A new method for in-situ monitoring of the underground development of Orobanche cumana in sunflower (Helianthus annuus) with a mini-rhizotron

Recent trends in root phenomics of plant systems with available methods- discrepancies and consonances

The phenotyping of plant roots is a challenging task and poses a major lacuna in plant root research. Roots rhizospheric zone is affected by several environmental cues among which salinity, drought, heavy metal and soil pH are key players. Among biological factors, fungal, nematode and bacterial interactions with roots are vital for improving nutrient uptake efficiency in plants. The subterranean nature of a plant root and the limited number of approaches for root phenotyping offers a great challenge to the plant breeders to select a desirable root trait under different stress conditions. Identification of key root traits can provide a basic understanding for generating crop plants with enhanced ability to withstand various biotic or abiotic stresses. For instance, crops with improved soil exploration potential, phosphate uptake efficiency, water use efficiency and others. Laboratory methods such as hydroponics, rhizotron, rhizoslide and luminescence observatory for roots do not provide precise and desired root quantification attributes. Though 3D imaging by X-ray computed tomography (X-ray-CT) and magnetic resonance imaging techniques are complex, however, it provides the most applicable and practically relevant data for quantifying root system architecture traits. This review outlines the current developments in root studies including recent approaches viz. X-ray-CT, MRI, thermal infrared imaging and minirhizotron. Although root phenotyping is a laborious procedure, it offers multiple advantages by removing discrepancies and providing the actual practical significance of plant roots for breeding programs.

SoilCam: A Fully Automated Minirhizotron using Multispectral Imaging for Root Activity Monitoring

A minirhizotron is an in situ root imaging system that captures components of root system architecture dynamics over time. Commercial minirhizotrons are expensive, limited to white-light imaging, and often need human intervention. The implementation of a minirhizotron needs to be low cost, automated, and customizable to be effective and widely adopted. We present a newly designed root imaging system called SoilCam that addresses the above mentioned limitations. The imaging system is multi-modal, i.e., it supports both conventional white-light and multispectral imaging, with fully automated operations for long-term in-situ monitoring using wireless control and access. The system is capable of taking 360° images covering the entire area surrounding the tube. The image sensor can be customized depending on the spectral imaging requirements. The maximum achievable image quality of the system is 8 MP (Mega Pixel)/picture, which is equivalent to a 2500 DPI (dots per inch) image resolution. The length of time in the field can be extended with a rechargeable battery and solar panel connectivity. Offline image-processing software, with several image enhancement algorithms to eliminate motion blur and geometric distortion and to reconstruct the 360° panoramic view, is also presented. The system is tested in the field by imaging canola roots to show the performance advantages over commercial systems.

3-D Image-Driven Morphological Crop Analysis: A Novel Method for Detection of Sunflower Broomrape Initial Subsoil Parasitism

Effective control of the parasitic weed sunflower broomrape (Orobanche cumana Wallr.) can be achieved by herbicides application in early parasitism stages. However, the growing environmental concerns associated with herbicide treatments have motivated the adoption of precise chemical control approaches that detect and treat infested areas exclusively. The main challenge in developing such control practices for O. cumana lies in the fact that most of its life-cycle occurs in the soil sub-surface and by the time shoots emerge and become observable, the damage to the crop is irreversible. This paper approaches early O. cumana detection by hypothesizing that its parasitism already impacts the host plant morphology at the sub-soil surface developmental stage. To validate this hypothesis, O. cumana- infested sunflower and non-infested control plants were grown in pots and imaged weekly over 45-day period. Three-dimensional plant models were reconstructed using image-based multi-view stereo followed by derivation of their morphological parameters, down to the organ-level. Among the parameters estimated, height and first internode length were the earliest definitive indicators of infection. Furthermore, the detection timing of both parameters was early enough for herbicide post-emergence application. Considering the fact that 3-D morphological modeling is nondestructive, is based on commercially available RGB sensors and can be used under natural illumination; this approach holds potential contribution for site specific pre-emergence managements of parasitic weeds and as a phenotyping tool in O. cumana resistant sunflower breeding projects.

Control of Egyptian Broomrape in Processing Tomato: A Summary of 20 Years of Research and Successful Implementation

The obligate root parasitic weeds commonly known as broomrape (Orobanche and Phelipanche spp.) cause severe damage to vegetable and field crops worldwide. Efficient control of these parasites is difficult due to their development and attachment to the host plant (via a specialized organ, the haustorium) under the soil surface and to their unique biological traits of massive seed production, facile seed dispersal, germination only under specific conditions, and seed longevity. The major damage inflicted by the parasites takes place underground, making control extremely challenging. Egyptian broomrape (Phelipanche aegyptiaca) is a devastating pest in the Mediterranean basin, parasitizing a wide host crop range, including tomato, sunflower, legumes, and carrot, resulting in severe crop losses. Twenty years of research have led to the development of integrated smart management strategies for combating this parasite in processing tomato fields. In particular, an explicit decision support system (DSS) designated PICKIT has been developed; this DSS is based on predicting parasitism dynamics and employing a range of selective targeted chemical applications (preplanting incorporation, foliar application, and herbigation). In this feature article, we describe the evolution of this research from the laboratory, through greenhouse and experimental field trials, to large scale commercial fields and the successful assimilation of PICKIT into agricultural practice. The use of PICKIT in fields of processing tomatoes in northern Israel has led to effective control of Egyptian broomrape, even in fields with high infestation levels, resulting in a tomato yield increase of an average of 40 tons ha^-1 compared with nontreated plots. In 2016, PICKIT was commercially implemented in 33 fields, totaling 400 ha, giving 95% Egyptian broomrape control and tomato yields of 115 to 145 tons ha^-1. The outcome of this research is now enabling farmers to grow tomatoes in Egyptian broomrape-infested fields with assured increased yields and hence high profits.

The Effect of Orobanche crenata Infection Severity in Faba Bean, Field Pea, and Grass Pea Productivity

Broomrape weeds (Orobanche and Phelipanche spp.) are root holoparasites that feed off a wide range of important crops. Among them, Orobanche crenata attacks legumes complicating their inclusion in cropping systems along the Mediterranean area and West Asia. The detrimental effect of broomrape parasitism in crop yield can reach up to 100% depending on infection severity and the broomrape-crop association. This work provides field data of the consequences of O. crenata infection severity in three legume crops, i.e., faba bean, field pea, and grass pea. Regression functions modeled productivity losses and revealed trends in dry matter allocation in relation to infection severity. The host species differentially limits parasitic sink strength indicating different levels of broomrape tolerance at equivalent infection severities. Reductions in host aboveground biomass were observed starting at low infection severity and half maximal inhibitory performance was predicted as 4.5, 8.2, and 1.5 parasites per faba bean, field pea, and grass pea plant, respectively. Reductions in host biomass occurred in both vegetative and reproductive organs, the latter resulting more affected. The increase of resources allocated within the parasite was concomitant to reduction of host seed yield indicating that parasite growth and host reproduction compete directly for resources within a host plant. However, the parasitic sink activity does not fully explain the total host biomass reduction because combined biomass of host-parasite complex was lower than the biomass of uninfected plants. In grass pea, the seed yield was negligible at severities higher than four parasites per plant. In contrast, faba bean and field pea sustained low but significant seed production at the highest infection severity. Data on seed yield and seed number indicated that the sensitivity of field pea to O. crenata limited the production of grain yield by reducing seed number but maintaining seed size. In contrast, the size of individual parasites was not genetically determined but dependent on the host species and resource availability as a consequence of competition between parasites at increasing infection severities.

Thermal Time Model for Egyptian Broomrape (Phelipanche aegyptiaca) Parasitism Dynamics in Carrot (Daucus carota L.): Field Validation

Carrot, a highly profitable crop in Israel, is severely damaged by Phelipanche aegyptiaca parasitism. Herbicides can effectively control the parasite and prevent damage, but for optimal results, knowledge about the soil-subsurface phenological stage of the parasite is essential. Parasitism dynamics models have been successfully developed for the parasites P. aegyptiaca, Orobanche cumana, and Orobanche minor in the summer crops, tomato, sunflower, and red clover, respectively. However, these models, which are based on a linear relationship between thermal time and the parasitism dynamics, may not necessarily be directly applicable to the P. aegyptiaca-carrot system. The objective of the current study was to develop a thermal time model to predict the effect of P. aegyptiaca parasitism dynamics on carrot growth. For development and validation of the models, data was collected from a temperature-controlled growth experiment and from 13 plots naturally infested with P. aegyptiaca in commercial carrot fields. Our results revealed that P. aegyptiaca development is related to soil temperature. Moreover, unlike P. aegyptiaca parasitism in sunflower and tomato, which could be predicted both a linear model, P. aegyptiaca parasitism dynamics on carrot roots required a nonlinear model, due to the wider range of growth temperatures of both the carrot and the parasite. Hence, two different nonlinear models were developed for optimizing the prediction of P. aegyptiaca parasitism dynamics. Both models, a beta function model and combined model composed of a beta function and a sigmoid curve, were able to predict first P. aegyptiaca attachment. However, overall P. aegyptiaca dynamics was described more accurately by the combined model (RMSE = 14.58 and 10.79, respectively). The results of this study will complement previous studies on P. aegyptiaca management by herbicides to facilitate optimal carrot growth and handling in fields infested with P. aegyptiaca.