Plants have evolved several adaptive strategies through physiological changes in response to herbivore attacks. Plant secondary metabolites (PSMs) are synthesized to provide defensive functions and regulate defense signaling pathways to safeguard plants against herbivores. Herbivore injury initiates complex reactions which ultimately lead to synthesis and accumulation of PSMs. The biosynthesis of these metabolites is regulated by the interplay of signaling molecules comprising phytohormones. Plant volatile metabolites are released upon herbivore attack and are capable of directly inducing or priming hormonal defense signaling pathways. Secondary metabolites enable plants to quickly detect herbivore attacks and respond in a timely way in a rapidly changing scenario of pest and environment. Several studies have suggested that the potential for adaptation and/or resistance by insect herbivores to secondary metabolites is limited. These metabolites cause direct toxicity to insect pests, stimulate antixenosis mechanisms in plants to insect herbivores, and, by recruiting herbivore natural enemies, indirectly protect the plants. Herbivores adapt to secondary metabolites by the up/down regulation of sensory genes, and sequestration or detoxification of toxic metabolites. PSMs modulate multi-trophic interactions involving host plants, herbivores, natural enemies and pollinators. Although the role of secondary metabolites in plant-pollinator interplay has been little explored, several reports suggest that both plants and pollinators are mutually benefited. Molecular insights into the regulatory proteins and genes involved in the biosynthesis of secondary metabolites will pave the way for the metabolic engineering of biosynthetic pathway intermediates for improving plant tolerance to herbivores. This review throws light on the role of PSMs in modulating multi-trophic interactions, contributing to the knowledge of plant-herbivore interactions to enable their management in an eco-friendly and sustainable manner.

The weather-based prediction model for brown planthopper (BPH), Nilaparvata lugens (Stal) was developed and validated using BPH sweep net catch data collected from Delhi during kharif 2017 and 2018. The BPH incidence started from 29^th standard meteorological week (SMW) onwards (3BPH/20 sweeps) and attained its peak during 43^rd SMW (213 BPH/20 sweeps) during kharif 2017. However, it declined thereafter and eventually disappeared after 47^th SMW. The BPH sweep net catches revealed maximum and significant positive correlation with sun shine hours (SSH) of 2-lag week, and showed a significant negative correlation with evening relative humidity (RH₂) and wind velocity (WV) of current and 1-lag week. On the other hand, BPH catches revealed a positive correlation with Tmax and morning relative humidity (RH₁) of current, 1-lag as well as 2-lag week. Similarly, BPH catches had a negative association with Tmin and rainfall (RF) of current, 1-lag and 2-lag week. Of the weather factors RH₁, RH₂ and SSH were found to be the important factors that influenced BPH sweep net catches. The model was validated with the pest and weather data collected during kharif 2018 (R² =0.733, RSME=2.16, MBE=-0.64 and MAE= 1.72.)