ACS agricultural science & technology最新文献

Nitrogen fertilization in agriculture has serious environmental consequences, including production of the greenhouse gas nitrous oxide (N₂O), pollution of groundwater with nitrate (NO₃^–), and river eutrophication. Nitrogen use efficiency can be increased by amending fertilizers with inhibitors to slow microbial nitrification processes, which transform ammonia to NO₃^–. Unfortunately, commercial inhibitors have failed to perform reliably across various agroecosystems for reasons not well understood. Using a combination of bacterial studies and soil incubations, we demonstrate here that 4-methyl-1-(prop-2-yn-1-yl)-1H-1,2,3-triazole (MPT) exhibits superior nitrification inhibitory properties. Unlike the commercial reversible inhibitors, MPT acts as a mechanistic, irreversible inhibitor of the key enzyme ammonia monooxygenase, enabling effective retention of ammonium (NH₄⁺) and suppression of NO₃^– and N₂O production over 21 days in several agricultural soils with pH values ranging from 4.7 to 7.5. A bacterial viability stain and a suite of freshwater and terrestrial ecotoxicity tests did not indicate any acute or chronic toxicity. Real-time quantitative polymerase chain reaction (qPCR) analysis revealed an enhanced inhibitory effect of MPT on both ammonia-oxidizing bacteria and archaea. Thus, MPT outperforms currently available nitrification inhibitors and has great potential for broad application in various agricultural settings.

Plants respond to environmental pollutants and experience several abiotic stresses, among which heavy metal stress has been a serious concern in the global scientific community due to its yield-limiting effects on crop plants. Heavy metals intrude into the plant defense system and interfere with the cellular machinery, leading to metal toxicity and resulting in plant growth inhibition or death. Plants employ several counterbalance strategies, such as the formation of phytochelatins or metallothionein metal complexes, or vacuolar sequestration of ligand–metal complexes, etc., to combat heavy metal stress. Additionally, microbes present in the rhizospheric region share a special relationship with plants and immobilize heavy metals to improve plant health. Thus, the precise detection of heavy metals in adjoining environments is crucial to develop strategic defense strategies for sustainable agriculture. In this context, plant-based biomarkers have evolved as a promising approach. This review sheds light on heavy metal stress, various defense strategies employed by plants, and potential biomarkers used to detect heavy metal stresses and tries to draw a possible roadmap toward smart and sustainable agriculture.

Cyanobacterial blooms are a global ecological problem. The purpose of this study is to find microbial strains that can be used for the biological control of cyanobacterial blooms. In this study, a strain of Lysinibacillus fusiformis (QY-12) with the best algae inhibition effect was isolated and screened. The inhibition rate of Microcystis aeruginosa in the growth index period was 82.01% after 8 days of interference by QY-12. The algicidal substance l-2-aminoadipic acid (L-2-AA) produced by QY-12 was purified via preparative HPLC and identified by nuclear magnetic resonance (NMR), liquid chromatography-mass spectrometry (LC-MS) and infrared spectroscopy (IR). It was found by scanning electron microscopy that L-2-AA had a significant inhibitory effect on Microcystis aeruginosa in the early and middle stages of growth. This study provides a new idea for the prevention and control of cyanobacterial blooms.

Vegetable pests and diseases are some of the main factors affecting vegetable yield. Accurate monitoring and intelligent identification of vegetable pests and diseases are prerequisites for pest forecasting and integrated control. In this study, a vegetable pest identification system based on an improved Alexnet algorithm and 5G communication is designed. The system uses high-definition cameras and 5G communication modules to form the pest monitoring network. It builds an image recognition model based on the improved Alexnet algorithm to identify vegetable pests, and then it collects pictures for transmission to the terminal. After the experimental test, the pest identification system proposed in this study accounts for only 11.71, 11.91, 30.92, and 31.38% of the identification system of the 4G communication network in terms of transmission delay, transmission jitter, packet loss rate, and packet error rate, respectively. The recognition accuracy of the improved Alexnet algorithm is 18.76% higher than that of the unimproved one. After multiple iterations, it is verified that the recognition accuracy and loss function are better than those of the unimproved Alexnet algorithm. It shows that the identification system proposed can better monitor and identify vegetable pests and diseases, which is beneficial to integrated management.

The objective of this study was to investigate the nitrogen use efficiency of various wheat varieties and to establish evaluation indicators for nitrogen efficient use in wheat, thereby providing both theoretical reference and a practical basis. The experiment was conducted at Jiaozhou Modern Agriculture Demonstration Park of Qingdao Agricultural University (35.53°N, 119.58°E) from October 2021 to June 2023. Twenty-six main wheat varieties in the North China Plain were used as test materials. Four nitrogen fertilizer levels of 0, 150, 210, and 270 kg/hm² were set up. The nitrogen fertilizer level was the main factor, and the variety was the secondary factor. According to the yield and nitrogen accumulation of each variety under different nitrogen fertilizer levels, cluster analysis was carried out, respectively. It was found that Zhongmai 578 (H1), Zhongmai 175 (H2), and Weimai 8 (H3) had a higher yield under four nitrogen fertilizer levels. These varieties were nitrogen efficient, and their nitrogen accumulation was also higher. On the other hand, Jingshuang 16 (L1), Nongda 212 (L2), and Beijing 841 (L3) had lower yields under four nitrogen fertilizer levels. These varieties were nitrogen inefficient, and their nitrogen accumulation was also lower. The other 20 varieties had a medium yield and medium nitrogen accumulation. In this study, the differences of nitrogen use efficiency, nitrogen harvest index, nitrogen agronomic efficiency, and nitrogen partial factor productivity between three nitrogen efficient varieties and three nitrogen inefficient varieties were analyzed.

As a primary food cereal, maize (Zea mays L.) has been domesticated for thousands of years and undergoes four breeding stages to date, including Breeding 1.0 (experience breeding), Breeding 2.0 (experimental breeding), Breeding 3.0 (biological breeding), and Breeding 4.0 (intelligent breeding). In this review, we focus on the recent advances of modern breeding strategies and their applications in the maize Breeding 3.0 stage. These modern breeding strategies mainly include marker-assisted selection, genomic selection, genetic engineering, haploid induced breeding, gene editing, and synthetic biology, which act as breeding accelerators and lead to maize improvement in different important traits, such as male sterility, grain yield, grain quality, biotic and abiotic stress resistance, and nitrogen use efficiency. Furthermore, we also propose several promising breeding strategies in the next era of Breeding 4.0, which will improve maize production greatly for ensuring global food security.

Drought stress significantly affects plant growth and productivity, including sunflowers (Helianthus annuus L.). Superabsorbent hydrogels, specifically composed of dextrin and polyacrylamide, offer a potential solution to mitigate drought stress and enhance the biochemical traits of sunflowers. This study explored the impact of copolymer composition on the gel fraction, swelling behavior, water retention, morphology, and chemical structure of dextrin (Dix)/polyacrylamide (PAAm) hydrogels synthesized via radical polymerization. Results revealed that the 50/50 ratio of the Dix/PAAm hydrogel exhibited desirable characteristics, including a heterogeneous pore structure (approximately 100 μm) and higher water absorption capacity attributed to a greater Dix content. In a pot experiment, the (Dix/PAAm) hydrogel played a crucial role in alleviating the harmful effects of drought stress on the growth, chlorophyll content, fresh shoot weight, and pigments in sunflowers. The hydrogel application positively influenced these parameters by enhancing water retention, nutrient availability, and physiological responses to drought stress. Overall, these findings highlight the potential of the (Dix/PAAm) hydrogel as an effective tool for enhancing plant resilience to drought stress and promoting growth and biochemical traits in sunflowers.

In precision agriculture, nanotechnology has made significant contributions to the development of a smart cropping system through the support of unique properties of nanomaterials. Of the various nanomaterials, porous nanomaterials have an outstanding performance in building a sustainable delivery system for agrochemicals. In pesticide delivery, amorphous porous silica nanomaterials are considered as some of the most suitable options because of their easy synthesis processes, nontoxic nature, structural variation, tunable porous structure, physical and chemical stability, and ease of surface functionality. So far, multiple roles of these materials have been discussed in the literature; however, the influence of porous structure and structural variations toward developing a sustainable delivery system was not clear. A comprehensive review of the compatibility among the porous silica nanocarriers and pesticide molecules is also lacking. Thus, this review discusses the progress of porous amorphous silica nanomaterial synthesis, their structural variation, and surface modification for effective delivery of different pesticides to explore their potential as carriers.

Diuron (DU) is a kind of cotton defoliant with high toxicity and strong persistence that poses a serious environmental threat. DU has electroactive inertness and oxidation resistance, and there are only a few types of recognition elements, making its sensitive and specific detection critical. Herein, a novel molecularly imprinted polymer-based electrochemical (MIP-EC) sensor was developed by combing gold nanocages (AuNCs) with hollow-interior and porous walls with amino-functionalized reduced graphene oxide nanosheets (NH₂-rGO) with a large surface area and excellent conductivity. Then, DU-MIP was directly grown on the modified electrode by electropolymerization, while it displayed a high imprinted factor (6.91) and high reusability (at least 5 times). Significantly, the NH₂-rGO/AuNC nanocomposite could also enhance the recognition efficiency of DU-MIP, improving the analytical performances of the MIP-EC sensor, with the detection limit down to 4.3 ng/mL. In addition, this sensor exhibited high selectivity and rapid elution/recombination, and a simple construction process was utilized to detect DU in cotton and soil.