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Proceeding Paper

Comparison of Proximal Remote Sensing Devices of Vegetable Crops to Determine the Role of Grafting in Plant Resistance to Meloidogyne incognita †

by
Yassine Hamdane
1,2,
Adrian Gracia-Romero
1,2,
Ma. Luisa Buchaillot
1,2,
Rut Sanchez-Bragado
1,2,
Aida Magdalena Fullana
3,
Francisco Javier Sorribas
3,
José Luis Araus
1,2 and
Shawn C. Kefauver
1,2,*
1
Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of Biology, University of Barcelona, 08028 Barcelona, Spain
2
AGROTECNIO (Center for Research in Agrotechnology), Av. Rovira Roure 191, 25198 Lleida, Spain
3
Department of Agri-Food Engineering and Biotechnology, Universitat Politècnica de Catalunya, 08860 Castelldefels, Spain
*
Author to whom correspondence should be addressed.
Presented at the 1st International Electronic Conference on Agronomy, 3–17 May 2021; Available online: https://sciforum.net/conference/IECAG2021.
Biol. Life Sci. Forum 2021, 3(1), 61; https://doi.org/10.3390/IECAG2021-09718
Published: 1 May 2021
(This article belongs to the Proceedings of The 1st International Electronic Conference on Agronomy)

Abstract

:
Proximal remote sensing devices are novel tools that enable the study of plant health status through the measurement of specific characteristics, including the color or spectrum of light reflected or transmitted by the leaves or the canopy. Among these, RGB images can provide spatially detailed information about crop status including estimates of biomass, chlorophyll (and chlorosis) and fractional vegetation cover. The aim of this study is to compare the RGB data collected during five years (2016–2020) of four fruiting vegetables (melon, tomato, eggplant and peppers) with trial treatments of non-grafted and grafted onto resistant rootstocks cultivated in a Meloidogyne incognita (a root-knot nematode, RKN) infested soil in a greenhouse. The proximal remote sensing of plant health status data collected were divided into three levels. Firstly, leaf level pigments were measured using two different handheld sensors (SPAD and Dualex). Secondly, canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the Normalized Difference Vegetation Index (NDVI) measured with a portable spectroradiometer (Greenseeker). Thirdly, we assessed plant level water stress, as a consequence of the root damage by nematodes, directly using stomatal conductance measured with a porometer, and indirectly using plant temperature with an infrared thermometer and also the stable carbon and nitrogen isotope composition of leaf dry matter. Among the measured parameters, carbon and nitrogen percentage exhibited the highest positive correlation (r = 0.90), whereas flavonoids and NBI (Nitrogen Balance Index) showed the highest inverse correlation (r = −0.87). It was found that the interaction between treatments and crops (ANOVA) was statistically different for only 4 of 17 parameters (flavonoid (p = 0.002), NBI (p = 0.044), NDVI (p = 0.004) and CSI (RGB-based Crop Senescence Index) (p = 0.002). Concerning the effect of treatments across all crops, differences existed only in two parameters, which were flavonoids (p = 0.003) and CSI (p = 0.001). Grafted plants contained less flavonoids ( x ̄ = 1.37) and showed lower CSI ( x ̄ = 11.65) than non-grafted plants ( x ̄ = 1.98 and x ̄ = 17.28, respectively, p = 0.020 and p = 0.029) when combining all five years and four crops. We conclude that the grafted plants were less stressed and more protected against nematode attack. Leaf flavonoids and the RGB indexes (CSI) were robust indicators of root-knot nematode impacts across multiple crop types.

1. Introduction

Root-knot nematodes (RKNs) are responsible for significant economic losses to a wide variety of crops worldwide [1]. PPNs cause a reduction in crop yield by the direct destruction of root cells, or, indirectly by propagating viruses, or by facilitating the invasion of fungi and bacteria through lesions caused during their penetration into the roots. New techniques have been integrated in agriculture by advancements in precision agriculture and plant phenotyping that allow for rapid and non-destructive assessments of crop health [1]. To better study crop physiological status and nutrient or other management requirements, we should consider more effective and efficient measures such as leaf sensors, proximal or remote sensing instruments. One of these techniques, RGB images, can provide information on the plant nutrient state and general health. This is interpreted from the analysis of RGB images, which effectively capture the whole range of photosynthetically active radiation (PAR) [2]. Hence, RGB image analysis techniques constitute a means for the detailed study of plants with non-destructive instruments. Precision agriculture and plant phenotyping developments have introduced new approaches to agriculture that enable quick and non-destructive analyses of crop health [3]. To more thoroughly research the physiological status and nutrient needs of crops, we advocate the utilization of cutting-edge instruments such as leaf sensors and nearby remote sensing apparatuses. For instance, the chlorophyll content of leaves (measured, for instance, using a mobile device) could be viewed as a reflection of the roots with nematode infestations having a decreased ability to absorb nutrients. Furthermore, the NDVI (Normalized Difference Vegetation Index), which measures the amount of biomass above ground and plant vigor combined), is helpful for determining the vigor of the entire plant and may be a combination of the effects of root injury on nutrition. Chlorophyll, flavanol, and anthocyanin concentrations are evaluated at the level of the individual leaf using sensors such as the Dualex, together with the nitrogen balance index, NBI. All of these indicators can provide a broad overview of the changes in pigment synthesis and the plant’s response to insect attacks. Utilizing stable isotopes that occur naturally, such as carbon and nitrogen, may provide tracking of how plants respond to various growth conditions; using stable isotope data can provide information on the state of the plant [4]; for decades, composition of carbon isotopes (δ13C) has been utilized as a tool for monitoring water plant health and water use efficiency (WUE) in C3 plants due to its natural abundance in plant dry matter [4].
In order to research nitrogen plant dynamics and as a tracer of the past nitrogen sources utilized by the plant, natural variation in the stable nitrogen isotope composition (δ15N) has been used [5]. In this work, total elemental contents, carbon and nitrogen stable signatures, and quick evaluation methods such as non-destructive, proximal, and remote sensing were employed to assess the impact of nematode presence and grafting on several organisms’ physiological conditions, including greenhouse plants and developing horticultural crops. To emphasize the importance of quick assessment of crop growth caused by nematodes, comparisons were made between the growth and physiological state of various crops grafted on nematode-resistant rootstock (RKNs) and those not covered in grafts (non-grafted). In this study, we first summarized some key findings from various studies and collected data related to nematodes and horticultural crops, and then we conducted combined analyses, including comparison and synthesis of five seasons of field data from various crops grown successively in the same greenhouse for five years from 2016 to 2020 with a strong nematode presence.

2. Materials and Methods

2.1. Study Site

The research was carried out between 28 September and 8 October over five successive years from 2016 to 2020 in a semi-open greenhouse located at the experimental station of Agròpolis (of the Escola Superior d’Agricultura of the Universitat Politècnica de Catalunya (ESAB-UPC), in the municipality of Viladecans (Barcelona, Spain). Management of crops was maintained by the technicians of the Agròpolis experimental station following local fertilizer, irrigation and pollination standards designed to ensure favorable growth and productivity apart from the RKNs and root stock study treatments.

2.2. Plant Material and Trial Design

Over the five years of the study, we rotated between four crops with half of cultivation non-grafted and half of plants grafted to nematode resistant rootstock. We used 40 melon (Cucumis melo var. reticulatus) cv. Paloma plots in total in 2016. Each block had five plants, and there were two treatment variables: the first was whether the plants were non-grafted or grafted onto the Cucumis metuliferus rootstock, and the second had three levels of nematode infection. So, for a total of six treatments, we had two crop treatments (grafted or non-grafted) for each of the control, low, and high infection groups. For the grafted and non-grafted control, there were 10 plots in total for each treatment. For the 2017 experiment, which involved growing melon (Cucumis melo var. reticulatus) and tomato plants (Solanum lycopersicum cv. Durinta), there were a total of 80 sample plots, divided into 40 melon plots and 40 tomato plots. The 40 plots of each species were divided into six treatments: non-grafted, grafted onto the rootstock “Alligator” for tomatoes, grafted onto the Cucumis metuliferus for melons, and non-grafted (control, low, high infection by nematode). For each treatment, there were five plot repeats for control, ten for grafted, and ten for non-grafted. In 2018, when we only tested the eggplant (Solanum melongena cv. Cristal), the 20 sample plots were separated into four blocks, each of which had five plants. Non-grafted eggplants were positioned in front of and around the block. For both crop lines, 10 non-grafted Solanum torvum ‘Brutus’ eggplants were grafted onto it and a total of 10 grafted eggplants. In 2019, 40 sample plots of pepper plants (Capsicum annuum cv. Tinsena) were divided into four lines, each having one treatment. Each treatment included 20 repetitions because there were ten treatments per line. Pepper plants were grafted onto pepper rootstock “Oscos” or left ungrafted in the treatments. A total of 40 sample plots were divided into four tomato (Solanum lycopersicum) lines, with the year 2020 serving as the end date. Then, two lines of tomato cv. Durinta and the remaining lines of tomato cv. Caramba were grown. We registered a total of 20 susceptible and 20 resistant tomato plots, showing the effects on plant performance.

2.3. Measurements and Sampling Methods

For the measurement of pigments, we used two handheld sensors (SPAD 502 and Dualex). The first tool determines the relative chlorophyll concentration by measuring the leaf absorbance in red and near-infrared regions (Spectrum Technologies Inc., Plainfield, IL, USA) [2], whereas the second measures the chlorophyll content of leaves using a transmittance ratio at two different wavelengths. The Dualex (Dualex, Orsay, France) furthermore also measures leaf flavonoid and anthocyanin content by a ratio of chlorophyll fluorescence and the chlorophyll to polyphenol ratio, known as the NBI [6].
In order to inform about plant health and vigor, some canopy level parameters were also measured, where firstly we used the Trimble Greenseeker handheld crop sensor (Trimble, Sunnyvale, CA, USA), which provides Normalized Differenced Vegetation Index (NDVI) values. Then, we performed the analyses of RGB images taken by Panasonic Lumix DMC-GX7 (Panasonic, Osaka, Japan) 16 MP camera in order to detect the percentages of yellow-green and green pixels as Green Area (GA), Green Greener Area (GGA), Normalized Green Red Difference Index (NGRDI), Triangular Greenness Index (TGI), and Crop Senescence Index (CSI), calculated using the CerealScanner plugin for FIJI (http://gitlab.com/sckefauver/cerealscanner; FIJI is just ImageJ, http://fiji.net, accessed 22 July 2022). Below are the equations of the different parameters, where R represents the reflectance at the indicated approximate wavelength (Equations (1) [7], (2) [8], (3) [9]).
TGI = −0.5 [190(R670 − R550) − 120(R670 − R480)].
NGRDI = (R550 − R670)/(R550 + R670).
CSI = 100 × (GA − GGA)/GA.
Stomatal conductance was measured using a porometer (Decagon Leaf Porometer SC-1) [10], plant temperature using a Raytek PhotoTemp TM XMXSTM TD infrared thermometer (Raytek, Santa Cruz, CA USA, Ref. [11]) and analysis was performed for both C and N stable isotopes in leaf dry matter. Briefly, the scientific protocol followed was the following: dry leaves were ground to a fine powder and 0.7–0.9 mg of leaf dry matter from each plot was weighed and sealed into tin capsules and sent for analyses. Stable carbon (δ13C) and nitrogen (δ15N) isotope ratios as well as the leaf N and C concentrations (%) were measured using an elemental analyzer (Flash 1112 EA; Thermo Finnigan, Bremen, Germany) coupled with an isotope ratio mass spectrometer (Delta C IRMS, Thermo Finnigan) operating in a continuous flow mode. Samples were loaded into a sampler and analyzed by technical services staff. From these measurements, we assessed the level water stress experienced by the plant and indirectly the root health (see Table 1 for more details).

2.4. Statistical Processing

Statistical treatment was performed using Statgraphics Centurion XVI (Developed by Statpoint Technologies, Warrenton, VA, USA) for basic data analyses such as mean and standard error and ANOVA. Correlation between differences was performed by MS Office Excel 2007 (developed by Microsoft, Redmond Washington, DC, USA). Finally, the graphics were obtained using Sigma Plot 12.5 (Statistical software developed by Systat software, Chicago, IL, USA).

3. Results

Figure 1, divided in 4 parts, presents an overview of the findings and shows how indices and pigments varied between the various treatments.
A comprehensive overview of the RGB-based CSI variants is shown in Figure 1a. This index, which can be affected by a number of factors including the field of view of the RGB camera, indicates the degree of senescence in the plant. It is possible to discern changes in CSI between the two treatments in the various crops; however, in 2017 this difference entirely disappeared. While grafted plants were more valuable than non-grafted ones for pepper and eggplant, the tomato crop showed the most highly significant differences in CSI, with the opposite being true for combination years and in 2020. Despite the possibility that nematode attack accelerates plant senescence, other elements, such as measurement stage, viewing angles, and climatic conditions can also impact.
The variation in TGI values based on RGB photos as a representation of the crop’s photosynthetically active chlorophyll content is shown in Figure 1b. When the grafted treatment was selected, there were noticeable variations between the two treatments in melon and tomatoes. Grafted plants have increased TGI, which was used as a metric of crop vigor.
Figure 1c displays the change in NBI data obtained from the Dualex leaf level sensor. This graph only shows one notable change: the grafted eggplant values fared better than the non-grafted eggplant values. Indirectly indicating the strength and capacity of the crop’s roots for assimilation is the plant’s level of nitrogen balance, which can provide information about how rapidly nitrogen is assimilated by the plant.
The variance in Flav levels between the treatments is depicted in Figure 1d. The Flav values of non-grafted pepper plants were found to be greater than those of grafted plants in 2017, and the same was seen for melon. Several of the most important stress indicators showed higher values in plants, including higher flavonoid production, as stress levels grew. In contrast, Flav saw greater readings in the non-grafted plants, a symptom of increasing stress. Crop comparisons between the treatments (grafted vs. non-grafted) were not taken into account because each species possessed physiological and biological characteristics that would significantly affect the measurement, especially for canopy proximal remote sensing techniques that are influenced by canopy features such as the RGB index TGI.

4. Discussion

A viable non-chemical method to control RKN populations and lessen yield losses in the most vulnerable cucurbit crops is grafting onto resistant-tolerant rootstocks. Several authors have previously examined findings that are comparable to those made in this study, touching on the subject in regard to related species and the effect of nematodes on crop health. Plant resistance has been identified as an efficient and profitable control strategy to lower equilibrium density and RKN reproduction rate [13]. Due to the bigger root systems and better disease tolerance, the grafting procedure has been shown to increase water and nutrient intake [14].
The various metrics that may be retrieved from RGB images, such as TGI and CSI, as well as other direct sensor measures, such as the NDVI, can be used to assess the general development and health of plants, as well as, conversely, the delayed onset of agricultural senescence [15]. These methods are non-destructive tools that quickly offer highly pertinent information on plant physiological state and efficiently quantify how grafted plants gain from resistant root stocks in a variety of ways. They also show fewer symptoms of nutrient or water stress as a sign of an overall improvement in root system function, which is reflected in both vegetative vigor and total yields at the end-of-life crop cycle [16].
Similarly, leaf senescence, which is thought to be the final phase of leaf development, might act as a sign that the biological processes involved in a plant’s life cycle are accelerating. Longer reproductive phases and higher yields are common outcomes of longer crop cycles [17]. Senescence can result from highly controlled alterations at the molecular, cellular, biochemical, and physiological levels that can be accelerated by biotic or abiotic causes including pathogen attack (here considering nematodes). Because of its vulnerability to Meloidogyne, the non-grafted tomato crop showed the highest values of CSI. Crop stress brought on by RKN expedites the process of senescence and reduces the life cycle of plants, which often results in a decrease in crop production.
For plants to grow and produce, they need nutrition. The ability of crop roots to absorb nitrogen and other important macronutrients that promote the formation of chlorophyll and other crucial plant activities is crucial. When compared across several years, grafted plants consistently recorded the highest NBI levels measured by the Dualex sensor. NBI is a measure of how well-balanced leaf N is with other crucial macronutrients and, consequently, how well it can support plant functions, particularly photosynthesis. In contrast to Silva-Sanchez et al.’s [18] examination of just one year of the same data, which supported the use of whole canopy measurements over leaf measurements, greater NBI supported estimates of improved yield when compared over many years and crop kinds.
Flavanoid concentration is a different parameter obtained by the Dualex leaf sensor. Jasmonic acid, salicylic acid, ethylene, auxin, and ROS crosstalk, likely activated when the PPNs cause mechanical damage and injury during feeding and penetration, might induce flavonoid biosynthesis pathways in the plant. The greater levels of Flav seen in non-grafted plants are a result of stress signaling and are an indication that critical processes are being compromised. Grafting may be able to mitigate these effects by limiting RKN infection [19].
Other soil-borne diseases including bacterial wilt (produced by Ralstonia solanacearum) and fusarium wilt (induced by Fusarium oxysporum fs. lycopersici) are also successfully controlled by grafting [20]. However, accessions of wild Cucumis spp., including C. africanus, C. anguria, C. ficifolius, C. metuliferus, C. myriocarpus, C. postulatus, and C. subsericeus, have been reported to be resistant to RKN. Grafting susceptible scions onto nematode-resistant rootstocks is one way to treat nematode infections in melons [21]. When melon plants were grafted onto various Cucurbita rootstocks, a higher fruit yield was obtained as a result of grafting [22]. This could have happened due to a variety of circumstances, such as an increase in water and nutrient absorption brought on by the larger root.

5. Conclusions

According to all the results obtained over four successive years, we note that grafting techniques constitute a means of protection against attack by RKNs. This is seen in the majority of cases studied by the values of physiological parameters (NBI, CSI, and TGI) of grafted plants, which indicate better crop health than that of non-grafted plants. These limited results indicate good functioning of the plant physiological defense processes in the grafted plants compared to that of the non-grafted, which suffered from the intensity of attacks by nematodes through the limited uptake of key resources and the increased activation of defense mechanisms. Grafting has been previously observed to be more effective on some crops and is potentially linked to the compatibility between the rootstock and graft and quality of benefits obtained from the rootstock. Some root stocks are more effective than others and bring more benefits to the plant, which affects growth and final production in addition to resistance to pests. Our study also supports the role of RGB images as a nondestructive and low-cost technique that ensures a detailed diagnosis of plant physiological status. RGB image analyses are being used more and more in agricultural studies, on the one hand to save time, but also to more effectively monitor crop status in order to ensure the best possible conditions for development and subsequently optimize production. Taking into account climate change, resistant root grafting may reduce the damage caused by RKNs, but may also necessitate the development of new more effective rootstocks, adapted not only to the biotic soil factors but also to changing environmental conditions. New resistant root stock breeding efforts may be supported by genetic engineering to improve rootstocks with a more favorable adaptation to global change.

Author Contributions

Conceptualization, Y.H. and S.C.K.; methodology, Y.H., S.C.K., A.M.F. and F.J.S.; software, S.C.K.; validation, Y.H., M.L.B., A.G.-R., R.S.-B., A.M.F. and F.J.S.; formal analysis, Y.H.; investigation, Y.H., M.L.B., A.G.-R., R.S.-B., A.M.F. and F.J.S.; resources, S.C.K. and J.L.A.; data curation, Y.H., M.L.B., A.G.-R., R.S.-B., A.M.F.; writing—original draft preparation, Y.H.; writing—review and editing, S.C.K., F.J.S. and J.L.A.; visualization, Y.H.; supervision, S.C.K. and J.L.A.; project administration, S.C.K., F.J.S., J.L.A.; funding acquisition, S.C.K., F.J.S. All authors have read and agreed to the published version of the manuscript.

Funding

Y.H. acknowledges the support of the Tunisian government from the Ministery of Higher Education and Scientific Research. J.L.A. acknowledges support from the Institució Catalana d’Investigació i Estudis Avançats (ICREA) Academia, Generalitat de Catalunya, Spain. S.C.K. is supported by the Ramon y Cajal RYC-2019-027818-I research fellowship from the Ministerio de Ciencia e Innovación, Spain. Thanks are also given to the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (FEDER) for funding the project AGL2013-49040-C2-1-R and to the Ministry of Science and Innovation from the Spanish Government for funding the AGL2017-89785-R, and to the European Regional Development Fund (FEDER) AGL2017-89785-R, and for providing the FPI grant PRE2018-084265 to A.M.F. This research was also supported by the COST Action CA17134 SENSECO (Optical synergies for spatiotemporal sensing of scalable ecophysiological traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu accessed on 29 April 2022).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No data reported.

Acknowledgments

The authors thank Picó and Gisbert from COMAV-UPV, for providing seeds of C. metuliferus accession BGV11135; Semillas Fitó for providing the melon cv. Paloma seeds; and Hishtil GS nurseries for providing the grafted plants. The authors are also grateful to Sheila Alcalá, Maria Julià, Sergi García, Miquel Masip, Helio Adán García-Mendívil and Alejandro Expósito for technical assistance.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Variation of (a) RGB based Crop Senescence Index (CSI), (b) Triangular Greenness Index (TGI), (c) Nitrogen Balance Index (NBI) and (d) Flavonoid (Flav) values between two treatments (grafted, non-grafted) for four crops (melon, tomato, eggplant, and pepper) during five years of experiments (2016–2020). For melon, we present both the combined and separate analyses for 2016 and 2017. Concerning the tomato crop, combined years and 2017 and 2020 are shown. The eggplant crop was studied for just one year (2018) as well as pepper (2019). NS: non-significant (p > 0.05), *: weakly significant (p < 0.05), **: significant (p < 0.01), ***: highly significant (p < 0.001).
Figure 1. Variation of (a) RGB based Crop Senescence Index (CSI), (b) Triangular Greenness Index (TGI), (c) Nitrogen Balance Index (NBI) and (d) Flavonoid (Flav) values between two treatments (grafted, non-grafted) for four crops (melon, tomato, eggplant, and pepper) during five years of experiments (2016–2020). For melon, we present both the combined and separate analyses for 2016 and 2017. Concerning the tomato crop, combined years and 2017 and 2020 are shown. The eggplant crop was studied for just one year (2018) as well as pepper (2019). NS: non-significant (p > 0.05), *: weakly significant (p < 0.05), **: significant (p < 0.01), ***: highly significant (p < 0.001).
Blsf 03 00061 g001aBlsf 03 00061 g001b
Table 1. The main tool used in the experiment to take measurements.
Table 1. The main tool used in the experiment to take measurements.
InstrumentImage and Citation
SPAD 502 Blsf 03 00061 i001 [12].
Dualex Blsf 03 00061 i002 [6].
Trimble Greenseeker Blsf 03 00061 i003 [2].
Decagon Leaf Porometer Blsf 03 00061 i004 [10].
Raytek PhotoTemp TM XMXSTM TD infrared thermometer Blsf 03 00061 i005 [11].
Panasonic Lumix DMC-GX7 Blsf 03 00061 i006 [7].
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Hamdane, Y.; Gracia-Romero, A.; Buchaillot, M.L.; Sanchez-Bragado, R.; Fullana, A.M.; Sorribas, F.J.; Araus, J.L.; Kefauver, S.C. Comparison of Proximal Remote Sensing Devices of Vegetable Crops to Determine the Role of Grafting in Plant Resistance to Meloidogyne incognita. Biol. Life Sci. Forum 2021, 3, 61. https://doi.org/10.3390/IECAG2021-09718

AMA Style

Hamdane Y, Gracia-Romero A, Buchaillot ML, Sanchez-Bragado R, Fullana AM, Sorribas FJ, Araus JL, Kefauver SC. Comparison of Proximal Remote Sensing Devices of Vegetable Crops to Determine the Role of Grafting in Plant Resistance to Meloidogyne incognita. Biology and Life Sciences Forum. 2021; 3(1):61. https://doi.org/10.3390/IECAG2021-09718

Chicago/Turabian Style

Hamdane, Yassine, Adrian Gracia-Romero, Ma. Luisa Buchaillot, Rut Sanchez-Bragado, Aida Magdalena Fullana, Francisco Javier Sorribas, José Luis Araus, and Shawn C. Kefauver. 2021. "Comparison of Proximal Remote Sensing Devices of Vegetable Crops to Determine the Role of Grafting in Plant Resistance to Meloidogyne incognita" Biology and Life Sciences Forum 3, no. 1: 61. https://doi.org/10.3390/IECAG2021-09718

APA Style

Hamdane, Y., Gracia-Romero, A., Buchaillot, M. L., Sanchez-Bragado, R., Fullana, A. M., Sorribas, F. J., Araus, J. L., & Kefauver, S. C. (2021). Comparison of Proximal Remote Sensing Devices of Vegetable Crops to Determine the Role of Grafting in Plant Resistance to Meloidogyne incognita. Biology and Life Sciences Forum, 3(1), 61. https://doi.org/10.3390/IECAG2021-09718

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