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Application of rhizospheric fungi is an effective and environmentally friendly method of improving plant growth and controlling many plant diseases. The current study was aimed to identify phytohormone-producing fungi from soil, to understand their roles in sesame plant growth, and to control Fusarium disease. Three predominant fungi (PNF1, PNF2, and PNF3) isolated from the rhizospheric soil of peanut plants were screened for their growth-promoting efficiency on sesame seedlings. Among these isolates, PNF2 significantly increased the shoot length and fresh weight of seedlings compared with controls. Analysis of the fungal culture filtrate showed a higher concentration of indole acetic acid in PNF2 than in the other isolates. PNF2 was identified as Penicillium sp. on the basis of phylogenetic analysis of ITS sequence similarity. The in vitro biocontrol activity of Penicillium sp. against Fusarium sp. was exhibited by a 49% inhibition of mycelial growth in a dual culture bioassay and by hyphal injuries as observed by scanning electron microscopy. In addition, greenhouse experiments revealed that Fusarium inhibited growth in sesame plants by damaging lipid membranes and reducing protein content. Co-cultivation with Penicillium sp. mitigated Fusarium-induced oxidative stress in sesame plants by limiting membrane lipid peroxidation, and by increasing the protein concentration, levels of antioxidants such as total polyphenols, and peroxidase and polyphenoloxidase activities. Thus, our findings suggest that Penicillium sp. is a potent plant growthpromoting fungus that has the ability to ameliorate damage caused by Fusarium infection in sesame cultivation.

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Anthocyanins play an important role in physiological functions related to human health. The objective of this study was to investigate the profiles of anthocyanins in the immature purple pods and black seeds of yard-long beans ( Vigna unguiculata ssp. sesquipedalis L.) using high-performance liquid chromatography (HPLC) with diode array detection and electrospray ionization/mass spectrometry (DAD-ESI/MS) analysis. The individual anthocyanins were identified by comparing their mass spectrometric data and retention times. In the purple pods, five individual anthocyanins were identified: delphinidin-3-O-glucoside (2), cyanidin-3-O-sambubioside (4), cyanidin-3-O-glucoside (5), pelargonidin-3-O-glucoside (7), and peonidin-3-O-glucoside (8). From the black seed coat of the yard-long beans, seven anthocyanins were identified, including delphinidin-3-O-galactoside (1), cyanidin-3-O-galactoside (3), petunidin-3-O-glucoside (6), and malvidin-3-O-glucoside (9), together with compounds 2, 5, and 8. In this study, we report for the first time anthocyanin profiles for the pod and seed coat of yard-long beans.

Accurate information on the gross primary production (GPP) of paddy rice cropland is critical for assessing and monitoring rice growing conditions. The eddy co-variance technique was used to measure net ecosystem exchange (NEE) of CO 2 between paddy rice croplands and the atmosphere, and the resultant NEE data then partitioned into GPP (GPP EC ) and ecosystem respiration. In this study, we first used the GPP EC data from four paddy rice flux tower sites in South Korea, Japan and the USA to evaluate the biophysical performance of three vegetation indices: Normalized Difference Vegetation Index (NDVI); Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI) in terms of phenology (crop growing seasons) and GPP EC , which are derived from images taken by Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also ran the Vegetation Photosynthesis Model (VPM), which is driven by EVI, LSWI, photosynthetically active radiation (PAR) and air temperature, to estimate GPP over multiple years at these four sites (GPP VPM ). The 14 site-years of simulations show that the seasonal dynamics of GPP VPM successfully tracked the seasonal dynamics of GPP EC (R 2 ＞0.88 or higher). The cross-site comparison also shows that GPP VPM agreed reasonably well with the variations of GPP EC across both years and sites. The simulation results clearly demonstrate the potential of the VPM model and MODIS images for estimating GPP of paddy rice croplands in the monsoon climates of South Korea and Japan and the Mediterranean climate in California, USA. The application of VPM to regional simulations in the near future may provide crucial GPP data to support the studies of food security and cropland carbon cycle around the world.