Heat Stress and Plant–Biotic Interactions: Advances and Perspectives

Plants, Journal Year: 2024, Volume and Issue: 13(15), P. 2022 - 2022

Published: July 23, 2024

Climate change presents numerous challenges for agriculture, including frequent events of plant abiotic stresses such as elevated temperatures that lead to heat stress (HS). As the primary driving factor climate change, HS threatens global food security and biodiversity. In recent years, have negatively impacted physiology, reducing plant's ability maintain disease resistance resulting in lower crop yields. Plants must adapt their priorities toward defense mechanisms tolerate challenging environments. Furthermore, selective breeding long-term domestication higher yields made varieties vulnerable multiple stressors, making them more susceptible events. Studies on predict concurrent biotic will become severe future, potentially occurring simultaneously or sequentially. While most studies focused singular effects systems examine how plants respond specific stresses, simultaneous occurrence pose a growing threat agricultural productivity. Few explored interactions between plant-biotic interactions. Here, we aim shed light physiological molecular (bacteria, fungi, oomycetes, nematodes, insect pests, pollinators, weedy species, parasitic plants), well combined impact growth We also advances designing developing various strategies address multi-stress scenarios related factors.

Language: Английский

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Formation of a Novel Antagonistic Bacterial Combination to Enhance Biocontrol for Cucumber Fusarium Wilt

Microorganisms, Journal Year: 2025, Volume and Issue: 13(1), P. 133 - 133

Published: Jan. 10, 2025

Paenibacillus polymyxa strain PJH16, isolated and tested by our team, suppresses cucumber Fusarium wilt as an efficient biocontrol agent. For further investigation, the has been combined with two other Bacillus strains (Bacillus velezensis VJH504 subtilis JNF2) to enhance ability, which formed high-efficiency microbial agents in current study. The methodological target taken is based on achieving optimal growth conditions of agents; hence, medium composition culture were optimized through a single-factor test, orthogonal test response surface methodology. Following this, effectiveness combination was assessed pot experiments, provided theoretical foundation for synthesis flora significantly control wilt. results showed excellent compatibility, proving suitable proliferation VJH504, JNF2 together, specifically, when inoculation amounts adjusted 4% each. Using analysis, optimum composite identified 3% glucose carbon source, 2% yeast extract powder preferred nitrogen 1% dipotassium hydrogen phosphate most inorganic salt. Furthermore, optical density (OD600) solution reached its highest level at 3.16 under following conditions: volume 200 µL, 171 rpm speed, 21.6 h time, 30 °C cultural temperature, initial pH 7.0. experiment demonstrated that mixed bacterial achieved relative efficacy 93.4% against wilt, superior single- or pesticide treatment, also promoted growth. In summary, synthesized three displayed high concentration, optimization conditions, exerted remarkable growth-promoting effects This finding holds great significance future developments agents.

Language: Английский

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Modeling Whole-Plant Carbon Stock in Olea europaea L. Plantations Using Logarithmic Nonlinear Seemingly Unrelated Regression

Agronomy, Journal Year: 2025, Volume and Issue: 15(4), P. 917 - 917

Published: April 8, 2025

Carbon stock (CS) is an important indicator of the structure and function forest ecosystems, plays role in mitigating climate change, maintaining ecological system balance, promoting carbon trading, other socioeconomic values. Olea europaea L. a species high economic value, its excellent nutritional composition, strong drought tolerance, sustainable production characteristics, promotion agrodiversity make it guaranteeing food security. Accurately estimating CS offers reliable reference for artificial breeding yield prediction. Firstly, independent estimation model was constructed, while compatibility unitary binary constructed using nonlinear metric error. Secondly, system, total by Logarithmic Nonlinear Seemingly Unrelated Regression (LNSUR) method with D D2H as variables. The results show: (1) Aboveground (AGCS) C = 0.0014D1.92876H0.67174 (R2 0.909), Belowground (BGCS) 0.00723D1.23578H0.48553 0.686). AGCS effectively addresses issue component sums not equaling total, low RMSE (1.918); (2) LNSUR improved accuracy BGCS more significantly 0.787), estimated also had smaller (0.241~0.418); (3) Whole-plant 15 sample plots R2 0.964. This study first attempt to construct L., which provides scientific technological basis monitoring value indicators, such sink capacity.

Language: Английский

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Alternatives to chemical pesticides: the role of microbial biocontrol agents in phytopathogen management: a comprehensive review

Journal of Plant Pathology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 3, 2024

Language: Английский

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