogue, or with Tis-108, a chemical inhibitor of SL biosynthesis that targets the cytochrome P450 MAX1 (CYP711A), prior to inoculation with Botrytis cinerea. Among the tested concentrations, 0.1 μM rac-GR24 most effectively suppressed gray mold development, as reflected by reduced disease incidence, lesion diameter, and fungal biomass compared with the control, together with enhanced activities of defense-related enzymes, including CHI and GLU, whereas Tis-108 treatment aggravated disease development. Integrated transcriptomic and metabolomic analyses revealed significant changes in pathways related to phenylalanine, tyrosine, and tryptophan biosynthesis, as well as phenylpropanoid and flavonoid biosynthesis. Notably, rac-GR24 treatment markedly increased the expression and activities of key enzymes involved in the phenylpropanoid pathway, including PAL, C4H, and 4CL. Consistent with these molecular responses, rac-GR24 treatment significantly increased the accumulation of total phenolics, flavonoids, and representative compounds such as catechin, epicatechin, rutin, and chlorogenic acid. Overall, these findings suggest that rac-GR24 treatment is associated with defense responses and changes in phenylpropanoid metabolism in postharvest sweet cherry. This study provides new insights into the molecular basis of defense responses induced by rac-GR24 and highlights its potential as an effective strategy to reduce postharvest losses.