Simultaneous overexpression of multiple herbicide-metabolizing genes for broad-spectrum resistance in an agricultural weed Echinochloa phyllopogon

The use of herbicides in agricultural fields has driven the evolution of weeds for resistance, causing a grave threat to the current agriculture. One big mystery of weed resistance involves multiple-herbicide resistance (MHR) concomitant to enhanced herbicide metabolism. Previous research unveiled that the overexpression of catalytically promiscuous cytochrome P450s underlies the metabolism-based cross-resistance in multiple species. However, the concept of activation of promiscuous enzymes does not fully accommodate the resistance to diverse herbicides in MHR Echinochloa phyllopogon although the genetic inheritance of MHR was suggested as under a single gene control. Here, we show that the high-level resistance to diclofop-methyl in E. phyllopogon is caused by the simultaneous overexpression of CYP81A12/21, the previously identified promiscuous P450s, and a novel P450 CYP709C69. We found that the MHR line rapidly produced two distinct hydroxylated-diclofop-acid, only one of which was the major metabolite produced by CYP81As. RNA-seq followed by real-time PCR in the crossed progeny of MHR and sensitive lines identified several P450 genes whose overexpressions were associated with MHR. Gene functional characterization revealed that only CYP709C69 conferred diclofop-methyl resistance in rice calli and produced another hydroxylated-diclofop-acid in yeast, reinforcing the relatively low activity of CYP81As to diclofop-methyl. Plants transformed with CYP709C69 had unchanged sensitivity to 46 herbicides except for clomazone, where transgenic plants became more susceptible. The present findings establish a novel concept that simultaneous overexpression of herbicide-metabolizing genes enhances and broadens the profile of metabolic resistance in weeds.

Secondary Metabolites and Eco-Friendly Techniques for Agricultural Weed/Pest Management

In agro-ecosystems, pests (insects, weeds, and other plant’s parasites) compete with crops for edaphic resources, negatively affecting quality and crop yields [...]

Leptochloa mucronata (mucronate sprangletop).

Leptochloa mucronata is a grass native to the warmer parts of North, Central and South America and the Caribbean; taxonomists disagree over whether the form found in the Caribbean is part of the same species or should be classified separately as Leptochloa panicea ssp. brachiata. The species is present in a number of countries in south and south-east Asia, in a few countries in Africa, and in Australia; in most of these countries it is considered to be introduced, although it is reported as native in some of them. Little information is available about how it was spread, but it probably involved the accidental movement of seeds. In parts of both its native range and its introduced range it is a significant agricultural weed, and this is the main reason why it is of interest, although there have been some studies of its use as a green manure.

Lindernia crustacea (Malaysian false pimpernel).

L. crustacea is an herb including in the Global Compendium of Weeds where it is listed as environmental and agricultural weed (Randall, 2012). It has a wide distribution across tropical and subtropical regions of the world where it occurs in a wide range of wetland and some non-wetland habitats and is able to exploit anthropogenic habitats such as rice fields. Once established, this species has the potential to grow forming a mat up to 30 cm high. Currently, L. crustacea is listed as invasive in Hawaii, French Polynesia and Singapore (Wagner, 1999; Chong et al., 2009; Lansdown, 2011).

Improving the Robustness of Object Detection Through a Multi-Camera–Based Fusion Algorithm Using Fuzzy Logic

A single camera creates a bounding box (BB) for the detected object with certain accuracy through a convolutional neural network (CNN). However, a single RGB camera may not be able to capture the actual object within the BB even if the CNN detector accuracy is high for the object. In this research, we present a solution to this limitation through the usage of multiple cameras, projective transformation, and a fuzzy logic–based fusion. The proposed algorithm generates a “confidence score” for each frame to check the trustworthiness of the BB generated by the CNN detector. As a first step toward this solution, we created a two-camera setup to detect objects. Agricultural weed is used as objects to be detected. A CNN detector generates BB for each camera when weed is present. Then a projective transformation is used to project one camera’s image plane to another camera’s image plane. The intersect over union (IOU) overlap of the BB is computed when objects are detected correctly. Four different scenarios are generated based on how far the object is from the multi-camera setup, and IOU overlap is calculated for each scenario (ground truth). When objects are detected correctly and bounding boxes are at correct distance, the IOU overlap value should be close to the ground truth IOU overlap value. On the other hand, the IOU overlap value should differ if BBs are at incorrect positions. Mamdani fuzzy rules are generated using this reasoning, and three different confidence scores (“high,” “ok,” and “low”) are given to each frame based on accuracy and position of BBs. The proposed algorithm was then tested under different conditions to check its validity. The confidence score of the proposed fuzzy system for three different scenarios supports the hypothesis that the multi-camera–based fusion algorithm improved the overall robustness of the detection system.

Mimosa pigra (giant sensitive plant).

M. pigra is a small prickly shrub that infests wetlands and is also an agricultural weed in rice fields in many parts of the old world tropics. In natural wetlands the shrub alters open grasslands into dense thorny thickets and negatively impacts on native biodiversity. It is regarded as one of the worst alien invasive weeds of wetlands of tropical Africa, Asia and Australia, and the cost of control is often high.

Solanum elaeagnifolium (silverleaf nightshade).

S. elaeagnifolium is a deep-rooted summer-growing perennial plant, native to the Americas, but now widely naturalized beyond its native range in extra-tropical regions. It is considered a tenacious weed in many arid to semi-arid places including India, Australia, South Africa, the Pacific Islands, and the USA (Holm et al., 1979; Wagner et al., 1999; Randall, 2012; USDA-ARS, 2014). It is known to be invasive in Cuba (Oviedo-Prieto et al., 2012) and Hawaii (PIER, 2014), a principal weed in India (Holm et al., 1979), and an agricultural weed in Java (Randall, 2012). It has been declared a noxious weed in the U.S. states of Arkansas, California, Idaho, Nevada, and Washington, and an "A" designated weed for quarantine in Oregon and Washington (USDA-NRCS, 2014). The species competes with crops, interferes with livestock, acts as a host for insects and plant diseases, and spreads by forming dense colonies from its extensive root system as well as by propagation of seeds (Boyd et al., 1984; Wagner et al., 1999; EPPO, 2007; PIER, 2014). The species is difficult to control without chemicals (UC Davis Weed Research and Information Center, 2013) and it is essential to keep it out of uncontaminated areas (EPPO, 2007). The species is known to be toxic to cattle, causing damage to intestinal tract and nervous systems and, in severe cases, can cause hallucinations, paralysis, and death (Mas and Lugo-Torres, 2013).