Plant Productivity Research Articles

Plant species richness and legume presence increase microbial necromass carbon accumulation

Biodiversity control experiments have demonstrated that higher plant species richness increases plant production and soil organic carbon (SOC) stocks. However, although microbial necromass C constitutes a substantial and stable component of SOC, the effect of species richness on microbial necromass C accumulation remains unclear, especially concerning the presence or absence of legumes. We conducted an 8-year grassland biodiversity experiment to investigate how changes in plant diversity, with or without legumes, affect microbial necromass C and its proportion in SOC. Aboveground and root biomass increased by 254 % and 195 %, respectively, from monoculture plots to those with twelve species. SOC, total nitrogen (N), and microbial biomass C (MBC) all increased with plant species richness, independent of legume presence. The presence of legumes further increased the SOC, total N, MBC, and inorganic N compared to plots without legumes. Microbial necromass C increased by 48.3 % in twelve-species mixtures compared to monocultures; however, the ratio of microbial necromass C to SOC remained stable with increasing species diversity. Notably, the presence of legumes increased both the accumulation of microbial necromass C and its proportion in SOC compared to the absence of legumes at both high and low species diversity levels. This greater accumulation was primarily driven by increased plant productivity and microbial biomass, induced by legume-associated nitrogen fixation. Our findings highlight significant implications for ecosystem management: maintaining high levels of plant species diversity, particularly in conjunction with legumes, can increase microbial necromass C and enhance soil C sequestration.

Comprehensive analysis on investigating water-saving potentials of irrigated cotton in semi-arid area in China

Deficit irrigation is a common strategy to reduce water use and improve the sustainability of cotton production. However, the effects of water deficits on crop productivity and quality are subject to genotype by management by environmental interactions. This study investigated effects of water deficits and frequency of irrigation on cotton performance grown in semi-arid region, Xinjiang, the main cotton-growing area in China. Two field trials (2020 and 2021) with split experimental design, including main factors of three irrigation levels (moderate-deficit, mild-deficit and full-irrigation) and split factors of three irrigation frequencies (4, 8 and 12 days) were conducted. Results from two trials both showed little negative influence of irrigation levels on yield, and higher irrigation frequency improved yield under same irrigation level. Significant effects of irrigation levels on yield components were found in 2021, with a 22 % increase in boll number and an 18 % reduction in boll weight under moderate-deficit irrigation compared with those under full-irrigation. Interactions between irrigation levels and frequencies significantly affected harvest index (HI), showing that reduced irrigation might be beneficial for improving HI. However, decreased fibre length while increased fibre micronaire were found under deficit irrigation. A strong association between radiation use efficiency (RUE) and boll growth rate was observed, suggesting that RUE might be the driving force of yield formation. A tight correlation between both biomass and transpiration efficiency versus delta temperature between air and canopy (ΔTair-canopy) was observed, suggesting ΔTair-canopy could be used as an efficient tool to assess plant production under deficit irrigation. This study provided an improved understanding of the physiological basis of cotton yield formation and further identified a high-throughput and instantaneous method to monitor effects of deficit irrigation on crop productivity.

Performability analysis for the SPVC line system of leaf spring production plant using probabilistic approach

PurposeThis work ensures the higher performability of this complex system, which consists of five different subsystems, i.e. shearing machine, V-cutting machine, center hole punch, edge cutting burr and drilling machine. These subsystems are placed in combinations of both series and parallel arrangement. The concerned plant management must be aware of the failures that have the greatest/least impact on the system’s performance.Design/methodology/approachPerformability analysis has been done for the Shearing, Punch and V- Cutting (SPVC) line system by using a probabilistic approach (i.e. Markov method). This system was further divided into five subsystems, and single-order differential equations are derived using the transition diagram. MATLAB software was used to determine the performability of the system for various combinations of repair and failure rates.FindingsIn this research work, performability analysis was done using different combinations of repair and failure rates for these subsystems. Further, a decision matrix (DM) has been developed that indicates that edge cutting burr is the most critical subsystem, which requires the top level of maintenance priorities among the various subsystems. This matrix will facilitate policymaking related to various maintenance activities for the respective system.Originality/valueIn this research work, a mathematical modeling based on a single differential equation using a transition diagram has been developed for the SPVC line system. The novelty of this work is to consider interaction among different subsystem, which generates more realistic situation during modeling. The purposed DM helps make future maintenance planning, which reduces maintenance costs and enhances system's performability.

SPATIAL DISTRIBUTION OF PHOMA LEAF SPOT OF COFFEE AND RELATIONSHIP WITH ENVIRONMENTAL AND HOST VARIABLES

The objective of this study was to evaluate the spatial distribution of Phoma leaf spot of coffee and its relationship with the environmental variables altitude, soil texture, and mineral nutrients. In addition, the relationship between disease and foliar nutrients, leafing, and plant production was evaluated. The study was carried out in a 7.65 ha coffee plantation for two years. A total of 86 points were georeferenced in this area. The incidence and severity of the disease were assessed monthly, and the data were transformed into annual values of “Area Under the Incidence Progress Curve” (AUIPC) and “Area Under the Severity Progress Curve” (AUSPC) of the disease. Likewise, the monthly data for the leafing were transformed into annual values of “Area Under the Leafing Progress Curve” (AULPC). Environmental and host variables significantly correlated with the AUIPC were subjected to geostatistical modeling. Higher AUIPC and AUSPC were observed in the second year of the study. The altitude, P-rem and Ca present in the soil, as well as the P and N present in the leaves, showed a positive correlation with the AUIPC. The K, Cu, and Mn present in the leaves, the AULPC and the production were negatively correlated with this variable. The exponential semivariogram model was the most appropriate to model the spatial autocorrelation of the variables analyzed, except for altitude.

Multi-Omics Analysis Reveals the Transcriptional Regulatory Network of Maize Roots in Response to Nitrogen Availability

Nitrogen (N) availability determines higher plant productivity and yield. However, the molecular mechanisms governing N acquisition and utilization remain largely unknown in maize. In this study, ATAC-seq, RNA-seq, and Ribo-seq analyses were conducted in maize roots under different N supply conditions. A set of differentially expressed genes enriched in N and phenylpropanoid metabolisms at both the transcription and translation levels were highlighted. Interestingly, less than half of low-N responsive genes were shared between transcription and translation. The alteration of translational efficiency (TE) is also an important mechanism by which maize responds to LN. In addition, we identified low-N-induced open chromatin regions (OCRs) and observed an enrichment of transcription factor (TF) binding motifs. Furthermore, we constructed a transcriptional regulatory network for maize roots subjected to low-N. These findings extend our understanding of N availability response and provide new insights for improving N use efficiency (NUE).

Root-Zone Bacterial Diversity in Field-Grown Individual Plants from Alfalfa Lines with Wild Relatives in Their Genetic Backgrounds

Alfalfa (Medicago sativa L.) is a vitally important perennial fodder legume worldwide. Given their particular traits, alfalfa crop wild relatives (CWRs) could be used to develop cultivars that can tolerate extreme environmental and climatic conditions. Until now, researchers have overlooked the composition and structure of bacterial communities in the root zone of alfalfa and its relevant CWRs and their influence on forage performance under actual field conditions. In this study, high-throughput sequencing of 16S rRNA analysis was performed to investigate the diversity and assemblies of bacterial communities in the bulk soil and in the root zone of individual field-grown Medicago plants arranged in a honeycomb selection design. The plants used in this study were M. sativa × M. arborea hybrids (Genotypes 6 and 8), the closely-related M. sativa nothosubsp. varia (Martyn) Arcang. (Genotype 13), and M. sativa ssp. sativa (Genotype 20). The bacterial communities in the root-zone samples and the assemblies in the bulk soil differed significantly. Genotype 13 was found to have distinct bacterial assemblies from the other genotypes while exhibiting the lowest forage productivity. These findings suggest that plant productivity may influence the composition of bacterial communities in the root zone. Biomarker analysis conducted using linear discriminant analysis (LDA) revealed that only members of the Rhizobiales order were enriched in the M. sativa nothosubsp. varia root zone whereas taxa belonging to Sphingomonas and various Bacteriodota were enriched in the other genotypes. Of the shared taxa identified in the root zone of the Medicago lines, the abundance of specific taxa, namely, Flavisolibacter, Stenotrophomonas, and Sphingomonas, were positively associated with forage yield. This pioneering study, in which the root zones of individual Medicago plants under actual field conditions were examined, offers evidence of differences in the bacterial composition of alfalfa genotypes with varying genetic backgrounds. Its findings indicate that particular bacterial taxa may favorably influence plant performance. This study covered the first six months of crop establishment and paves the way for further investigations to advance understanding of how shifts in bacterial assemblies in alfalfa roots affect plant performance over time.

Virtual Reality Application for the Safety Improvement of Intralogistics Systems

Immersive technologies from the spectrum of Industry 4.0, such as Virtual Reality (VR), are increasingly used in research and safety analysis in industrial and intralogistics systems, including distribution warehouses and production plants. Safety in intralogistics systems is influenced by design and management processes, human behavior, and device performance. In all these areas, VR can serve as a supportive technology for visualization, testing, and employee training. However, this requires the development of principles for integrating VR into standard procedures for the design, modernization, and analysis of intralogistics and production systems. This article discusses the use of VR to analyze the occupational and functional safety of intralogistics systems. It reviews the literature and VR implementations aimed at examining and improving safety in industrial systems. The article explores the integration of VR into the design and analysis procedures for intralogistics and production systems. The authors present a five-dimensional decision space for assessing the use of VR, including identifying subjects of safety analysis, threats and hazards specific to intralogistics, countermeasures for these threats, factors affecting safety, and mechanisms by which VR can improve safety in intralogistics systems. As a subsequent step, the authors discuss using universal simulation environments that support VR technology to study and enhance safety in intralogistics systems, providing a framework example based on the FlexSim (2023 update 2) environment. Finally, this article addresses the threats and limitations of VR technology, along with the challenges and future prospects of VR in the context of Industry 4.0. The article concludes that VR can be an essential tool for increasing safety in the future, albeit with some reservations about certain features of this technology.

A Combined Discrete Event Simulation and Factorial Design Experiment for the Scheduling Problem in a Hybrid Flow Shop

Production plants have always been confronted with the problem of scheduling, as this has a direct impact on production time and therefore on production costs. This is especially true in today's world, where it is necessary to produce a quality product at a low price and in a short time, while at the same time responding flexibly to customer demands. Due to the complexity and for economic reasons, testing different variants in a real production environment is insufficient and ineffective. For this reason, this paper proposes a new method that combines discrete event simulation and factorial design experiment to find the optimal schedule in hybrid flow shop. It was tested with the goal of achieving the minimum makespan. The results show that this method makes it possible to find improved solution very quickly. Compared to the original production schedule, the makespan could be reduced by 3 hours and 31 minutes which is reduction of 16.3%. The proposed methodology can be used in many discrete and process production plants.

A novel algorithm MPPT controller based on the herd horse optimization for photovoltaic systems under partial shadow conditions

In recent years, a significant scientific issue has been the creation of maximum power point tracking (MPPT) methods to increase the energy production of PV plants. Moreover, to try to cope with the unparalleled operating conditions of PV plants, many bio-inspired meta-heuristic algorithms have already been suggested in the literature, but their implementation is often complex and difficult. In this sense, we propose a novel algorithm for monitoring the (MPPT), using the newly meta-heuristic approach of herd horse optimization (HHO). A DC/DC boost converter is utilised in the suggested controllers to extract the most power possible from the PV resource. The system is programmed and modelled using the MATLAB/SIMULINK software, which also studies four shadow models and a 3S1P topography of single-junction solar arrays. Considering partial shading conditions (PSC), the success of the power values in the global maximum power point (GMPP) of the proposed method is between 99.64% and 99.07%. Besides the time to capture the GMPP by the proposed algorithm is between 0.396 s and 1.666 s, shorter than that of the CSA and FPA algorithms. Comparison with the CSA and FPA optimizers confirmed the quality of the MPPT-based HHO algorithm for GMPP extraction in different (PSC).

RESPON CABAI (Capsicum annum L.) TERHADAP PENGGUNAAN PUPUK ORGANIK CAIR DAN PUPUK HAYATI MIKORIZA

Red chili (Capsicum annuum L.) is one of the commodities vegetables that have high economic value. One attempt to increase the growth and yield of chili plants by using liquid organic fertilizer and mycorrhizal biological fertilizer. This research aims to determine the best dosage of liquid organic fertilizer and mycorrhizal biological fertilizer on the yield of red chili (Capsium annum L.). The research was carried out on land of Agriculture of Palembang City, South Sumatra Province. The research period was carried out from February to June 2023. The research used a Randomized Group Factorial Design (RAKF) with 9 treatments and 3 replications. The first factor is liquid organic fertilizer from vegetable waste according to the treatment, namely O1 = 5 ml/L, O2 = 10 ml/L and O3= 15 ml/L. The second factor is the provision of Mycorrhizal biofertilizer (M) which consists of 4 treatment dose levels, namely M0 = 0 g/ta (without mycorrhiza), M1 = 2.5 g/ta, M2 = 5 g/ta, M3 = 7.5 g /ta. The observation parameters in this study were chili weight per plant (g), chili weight per plot (g) and number of productive brances (brances). The results of the research showed that treatment with a POC dose of vegetable waste of 5 ml/l of water with mycorrhizal biological fertilizer of 2.5 g/lot had the highest influence on chili plant production of 48.33 g/plot or the equivalent of 193,32 kuintal/ha.

Productivity Of Various Cocoa Clones (Theobroma Cacao L.) At Different Rainfall Levels In Tettikenrarae Village, Soppeng Regency

Changes in rainfall are one of the causes of declining production in cocoa plants and cause land degradation, thus reducing national cocoa productivity. This study aims to analyze the productivity of various clones of cocoa plants at different rainfall levels so that the relationship between production levels and cocoa productivity at different rainfall levels is known. This study used the observation method. Data collection was done by random sampling in farmers' farms by determining the appropriate sample plants. The sample plants used came from three different clones, namely MCC Clone 01 (M01), MCC Clone 02 (45), and Sulawesi Clone 1 (S1) which were 13 years after planting and still productive. Rainfall data was obtained from available data at the BMKG of South Sulawesi Province. Data analysis was conducted to determine the productivity comparison of three cocoa clones at different rainfall levels. The results showed that: 1) Different rainfall levels affect the productivity of various cocoa clones in Tettikenrarae Village, Soppeng Regency. This can be seen in the parameters of number of seeds and weight of seeds, with productivity respectively for clone MCC 02 amounting to 4350.66 kg, clone S1 4326.78 kg, and clone MCC 01 with a production of 3863.29 kg. 2) Productivity of cocoa clones in Tettikenrarae Village, Soppeng Regency is best in moderate rainfall conditions, where clone MCC 02 has the highest productivity of 1820.47 kg which occurs in rainfall of 100 - 300 mm.

Rhizobacterial consortium differently affects black leaf spot, physiological, morphological, and productive components in two generations of banana plants

Rhizobacteria's effects on commercial banana plants in different generations remain unclear. In the present field-level investigation, we evaluated the effect of three types (injection, edaphic, and foliar) of applications of a local rhizobacterial consortium on Black leaf spot (BLS), chlorophyll content, morphological components, and fruit production in two generations of commercial banana plants cv. Williams. The rhizobacteria-treated mother and daughter plants received one and two applications, respectively, while the untreated plants constituted the control group. Results of the present investigation indicated that the rhizobacteria differently affect the aerial tissues of different generations of banana plants. Regardless of how the rhizobacteria were applied, they reduced an average of 40 % the BLS incidence on leaves (P ≤ 0.0001) and increased an average 9 % the plant height and pseudostem circumference (P ≤ 0.0001 – P = 0.0475) of mother and daughter plants were observed. However, both morphological variables improved even more in daughter plants edaphically treated with rhizobacteria. Leaf pigments like chlorophyll B (P = 0.0262) and the total content (P = 0.0230) only increased an average of 40 % in daughter plants treated with rhizobacteria. Rhizobacteria edaphic application and injection improved bunch weight (P = 0.0048) and hands per bunch (P ≤ 0.0001) in mother plants. Meanwhile, the edaphic application significantly increased the bunch weight (P = 0.0031), hands per bunch (P = 0.0074), and rachis weight (P = 0.023) by 17% on average in edaphically and foliar-treated mother plants, while the finger length (P = 0.0064) increased by 5% on average. Generally, the morphological and productive components increased much more in daughter plants than in mother. These findings demonstrate the potential of edaphically and foliar rhizobacterial applications to enhance plant health and productivity, providing a sustainable management strategy for banana cultivation.

Transcriptomics Provide Insights into Early Responses to Sucrose Signaling in Lupinus albus, a Model Plant for Adaptations to Phosphorus and Iron Deficiency

Phosphorus (P) and iron (Fe) deficiency are major limiting factors for plant productivity worldwide. White lupin (Lupinus albus L.) has become a model plant for understanding plant adaptations to P and Fe deficiency, because of its ability to form cluster roots, bottle-brush-like root structures play an important role in the uptake of P and Fe from soil. However, little is known about the signaling pathways involved in sensing and responding to P and Fe deficiency. Sucrose, sent in increased concentrations from the shoot to the root, has been identified as a long-distance signal of both P and Fe deficiency. To unravel the responses to sucrose as a signal, we performed Oxford Nanopore cDNA sequencing of white lupin roots treated with sucrose for 10, 15, or 20 min compared to untreated controls. We identified a set of 17 genes, including 2 bHLH transcription factors, that were up-regulated at all three time points of sucrose treatment. GO (gene ontology) analysis revealed enrichment of auxin and gibberellin responses as early as 10 min after sucrose addition, as well as the emerging of ethylene responses at 20 min of sucrose treatment, indicating a sequential involvement of these hormones in plant responses to sucrose.

Evaluation of spent coffee grounds as a nutrient source for turfgrass systems

The growing popularity of cold-brewed coffee has resulted in large amounts of localized spent coffee grounds (SCG) generated from production plants. Spent coffee grounds offer many favorable agronomic properties, but also contain caffeine, tannins and phenolic compounds that may be deleterious to plant growth. There is a growing body of research examining the effects of SCG on plants, but little of which pertains to use in turfgrass systems. The objective of this two-year field study was to evaluate the feasibility of using SCG as an agronomic source of nutrients for turfgrass. Field studies were conducted over two years to characterize performance of ‘Riley’s Super Sport’ (Celebration®) bermudagrass (Cynodon dactylon) receiving multiple nutrient source treatments including fresh and composted SCG, as well as synthetic, natural organic, and bridge fertilizers, some which included SCG. Soils were analyzed at the conclusion of the study to determine whether SGC provided long-term effects of on soil pH and/or nutrient concentrations. Our results demonstrated that although SCG possesses between 2.3-2.9% N and a favorable C:N ratio, direct SCG applications over two seasons did not produce responses typical of a fertilizer when applied as a topdressing. However, when combined with poultry litter, the SCG-containing organic fertilizer GeoJava produced improved turf quality relative to other organic and synthetic commercial fertilizers in our study, including Milorganite, ammonium sulfate, and URI-PEL S.R. Further, despite the acidic nature of SCG, their repeated application over multiple years did not result in any long-term changes to soil pH. Although early on, SCG treatments caused mild and transient phytotoxicity, these effects were not observed when it was applied in combination with the manure used in GeoJava.

Pemberian Edukasi Kepada Pelajar di Kabupaten Lamandau Mengenai Smart Agriculture

The world's increasing food needs due to the increase in population have caused humans to increasingly innovate to increase plant productivity. Smart Agriculture is the current answer that can be utilized and optimized to increase the productivity and sustainability of agricultural systems. This PkM activity was carried out online involving students in Lamandau Regency as activity participants. The aim of this PkM activity is to provide additional information and insight for students in Lamandau Regency regarding Smart Agriculture. The method used is lecture and activity stages consisting of, 1) Preparation Stage; 2) Implementation Phase and 3) Evaluation Phase. As a result of this PkM activity, understanding of Smart Agriculture among students has increased and motivated students to innovate and deepen knowledge related to Smart Agriculture.

Unmasking Spatial Heterogeneity in Phytotoxicology Mechanisms Induced by Carbamazepine by Mass Spectrometry Imaging and Multiomics Analyses.

Previous studies have highlighted the toxicity of pharmaceuticals and personal care products (PPCPs) in plants, yet understanding their spatial distribution within plant tissues and specific toxic effects remains limited. This study investigates the spatial-specific toxic effects of carbamazepine (CBZ), a prevalent PPCP, in plants. Utilizing desorption electrospray ionization mass spectrometry imaging (DESI-MSI), CBZ and its transformation products were observed predominantly at the leaf edges, with 2.3-fold higher concentrations than inner regions, which was confirmed by LC-MS. Transcriptomic and metabolic analyses revealed significant differences in gene expression and metabolite levels between the inner and outer leaf regions, emphasizing the spatial location's role in CBZ response. Notably, photosynthesis-related genes were markedly downregulated, and photosynthetic efficiency was reduced at leaf edges. Additionally, elevated oxidative stress at leaf edges was indicated by higher antioxidant enzyme activity, cell membrane impairment, and increased free fatty acids. Given the increased oxidative stress at the leaf margins, the study suggests using in situ Raman spectroscopy for early detection of CBZ-induced damage by monitoring reactive oxygen species levels. These findings provide crucial insights into the spatial toxicological mechanisms of CBZ in plants, forming a basis for future spatial toxicology research of PPCPs.

Cultivation of Chlorella vulgaris in wastewater: biodiesel potential and wastewater remediation.

The present investigation has evaluated the use of effluents from a secondary municipal wastewater treatment plant for biomass production and potential of the biomass for biodiesel production. Cultivations of Chlorella vulgaris using wastewater, wastewater with supplementation, and WC medium were carried out. Effect of wastewater collected in different months on biomass productivity (BP) and lipid composition was studied. Methods based on NMR and GC-MS techniques were applied for determining the composition of the lipids and their fatty acid profile including poly unsaturated fatty acids (PUFAs). Lipids extracted are comprised of both neutral (tri acyl glycerides, TAG; free fatty acids, FFA) and polar (glyco glycero/phospho) lipids. The TAG content of the extracted lipids was determined in the range of 22.5-41.3% w/w. The NMR and GC-MS compositional results of microalgal lipids of biomasses cultivated in wastewater without nutrient supplementation, collected in different months, showed potential for biodiesel production. The fatty acid profiles of neutral and polar lipids, which are mainly comprised of saturated and unsaturated long alkyl chain (C16-C22) fatty acids, are potential sources for the biodiesel and food industry. The concentration of nitrates (45-78mg L-1) in wastewater without supplementation, collected in different months, was found to be optimum to enable cultivation of biomasses with reasonably good BP of 21.5-28.1mg L-1day-1. Similar results have been obtained in the present work as well as reported in the literature in the case of WC medium (nitrate, 69mg L-1) with BP of 25.5-28.2mg L-1day-1, thus highlighted the significance of the presented work.

Chrysin Enhances Anti-cancer Activity of Jurkat T Cell and NK-92 Cells Against Human Breast Cancer Cell Lines.

Chrysin, a naturally occurring flavonoid in plant and bee products, demonstrates notable biological activities, including anti-cancer effects. These properties are partially attributed to its capability to activate immune cells. This study focused on exploring the immunomodulatory potential of chrysin on NK-92 and Jurkat-T cells targeting breast cancer cells (BCC). Chrysin leads to activation of NK-92 and T cells facilitated by the addition of human recombinant IL-2 and PHA-M. The anti-cancer efficacy of chrysin on these immune cells was evaluated in a co-culture setup with EGF-stimulated MCF-7 and MDA-MB-231 cells. Findings revealed that chrysin notably increased the cytotoxicity of NK-92 and T cells towards MCF-7 and MDA-MB-231 cells, with the most significant impact observed on MCF-7 cells (20%). The activation of NK-92 cells, marked by increased IFN-γ production and CD56 expression, correlated with enhanced secretion of cytokines. Additionally, the activation of these cells against BCC was linked with elevated levels of granzyme-B, TNF-α, and nitric oxide (NO). Similarly, the cytotoxic activation of Jurkat-T cells against BCC was characterized by increased production of granzyme-B, IL-2, and IFN-γ. Consequently, these results support the hypothesis that chrysin significantly contributes to the activation and functional enhancement of NK-92 and T-cells against two distinct BCC lines.

Modification of Coconut Fibers through Impregnation with Eco-Friendly Wood Based Isolate as a Method to Increase the Sustainability of Dessert Raspberries Production

Natural substrates used in horticultural practice quickly degrade during plant cultivation. Methods to extend their service life are sought using natural materials, the acquisition and disposal of which do not burden the natural environment. The paper presents a sustainable method for modifying the coconut fiber substrate by impregnation with a wood-based isolate activated for polymerization and the addition of biochar pellets with retention-increasing properties. The modifications applied to the substrates were shown to have an impact on some of their physical properties, which directly impacted their usefulness in the horticultural production of dessert raspberries. It was found that after a year of operation, the modified substrates showed significantly lower levels of degradation markers. The shrinkage of the impregnated substrate was ~50% lower than that of the control sample, while the substrate with the addition of biochar pellets resulted in similar shrinkage and the lowest plant root mass (25.47%). The usefulness of these substrates was also verified by measuring the physiological parameters of the plants, which determined the ability to photosynthesize and build biomass, as well as susceptibility to stress potentially caused by substrate modifications. The recorded values of these parameters indicate, in most cases, that there is no disturbance of the homeostasis of raspberry plants grown using these substrates. However, plant productivity (measured by the yield of harvested raspberry fruit) indicates that the use of impregnated coconut fiber substrate with the addition of biochar pellets allows for obtaining the highest fruit yields (fruit yield—2.43 kg plant−1). The yields obtained in combination with the extended durability of the modified substrates during operation recommend this solution for use in horticultural practice and make the production more sustainable.

Estimation of LAI of tobacco plant using selected spectral subsets of visible and near-infrared reflectance spectroscopy

Flue-cured tobacco is a main economic crop, and leaves are the direct product of tobacco plant. Monitoring leaf area index (LAI) of tobacco plant is important to field management, yield prediction, and industry regulation. Hyperspectral data have hundreds of narrow spectral bands in continuous spectral ranges, significantly advancing monitoring of LAI. However, considering spectral responses of LAI vary with wavelength, the use of the full spectral range in estimation of LAI is redundant. To reduce spectral redundancy and improve estimation of LAI, spectral subsets were selected based on importance of spectral bands. Variable importance in the projection (VIP) score obtained by partial least squares regression (PLSR) was adopted to measure the importance. The study was conducted in Yunnan Province, China. Canopy reflectance spectra of tobacco plant were measured in two consecutive growth seasons. Genetic algorithm (GA) and PLSR were used for model calibration. The identified important spectral regions for estimation of LAI were red edge, near-infrared (NIR), and green regions. In estimation of LAI of tobacco plant, compared with the estimation using the full spectral range of VNIR reflectance spectra, normalized root mean square error (NRMSE) and coefficient of determination (R2) values were improved from 10.30% and 0.83 to 7.68% and 0.90 and from 18.78% and 0.43 to 7.65% and 0.90 by using the reflectance spectra in identified spectral regions in the growth seasons in 2021 and 2022 separately. In addition to the identified continuous spectral regions, central bands of the identified spectral regions also achieved estimation of LAI, with the highest R2 value reaching 0.72. The selected spectral subsets improved estimation accuracy and reduced model complexity. The results indicate that selected spectral subsets are effective and promising in estimation of LAI, providing an alternative for estimation of LAI using hyperspectral data.