A Cost-effective Multispectral Sensor System for Leaf-Level Physiological Traits

With the concern of the global population to reach 9 billion by 2050, ensuring global food security is a prime challenge for the research community. One potential way to tackle this challenge is sustainable intensification; making plant phenotyping a high throughput may go a long way in this respect. Among several other plant phenotyping schemes, leaf-level plant phenotyping needs to be implemented on a large scale using existing technologies. Leaf-level chemical traits, especially macronutrients and water content are important indicators to determine crop’s health. Leaf nitrogen (N) level, is one of the critical macronutrients that carries a lot of worthwhile nutrient information for classifying the plant’s health. Hence, the non-invasive leaf’s N measurement is an innovative technique for monitoring the plant’s health. Several techniques have tried to establish a correlation between the leaf’s chlorophyll content and the N level. However, a recent study showed that the correlation between chlorophyll content and leaf’s N level is profoundly affected by environmental factors. Moreover, it is also mentioned that when the N fertilization is high, chlorophyll becomes saturated. As a result, determining the high levels of N in plants becomes difficult. Moreover, plants need an optimum level of phosphorus (P) for their healthy growth. However, the existing leaf-level P status monitoring methods are expensive, limiting their deployment for the farmers of low resourceful countries. The aim of this thesis is to develop a low-cost, portable, lightweight, multifunctional, and quick-read multispectral sensor system to sense N, P, and water in leaves non-invasively. The proposed system has been developed based on two reflectance-based multispectral sensors (visible and near-infrared (NIR)). In addition, the proposed device can capture the reflectance data at 12 different wavelengths (six for each sensor). By deploying state of the art machine learning algorithms, the spectroscopic information is modeled and validated to predict that nutrient status. A total of five experiments were conducted including four on the greenhouse-controlled environment and one in the field. Within these five, three experiments were dedicated for N sensing, one for water estimation, and one for P status determination. In the first experiment, spectral data were collected from 87 leaves of canola plants, subjected to varying levels of N fertilization. The second experiment was performed on 1008 leaves from 42 canola cultivars, which were subjected to low and high N levels, used in the field experiment. The K-Nearest Neighbors (KNN) algorithm was employed to model the reflectance data. The trained model shows an average accuracy of 88.4% on the test set for the first experiment and 79.2% for the second experiment. In the third and fourth experiments, spectral data were collected from 121 leaves for N and 186 for water experiments respectively; and Rational Quadratic Gaussian Process Regression (GPR) algorithm is applied to correlate the reflectance data with actual N and water content. By performing 5-fold cross-validation, the N estimation shows a coefficient of determination (R^2) of 63.91% for canola, 80.05% for corn, 82.29% for soybean, and 63.21% for wheat. For water content estimation, canola shows an R^2 of 18.02%, corn of 68.41%, soybean of 46.38%, and wheat of 64.58%. Finally, the fifth experiment was conducted on 267 leaf samples subjected to four levels of P treatments, and KNN exhibits the best accuracy, on the test set, of about 71.2%, 73.5%, and 67.7% for corn, soybean, and wheat, respectively. Overall, the result concludes that the proposed cost-effective sensing system can be viable in determining leaf N and P status/content. However, further investigation is needed to improve the water estimation results using the proposed device. Moreover, the utility of the device to estimate other nutrients as well as other crops has great potential for future research

Modern Seed Technology

Satisfying the increasing number of consumer demands for high-quality seeds with enhanced performance is one of the most imperative challenges of modern agriculture. In this view, it is essential to remember that the seed quality of crops does not improve

Development of Multifunctional Electrical Impedance Spectroscopy System for Characterization in Plant Phenotyping

Plant phenotyping plays an important role for the thorough assessment of plant traits such as growth, development, resistance, physiology, etc. Assessing the nutrients and water contents by obtaining the spectroscopy data is essential for plant characterization, and photosynthesis. The conventional optical methods like visible/near-infrared spectroscopy, hyperspectral or multispectral imaging, and optical tomography have been developed and studied for the assessment of plant nutrition status and water stress. Although there are several advantages of these methods, they have some limitations as to their environmental sensitivity and confounding factors (i.e., light intensity, and color). These methods require large data storage capacity which makes the system expensive, and heavier in weight. In addition, most of these methods are not useful for in situ and rapid measurements. To overcome these limitations a multifrequency electrical measurement method such as electrical impedance spectroscopy (EIS) has been investigated which is found less sensitive to the environmental variables. The physical and chemical changes of the plants can be accurately described by EIS parameters like impedance, resistance, or capacitance. The measurement using EIS is found non-destructive, inexpensive, in situ, and rapid which could be an attractive alternative to the optical methods. An accurate impedance spectroscopy modeling for the characterization of the plants using a multifunctional spectroscopy system is still desired which can overcome the shortcomings of the existing methods. This research work deals with the development of a multifunctional EIS system to increase the robustness in applications for assessing the leaf nitrogen status, leaf water stress, root growth, and root biomass of the plants, and detecting the plant-like organisms such as algae species by measuring impedances in multiple frequencies. The overall research work is divided into three phases. In the first phase, we developed new EIS models for the determination of plant leaf nitrogen concentrations by measuring leaf impedances in the vegetative growth stage. The models were evaluated by the regression analysis in multiple frequencies. EIS sensor is found highly accurate in determining the plant leaf nitrogen status compared to soil plant analysis development (SPAD), and the method using EIS sensor is found cost-effective. In addition, we developed other new EIS models for determining the leaf water contents under different water stress conditions of the plants rapidly and efficiently. Regression analysis was performed, and the models were optimized and evaluated with the measured leaf impedances in multiple frequencies. The EIS sensor is found a low-cost and effective tool in determining the crop leaf water status compared to the other conventional approaches. In the second phase, we investigated whether the EIS sensor can be used to determine the algae species in water. The photosynthetic pigments like Chlorophyll-a concentrations were estimated by measuring impedances of the algae species and the corresponding EIS characteristics were obtained to detect the species. New EIS models were developed and validated with less error by performing regression analysis in multiple frequencies. The models were found accurate, and suitable for the estimation performance. A rapid performance of the sensor is found for measuring Chlorophyll-a as an alternative to the conventional approaches. In the third phase, we investigated whether the developed EIS system can be used for obtaining three-dimensional (3D) images of plant roots. An in situ and rapid electrical impedance tomography (EIT) data acquisition system was developed based on EIS for the further experiments in imaging and assessing the growth of the plant roots. Multifrequency impedance imaging technique was utilized, and the samples were reconstructed with finite element method (FEM) modeling which was carried out using electrical impedance and diffuse optical tomography reconstruction software (EIDORS) in MATLAB. At first, a low-cost, and high-precision EIT system was developed by designing a portable sensor with two layers of electrode array in a cylindrical domain. Different edible plant slices of carrot, radish, and potato along with multiple plant roots were taken in the EIT domain to assess and calibrate the system and their images were reconstructed by mapping conductivity in two-dimensional (2D) and three-dimensional (3D) planes. Later, a novel, dynamic, and adjustable EIT sensor system with three layers of electrode array was designed for developing a portable, cost-effective, and high-speed EIT data acquisition system. A non-invasive 3D imaging of multiple plant roots was made in both water and soil media. A non-destructive evaluation of biomass estimation of tap roots was carried out by measuring impedances using the designed EIT sensor system. A good correlation was found between the biomass and measured impedances of tap roots, and the estimated models for biomass were validated with less error. The developed EIT system is found suitable for in situ measurements and capable of monitoring the growth and estimating the biomass of plant roots. In overall, the estimated results from the measurements using the developed EIS/EIT system were found highly correlated with the ground truth measurements. Therefore, the developed multifunctional EIS system can be used as a low-cost, and effective tool for rapid and in-situ measurements for the characterization in plant phenotyping

Robotic Technologies for High-Throughput Plant Phenotyping: Contemporary Reviews and Future Perspectives

Phenotyping plants is an essential component of any effort to develop new crop varieties. As plant breeders seek to increase crop productivity and produce more food for the future, the amount of phenotype information they require will also increase. Traditional plant phenotyping relying on manual measurement is laborious, time-consuming, error-prone, and costly. Plant phenotyping robots have emerged as a high-throughput technology to measure morphological, chemical and physiological properties of large number of plants. Several robotic systems have been developed to fulfill different phenotyping missions. In particular, robotic phenotyping has the potential to enable efficient monitoring of changes in plant traits over time in both controlled environments and in the field. The operation of these robots can be challenging as a result of the dynamic nature of plants and the agricultural environments. Here we discuss developments in phenotyping robots, and the challenges which have been overcome and others which remain outstanding. In addition, some perspective applications of the phenotyping robots are also presented. We optimistically anticipate that autonomous and robotic systems will make great leaps forward in the next 10 years to advance the plant phenotyping research into a new era

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production

Remote Sensing for Precision Nitrogen Management

This book focuses on the fundamental and applied research of the non-destructive estimation and diagnosis of crop leaf and plant nitrogen status and in-season nitrogen management strategies based on leaf sensors, proximal canopy sensors, unmanned aerial vehicle remote sensing, manned aerial remote sensing and satellite remote sensing technologies. Statistical and machine learning methods are used to predict plant-nitrogen-related parameters with sensor data or sensor data together with soil, landscape, weather and/or management information. Different sensing technologies or different modelling approaches are compared and evaluated. Strategies are developed to use crop sensing data for in-season nitrogen recommendations to improve nitrogen use efficiency and protect the environment

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production

Rediscovering pepper, eggplant and lettuce landraces of the Valencian Community; an ancient resource with vast potential for the future

Tesis por compendio[ES] La erosión genética provocada en los cultivos al primar producción sobre calidad ha derivado en pérdida de biodiversidad, lo que compromete la seguridad alimentaria mundial. Los agricultores, a través de un proceso histórico de selección, han ido diferenciando variedades tradicionales de cultivo que sonfuente de biodiversidad agrícola que además favorece el desarrollo de la economía local. Por este motivo, su recuperación, clasificación y cultivo son clave para la economía y futuro alimentario. La conservación de las variedades tradicionales requiere un conocimiento de las mismas a través de la descripción detallada de las características fenotípicas, agronómicas, y de calidad nutricional como valor añadido. La Comunitat Valenciana, cuenta con un extenso patrimonio hortícola constituido por una gran diversidad de variedades tradicionales de hortalizas. Estas son fruto de la adaptación a variadas condiciones agroclimáticas de la geografía valenciana, por un lado, y de la selección aplicada por los agricultores en cada localidad por otro. En este sentido, estas variedades tienen un gran valor como patrimonio etnobotánico y como tal deberían ser conservadas. Asimismo, en la actualidad, el cultivo y el consumo de las variedades tradicionales están creciendo, ya que son especialmente atractivas para los consumidores por su diversidad y su alta calidad nutracéutica. En este contexto, esta tesis doctoral se basa en la caracterización fenotípica y nutricional para valorizar las variedades tradicionales de la comunidad, correspondientes a los cultivos de pimiento, berenjena y lechuga, con la finalidad de promover su conservación y cultivo en las zonas de origen, e impulsando la diversidad. La caracterización morfológica de las variedades autóctonas ha sido objeto de numerosos estudios, necesarios porque proporcionan información sobre los caracteres fenotípicos diferenciadores, y contribuyen a optimizar los programas de mejora vegetal. En este sentido, la caracterización de las variedades hortícolas valencianas seleccionadas se realizó siguiendo las directrices del IBPGR. Además, en esta tesis doctoral se han realizado estudios sobre el valor nutracéutico de las tres variedades seleccionadas por ser uno de los principales intereses del consumidor. Por ello, el contenido de algunos compuestos bioactivos y antioxidantes (fenoles, flavonoides, antocianinas, ácido ascórbico, licopeno, carotenoides, clorofilas y la actividad antioxidante), azucares y minerales fueron monitoreados para establecer parámetros de calidad en las especies mencionadas. También se determinó los parámetros indicativos de estrés oxidativo, para establecer la capacidad de conservación de atributos físico-químicos de la lechuga en el ensayo de post-cosecha.[CA] L'erosió genètica provocada en els cultius com a conseqüència de posar per davant producció sobre qualitat ha derivat en pèrdua de biodiversitat, fet que compromet la seguretat alimentària mundial. Els agricultors, a través d'un procés històric de selecció, han generat la diferenciació varietats tradicionals de cultiu que hui són font de biodiversitat agrícola. A més, s'afavoreix el desenvolupament de l'economia local. Per aquest motiu, la seva recuperació, classificació i cultiu són clau per a l'economia i el futur alimentari. La conservació de les varietats tradicionals requereix un coneixement de les mateixes mitjançant la descripció detallada de les seues característiques fenotípiques, agronòmiques, i de qualitat nutricional com a valor afegit. La Comunitat Valenciana compta amb un extens patrimoni hortícola constituït per una gran diversitat de varietats tradicionals d'hortalisses. Aquestes són fruit de l'adaptació a diverses condicions agroclimàtiques de la geografia valenciana, d'una banda, i de la selecció aplicada pels agricultors a cada localitat de l'altra. En aquest sentit, aquestes varietats tenen un gran valor com a patrimoni etnobotànic i com a tal haurien de ser conservades. Així mateix, actualment, el cultiu i el consum de les varietats tradicionals estan creixent, ja que són especialment atractives per als consumidors per la seua diversitat i la seua alta qualitat nutracèutica. En aquest context, aquesta tesi doctoral es basa en la caracterització fenotípica i nutricional per valoritzar les varietats tradicionals de la Ccomunitat, corresponents als cultius de pebre, albergínia i encisam, amb la finalitat de promoure'n la conservació i el cultiu a les zones d'origen, i impulsant la diversitat. La caracterització morfològica de les varietats autòctones ha estat objecte de nombrosos estudis, necessaris perquè proporcionen informació sobre els caràcters fenotípics diferenciadors, i contribueixen a optimitzar els programes de millora vegetal. En aquesta línia, la caracterització de les varietats hortícoles valencianes seleccionades es va fer seguint les directrius de l'IBPGR. A més, en aquesta tesi doctoral s'han fet estudis sobre el valor nutracèutic de les tres espècies seleccionades per ser un dels principals interessos del consumidor. Per això, el contingut d'alguns compostos bioactius i antioxidants (fenols, flavonoides, antocianinas, àcid ascòrbic, licopè, carotenoides, clorofil·les i l'activitat antioxidant), sucres i minerals van ser monitoritzats per establir paràmetres de qualitat a les espècies esmentades. També es van determinar els paràmetres indicatius d'estrès oxidatiu, per establir la capacitat de conservació d'atributs fisicoquímics de l'encisam a l'assaig de postcollita.[EN] Genetic erosion in crops, gained from prioritising production over quality, has led to biodiversity loss, which compromises global food security. By a historic selection process, farmers have been differentiating traditional crop varieties, which are a source of agricultural biodiversity that also favours the development of local economy, which makes their recovery, classification and cultivation key for food economy and the future. The conservation of traditional varieties requires knowledge of them, obtained from a detailed description of their phenotypical, agronomic and nutritional quality characteristics as added value. The Valencian Community (east Spain) has extensive horticultural heritage that is made up of a high diversity of traditional vegetable varieties. These are the result of adapting to the varied agroclimate conditions of the Valencian geography: on the one hand, the selection applied by farmers to each locality; on the other hand, these varieties are very valuable as ethnobotanical heritage and should be preserved. Moreover, the cultivation and consumption of traditional varieties are currently growing because they are particularly appealing to consumers for their diversity and high nutraceutical quality. In this context, the present doctoral thesis is based on a phenotypical and nutritional characterisation to evaluate traditional varieties in the Valencian Community, which correspond to pepper, eggplant and lettuce crops, to promote their conservation and cultivation in areas of origin, and to boost diversity. The morphological characterisation of landraces has been the subject of many studies, which are necessary because they provide information about differentiating phenotypical characteristics and help to optimise plant-breeding programmes. The characterisation of the selected Valencian vegetable varieties was carried out following IBPGR guidelines. Furthermore, studies were conducted in this doctoral thesis into the nutraceutical value of the three selected crops because this value is one of the main consumer interests. The content of some bioactive compounds and antioxidants (phenols, flavonoids, anthocyanins, ascorbic acid, lycopene, carotenoids, chlorophylls, antioxidant activity), sugars and minerals were monitored to establish quality parameters in the aforementioned species. Parameters indicative of oxidative stress were also determined to establish the conservation capacity of the physico-chemical attributes of lettuce in the post-harvest test.Martínez Ispizua, E. (2022). Rediscovering pepper, eggplant and lettuce landraces of the Valencian Community; an ancient resource with vast potential for the future [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/191053Compendi

Food, Nutrition and Agrobiodiversity Under Global Climate Change

Available evidence and predictions suggest overall negative effects on agricultural production as a result of climate change, especially when more food is required by a growing population. Information on the effects of global warming on pests and pathogens affecting agricultural crops is limited, though crop–pest models could offer means to predict changes in pest dynamics, and help design sound plant health management practices. Host-plant resistance should continue to receive high priority as global warming may favor emergence of new pest epidemics. There is increased risk, due to climate change, to food and feed contaminated by mycotoxin-producing fungi. Mycotoxin biosynthesis gene-specific microarray is being used to identify food-born fungi and associated mycotoxins, and investigate the influence of environmental parameters and their interactions for control of mycotoxin in food crops. Some crop wild relatives are threatened plant species and efforts should be made for their in situ conservation to ensure evolution of new variants, which may contribute to addressing new challenges to agricultural production. There should be more emphasis on germplasm enhancement to develop intermediate products with specific characteristics to support plant breeding. Abiotic stress response is routinely dissected to component physiological traits. Use of transgene(s) has led to the development of transgenic events, which could provide enhanced adaptation to abiotic stresses that are exacerbated by climate change. Global warming is also associated with declining nutritional quality of food crops. Micronutrient-dense cultivars have been released in selected areas of the developing world, while various nutritionally enhanced lines are in the release pipeline. The high-throughput phenomic platforms are allowing researchers to accurately measure plant growth and development, analyze nutritional traits, and assess response to stresses on large sets of individuals. Analogs for tomorrow’s agriculture offer a virtual natural laboratory to innovate and test technological options to develop climate resilience production systems. Increased use of agrobiodiversity is crucial to coping with adverse impacts of global warming on food and feed production and quality. No one solution will suffice to adapt to climate change and its variability. Suits of technological innovations, including climate-resilient crop cultivars, will be needed to feed 9 billion people who will be living in the Earth by the middle of the twenty-first century

Horticultural Crop Response to Different Environmental and Nutritional Stress

Environmental conditions and nutritional stress may greatly affect crop performance. Abiotic stresses such as temperature (cold, heat), water (drought, flooding), irradiance, salinity, nutrients, and heavy metals can strongly affect plant growth dynamics and the yield and quality of horticultural products. Such effects have become of greater importance during the course of global climate change. Different strategies and techniques can be used to detect, investigate, and mitigate the effects of environmental and nutritional stress. Horticultural crop management is moving towards digitized, precision management through wireless remote-control solutions, but data analysis, although a traditional approach, remains the basis of stress detection and crop management. This Special Issue summarizes the recent progress in agronomic management strategies to detect and reduce environmental and nutritional stress effects on the yield and quality of horticultural crops