Leaf Layers Research Articles

The Experience Using of Freeze-Dried Mulberry Leafs’ as Composition of Artificial Diet for Feeding Silkworm Caterpillars

Aims: Due to changes in the global climate and the recent increase in spring frosts, which lead to the death of silkworm caterpillars of the first ages due to lack of food, there is an urgent need to find effective and cheap means to replace natural food - mulberry leaf. One of the promising methods is the preservation of mulberry leaf. One of the new and progressive methods of preservation is the method of freeze-dried of mulberry leaf, for the basis of artificial diet. Place and Duration of Study: The experiments were conducted in the laboratory of the Scientific Research Institute of Sericulture in 2024y. Methodology: After hatching, the caterpillars were fed artificial food based on freeze-dried mulberry leaf, the food was given once a day, the room temperature was 25-26 ° C, humidity 65-70%. When the caterpillars reached the third age, some of the caterpillars of each breed and hybrid were selected and continued to be fed with artificial diet. The remaining caterpillars were transferred to natural leaf feeding according to a generally accepted method. Results: The drying time of the mulberry leaf in the freeze-dried mode was 14-18 hours, depending on the uniformity of the leaf layer in the chamber. A recipe for artificial diet was created, in which the content of mulberry leaf powder was 72%. All breeds and hybrids equally well received the developed artificial diet. In breeds and hybrids, the viability of caterpillars was 82-100%. And when switching from artificial diet to a natural leaf, the viability of caterpillars was 63-93%. Conclusion: All breeds and hybrids equally well accepted the developed artificial food based on freeze-dried mulberry leaf. According to the totality of the results shown, the studied breeds and hybrids are promising for feeding them on artificial feed and breeding appropriate lines and breeds from them.

Using Legume-Enriched Cover Crops to Improve Grape Yield and Quality in Hillside Vineyards

Natural covering (NATC) has spread on hillside vineyards of central Italy as a replacement for tillage to reduce soil erosion, although it increased nitrogen and water needs. Therefore, in the current context of global warming, using cover crops (CCs) that require less water and provide nitrogen becomes crucial. The effects of two low-competition legume-enriched CCs in a rainfed hillside vineyard—a perennial legume–grass mixture (PLGM) and an annual legume cover crop of Trifolium alexandrinum (ALTA)—were compared with NATC over three years. PLGM and ALTA provided good levels of soil coverage, slightly lower than NATC, which had a negligible presence of legumes. PLGM and ALTA, due to low competition, enhanced vine vigor, resulting in thicker and wider canopies (as indicated by total leaf area and leaf layer number), higher pruning weight, and increased yield. PLGM and ALTA led to good qualitative levels, with higher grapes acidities, lower pH and total soluble solids content and, additionally, significantly higher yeast assimilable nitrogen content. In conclusion, implementing low-competition legume species in CCs is an effective tool to avoid soil erosion in a climate change scenario, leading to increased productivity, higher acidity, and improved nitrogen content in the grapes.

Profiling Metabolites Distribution among Various Leaf Layers of Chinese Cabbage

Chinese cabbage is an important vegetable from both a nutritional and an economic standpoint, with the leafy head serving as the primary harvested organ. However, the nutrient accumulation as well as influencing factors within the leafy head have not yet been elucidated. Thus, the distribution of metabolites (soluble sugars, minerals, carotenoids, vitamin C, flavonoid compounds, glucosinolates, and total phenolic compounds) were investigated in different leaf layers of Chinese cabbage with varying head types. The results showed that the inner leaves consistently displayed markedly higher levels of fructose and glucose when contrasted with the outer leaves. Similarly, there was an accumulation of glucosinolates in the inner leaves. By contrast, however, the antioxidants content exhibited a consistent decline from the outer leaves towards the central core, in line with the diminishing antioxidant capacity. This descending trend was also apparent in the mineral content, encompassing calcium, sodium, magnesium and sulfur. These results will provide dietary instruction, especially for consumers who have particular dietary needs.

MONTPEL: A multi-component Penman-Monteith energy balance model

Mechanistic modelling is gradually replacing empiricism in crop models, focusing on leaf-level physiological processes. This shift necessitates simulating crop surface temperature at infra-canopy sub-daily scales but many crop models still rely on empirical formulations for canopy temperature estimation, typically on a daily basis. We developed MONTPEL, a multi-component Penman-Monteith model that allows simulating the crop energy balance with flexible canopy representations (“BigLeaf” vs. “Layered”, “Lumped” vs. “Sunlit-Shaded”) and accounts for atmospheric stability conditions. We analyzed the model behavior, sensitivity and accuracy, using measurements from four wheat (Triticum aestivum L.) experiments conducted under varying pedoclimatic and water stress conditions. Measurements included hourly energy balance terms (total net radiation, soil heat flux, sensible and latent energy fluxes), hourly temperature of the canopy surface or of leaves at different depths inside the canopy, and sunlit and shaded leaf temperatures around solar noon at different dates. MONTPEL reproduced the measured energy balance terms with a root mean square error (RMSE) between 21 and 87 Wm-2 and a coefficient of determination (R²) exceeding 0.65. The model's accuracy in simulating canopy temperature, with RMSE ≤ 2.2 °C and R² ≥ 0.92, remained consistent regardless of measurement scale. Adjusting the aerodynamic resistance for atmospheric stability minimized simulated canopy temperature errors, notably in semi-arid conditions. Crop latent energy flux and temperature were most sensitive to the maximal stomatal conductance (gs,max) parameter. However, using a single gs,max value across the simulated experiments yielded satisfactory results, suggesting a weak sensitivity to the temporal and site-to-site variability of gs,max. Distinguishing sunlit from shaded canopy fractions systematically resulted in lower latent energy fluxes compared to “Lumped” canopy representation results. Analysis identified limitations in the multi-component approach, particularly an unrealistic uniform temperature shift across leaf layers when soil surface temperature changes.

Photosynthesis and photoprotection in top leaves respond faster to irradiance fluctuations than bottom leaves in a tomato canopy.

Accounting for the dynamic responses of photosynthesis and photoprotection to naturally fluctuating irradiance can improve predictions of plant performance in the field, but the variation of these dynamics within crop canopies is poorly understood. We conducted a detailed study of dynamic and steady-state photosynthesis, photoprotection, leaf pigmentation, and stomatal anatomy in four leaf layers (100, 150, 200 and 250cm from the floor) of a fully-grown tomato canopy in the greenhouse. We found that leaves at the top of the canopy exhibited higher photosynthetic capacity and slightly faster photosynthetic induction compared to lower-canopy leaves, accompanied by higher stomatal conductance and a faster activation of carboxylation and linear electron transport capacities. In upper-canopy leaves, non-photochemical quenching showed faster induction and relaxation after in- and decreases in irradiance, allowing for more effective photoprotection in these leaves. Despite these observed differences in transient responses between leaf layers, steady-state rather than dynamic photosynthesis traits were more influential for predicting photosynthesis under fluctuating irradiance. Also, a model analysis revealed that time-averaged photosynthesis under fluctuating irradiance could be accurately predicted by one set of Rubisco activation/deactivation parameters across all four leaf layers, thereby greatly simplifying future modelling efforts of whole-canopy photosynthesis.

Monitoring the Nitrogen Nutrition Index Using Leaf-Based Hyperspectral Reflectance in Cut Chrysanthemums

Precise nitrogen supply is crucial for ensuring the quality of cut chrysanthemums (Chrysanthemum morifolium Ramat.). The nitrogen nutrition index (NNI) serves as an important indicator for diagnosing crop nitrogen (N) nutrition. Hyperspectral remote sensing (HRS) technology has been widely used in monitoring crop N status due to its rapid, accurate, and non-destructive capabilities. However, its application in estimating the NNI of cut chrysanthemums has received limited attention. Therefore, this study aimed to use HRS to accurately determine the cut chrysanthemum NNI, thereby providing valuable guidance for managing N fertilization. During several key growth stages, a hyperspectral spectroradiometer was used to capture hyperspectral reflectance data (350–2500 nm) from three leaf layers. Subsequently, cut chrysanthemum canopies were sampled for aboveground biomass (AGB) and plant nitrogen concentration (PNC). The collected AGB and PNC data were then utilized to fit the critical N (Nc) dilution curve of cut chrysanthemums using a Bayesian hierarchical model, enabling the calculation of the NNI. Finally, spectral indices and partial least squares regression (PLSR) were used to establish the NNI estimation model for cut chrysanthemums. The results showed that the Nc dilution curve of the cut chrysanthemums was Nc = 5.401 × AGB−0.468. The first leaf layer (L1) proved to be optimal for estimating cut chrysanthemum NNI. Additionally, a newly proposed two-band spectral index, DVI-L1 (R1105, R700), demonstrated moderate predictive capabilities for the NNI of cut chrysanthemums (R2 = 0.5309, RMSE = 0.3210). Compared with the spectral index-based NNI estimation model, PLSR-L1 showed the best performance in estimating the cut chrysanthemum NNI (R2 = 0.8177, RMSE = 0.2000). Our results highlight the rapid NNI prediction potential of HRS and its significance in facilitating precise N management in cut chrysanthemums.

The Effect of Irrigation on the Vineyard Canopy and Individual Leaf Morphology Evaluated with Proximal Sensing, Colorimetry, and Traditional Morphometry

The high number of grapevine (Vitis vinifera L.) cultivars grown world-wide are described and identified according to detailed morphological and morphometric descriptor lists. The grapevine leaf is of utmost importance in characterization, despite its traits being very sensitive to environmental factors. In this study, the effect of irrigation/drought stress on the individual leaf morphology and morphometry of the ‘Hárslevelű’ grapevine (Vitis vinifera L.) cultivar was examined. To verify the effect of the applied irrigation methods (drip and subsoil irrigation) on the plant’s water status, water potential measurements were carried out during the 2022 season. The effect of the applied treatments on the vegetative growth was evaluated according to point quadrat and a multichannel LiDAR analysis in order to describe the width of the canopy area, row volume, and area coverage index. The individual leaf morphology was assessed via traditional morphometry and colorimetry. Our results showed that rainfed plants had a significantly lower stem ψ compared to the drip- and subsoil-irrigated plants at all examined dates. The point quadrat results indicate that the leaf layer number was significantly (p < 0.05) influenced by the position, while the treatment showed no effect on the leaf layer number. The leaf colorimetry showed a difference among the samples, as significant alterations were found in 28 out of the 32 examined color properties. Within the traditional morphometric analysis, 54 traits were evaluated, and 14 of the traits were significantly altered due to the different water management systems.

Relationship between secondary metabolites and insect loads in cabbage with different leaf shapes and positions.

Secondary metabolites in plants play a crucial role in defense mechanisms against insects, pests, and pathogens. These metabolites exhibit varying distributions within and among plant parts under different biotic and abiotic conditions. Understanding the intricate relationships between secondary metabolites and insect populations can be helpful for elucidating plant defense mechanisms and enhancing agricultural managing efficiencies. To investigate the influence of the glucosinolate profile in the leaves of three cabbage (Brassica oleracea var.capitata L.) varieties on insect loads. Glucosinolate profiles across different leaf positions (such as bottom, middle, and center) and leaf shapes (such as curly and non-curly leaf) of three cabbage varieties (Xiagan [XGA], Xiaguang [XGU], and Qiangxia [QIX]) were analyzed by using high-performance liquid chromatography-mass spectrometry (LC-MS). The insect loads were recorded by visually inspecting the upper and lower layers of each target leaf. Increasing concentrations of four glucosinolates, namely, glucoiberin, progoitrin, glucoraphanin, and glucobrassicin, were positively related to insect loads. While increasing concentrations of the other four glucosinolates, such as neoglucobrassicin, 4-methoxyglucobrassicin, sinigrin, and gluconapin, were negatively related to insect loads. Furthermore, both glucosinolate synthesis and insect loads were significantly higher in the curly-shaped and middle-position leaves than in the non-curly-shaped and bottom- and central-position leaves across the cabbage varieties. Differences in glucosinolate profiles across leaf positions and shapes strongly influenced the insect loads of the three Brassica varieties. This link may further extend our understanding of the real defense power of a particular variety against herbivore damage.

Fluorescence lifetime of plant leaves with sub-nanosecond resolution

The study aimed to develop a measurement apparatus for in vivo chlorophyll-a (Chl-a) fluorescence decay measurements of plants by means of time correlated single photon counting. In this approach, sub-nanosecond laser pulses with a repetition rate of 10 MHz are applied to excite the sample, followed by the analysis of arrival times of the emitted fluorescence photons. Photon statistics are generated by iteratively fitting the sum of two exponential functions. The tool was tested on both plastid and in vivo leaf samples of Savoy cabbage (Brassica oleracea var. sabauda) with 3–4 subsequent leaves giving a complete sample coverage starting from the outermost. The Chl-a fluorescence lifetime exhibited a gradual increase in both the isolated plastid suspensions and the in vivo leaf samples towards the innermost leaf layers explained by an increase of natural absence of light (etiolation syndrome). Furthermore, cadmium stress and iron deficiency were investigated on treated sugar beet (Beta vulgaris) samples in vivo using TCSPS measurements. The reduced fluorescence quenching resulted in an increased fluorescence lifetime. Finally, a long-term (10 week) testing of the setup was carried out on Chl-retaining resurrection Haberlea rhodopensis plants protecting themselves by an elevated non-photochemical quenching yielding a decrease of fluorescence lifetime during their desiccation.

2011–2015年东洞庭湖洲滩典型植物群落样方调查数据集

The fixed sample plot investigation obtains the dynamic characteristics of ecosystem through long-term data accumulation and accurate space-time comparison, which provides a solid basis for long-term ecosystem research. In accordance with the unified monitoring specifications set forth by the Chinese Ecosystem Research Network (CERN), Dongting Lake Wetland Ecosystem Research Station conducts long-term positioning monitoring on the species composition and community characteristics of typical beach vegetation in the wetland ecosystem in response to the changing hydrological conditions of Dongting Lake. We processed the data of long-term monitoring sample plots of three typical wetland plant communities (Carex sp, Miscanthus lutarioriparius and Polygonum hydropiper) in Dongting Lake to obtain the dataset of sample survey of typical plant communities on East Dongting Lake beach from 2011 to 2015. This dataset covers a total of 14 indicators, including species name, Latin name, number of plants (clusters) (plants or clusters/quadrats), average height of leaf layer (cm), average height of reproductive branches (cm), coverage (%), phenological period, dominant species, number of plant species, density (plants or clusters/m2), leaf layer height (cm) of dominant species, reproductive branch height (cm) of dominant species, total coverage (%), and total dry weight of aboveground green parts (g/m2). This dataset comes with detailed background information to ensure its consistency across both spatial and temporal dimensions. Moreover, to ensure data accuracy and reliability, the dataset underwent comprehensive quality control throughout the entire process and is subject to expert review and verification. It can serve as an important source of background data for studying the process and succession trends of the beach wetland ecosystem in response to the hydrological conditions of Dongting Lake, and provide data support for vegetation remote sensing monitoring, biodiversity protection, wetland ecological restoration and adaptive management of Dongting Lake.

How do novel plant growth regulators and cultivation models strategies affect mechanical strength, lodging resistance and maize productivity in semi-arid regions?

Plant growth regulators are synthetic compounds that have become a significant and technical guarantee for agricultural productivity. In China, "Jindeli", which contains active elements of ethephon and cycocel (EC), has been proven to prevent maize stem elongation, improve maize stem thickness, stem morphology and mechanical strength, root growth, lodging resistance, and yield under various cultivation models. Diethyl aminoethyl hexanoate (DA-6) can promote cell division and growth. From 2020–2021, four growth regulators sprays were used to conduct a field experiment; G1: water spraying; G2: EC spraying; G3: DA-6 spraying; G4: EC+DA-6 spraying under two cultivation models; R: ridge covered with plastic film mulching and T: traditional flat planting without plastic mulching. The results indicated that RG4 treatment considerably decreased plant height, internode length, ear height, lodging rate, and center of gravity height, while improved the internode bending strength, cross-sectional area, cortical thickness, and stem vascular bundles as compared with rest of all other treatments. RG4 treatment considerably improved internode diameter, stem mechanical strength, filling degree, root growth, mean tilt angle, and lignin content, while significantly reducing LAI. In addition, RG4 considerably enhanced the quality of corn stems, such as increasing mechanical properties and enhancing the compressive strength of corn stalks that content of hemicellulose, cellulose, and lignin has been increased. Furthermore, RG4 treatment significantly improved grain yield by optimizing leaf layer structure and increasing bleeding saps levels, increasing the grains per row and ear. Thus, under the RG4 treatment maize lodging rate was decreased 72.1%, and increased WUE (52.8%), and grain yield (46.6%). In conclusion, the results clearly demonstrate that in the semi-arid regions risk of lodging can be avoided by spraying EC+DA-6 with ridge covered plastic film mulching to the enriched stalk quality, shaping plant morphological characteristics, and proving a stable cultivation model to improving maize productivity.

Looking at Leaf Layers

"Looking at Leaf Layers," submitted by Penelope Planet, examines the intersection between science and art using microscopy.

Cost-Effective 3D-Printed Bionic Hydrogel Evaporator for Stable Solar Desalination.

Solar desalination using hydrogel evaporators is an eco-friendly, highly efficient means with natural sunlight for sustainable freshwater production. However, it remains challenging to develop a cost-effective and scalable method to prepare salt-resistant hydrogel evaporators for stable desalination. Here, inspired by tree transpiration and hierarchical porous structure, a 3D-printed bionic hydrogel evaporator (3DP-BHE) is designed for long-term solar desalination. Commercialized activated carbon (AC) is introduced into biomass starch skeleton as a solar light absorber to build 3DP-BHE in a cost-effective fashion ($10.14m-2 of total materials cost). The bionic tree leaf layer for 94.01% light absorption and timely vapor diffusion. The bionic tree trunk layer with 3D printed bimodal porous structure for water transfer, thermal isolation, and salt ions convection and diffusion. With the unique bionic structure, the 3DP-BHE achieves a stable evaporation rate of 2.13kgm-2h-1 at ≈90.5% energy efficiency under one sun (1kWm-2). During the 7-day desalination of 10wt.% brine, a steady evaporation rate of 1.98kgm-2h-1 is maintained with a record-high cost-effectiveness (195.3gh-1$-1) manner. This 3DP-BHE will open significant opportunities for affordable solar desalination systems on multiple scales, from individual households to off-grid communities.

Monitoring of Nitrogen Concentration in Soybean Leaves at Multiple Spatial Vertical Scales Based on Spectral Parameters.

Nitrogen is a fundamental component for building amino acids and proteins, playing a crucial role in the growth and development of plants. Leaf nitrogen concentration (LNC) serves as a key indicator for assessing plant growth and development. Monitoring LNC provides insights into the absorption and utilization of nitrogen from the soil, offering valuable information for rational nutrient management. This, in turn, contributes to optimizing nutrient supply, enhancing crop yields, and minimizing adverse environmental impacts. Efficient and non-destructive estimation of crop LNC is of paramount importance for on-field crop management. Spectral technology, with its advantages of repeatability and high-throughput observations, provides a feasible method for obtaining LNC data. This study explores the responsiveness of spectral parameters to soybean LNC at different vertical scales, aiming to refine nitrogen management in soybeans. This research collected hyperspectral reflectance data and LNC data from different leaf layers of soybeans. Three types of spectral parameters, nitrogen-sensitive empirical spectral indices, randomly combined dual-band spectral indices, and "three-edge" parameters, were calculated. Four optimal spectral index selection strategies were constructed based on the correlation coefficients between the spectral parameters and LNC for each leaf layer. These strategies included empirical spectral index combinations (Combination 1), randomly combined dual-band spectral index combinations (Combination 2), "three-edge" parameter combinations (Combination 3), and a mixed combination (Combination 4). Subsequently, these four combinations were used as input variables to build LNC estimation models for soybeans at different vertical scales using partial least squares regression (PLSR), random forest (RF), and a backpropagation neural network (BPNN). The results demonstrated that the correlation coefficients between the LNC and spectral parameters reached the highest values in the upper soybean leaves, with most parameters showing significant correlations with the LNC (p < 0.05). Notably, the reciprocal difference index (VI6) exhibited the highest correlation with the upper-layer LNC at 0.732, with a wavelength combination of 841 nm and 842 nm. In constructing the LNC estimation models for soybeans at different leaf layers, the accuracy of the models gradually improved with the increasing height of the soybean plants. The upper layer exhibited the best estimation performance, with a validation set coefficient of determination (R2) that was higher by 9.9% to 16.0% compared to other layers. RF demonstrated the highest accuracy in estimating the upper-layer LNC, with a validation set R2 higher by 6.2% to 8.8% compared to other models. The RMSE was lower by 2.1% to 7.0%, and the MRE was lower by 4.7% to 5.6% compared to other models. Among different input combinations, Combination 4 achieved the highest accuracy, with a validation set R2 higher by 2.3% to 13.7%. In conclusion, by employing Combination 4 as the input, the RF model achieved the optimal estimation results for the upper-layer LNC, with a validation set R2 of 0.856, RMSE of 0.551, and MRE of 10.405%. The findings of this study provide technical support for remote sensing monitoring of soybean LNCs at different spatial scales.

Factors influencing the variation in canopy light extinction coefficient (k) among pisifera parents of two oil palm origins

Summary The canopy light extinction coefficient (k) is defined as the exponential decline in the amount of light passing through the leaf layers as a function of leaf area index (LAI). This definition is standard in oil palm breeding trials and models of canopy photosynthesis, where k is sometimes assumed to have a fixed value. The present experiment aims to validate the alleged constancy of k. Therefore, k was inferred from the fractional transmission of photosynthetically active radiation (PAR) and LAI, as obtained from dura x pisifera test crosses of Nigeria and Ghana pisifera origins. The palms were planted at two densities (135 and 160 palms ha−1) in North Sumatra in 2010. At the age of 7.5 years after planting, the area of newly opened leaves approached a maximum. Transmission of PAR remained very low and was only weakly related to k. By contrast, LAI exerted a strong negative effect on k, which generated, under both densities, considerable differences in k between both origins and among pisifera within an origin. The assumption of applying a fixed k value for a certain genotype or palm density, as obtained during leaf expansion at closed canopy, may therefore not be realistic. The present study suggests that the relationship of k with LAI over time merits further investigation, starting just before canopy closure.

Nanocarrier foliar uptake pathways affect delivery of active agents and plant physiological response.

Layered double hydroxide (LDH) nanoparticles enable foliar delivery of genetic material, herbicides, and nutrients to promote plant growth and yield. Understanding the foliar uptake route of nanoparticles is needed to maximize their effectiveness and avoid unwanted negative effects. In this study, we investigated how delivering layered double hydroxide (d = 37 ± 1.5 nm) through the adaxial (upper) or abaxial (lower) side of leaves affects particle uptake, nutrient delivery, and photosynthesis in tomato plants. LDH applied on the adaxial side was embedded in the cuticle and accumulated at the anticlinal pegs between epidermal cells. On the abaxial side, LDH particles penetrated the cuticle less, but the presence of the stomata enables penetration to deeper leaf layers. Accordingly, the average penetration levels of LDH relative to the cuticle were 2.47 ± 0.07, 1.25 ± 0.13, and 0.75 ± 0.1 μm for adaxial, abaxial with stomata, and abaxial without stomata leaf segments, respectively. In addition, the colocalization of LDH with the cuticle was ∼2.3 times lower for the adaxial application, indicating the ability to penetrate the cuticle. Despite the low adaxial stomata density, LDH-mediated delivery of magnesium (Mg) from leaves to roots was 46% higher for the adaxial than abaxial application. In addition, adaxial application leads to ∼24% higher leaf CO2 assimilation rate and higher biomass accumulation. The lower efficiency from the abaxial side was, at least partially, a result of interference with the stomata functionality which reduced stomatal conductance and evapotranspiration by 28% and 25%, respectively, limiting plant photosynthesis. This study elucidates how foliar delivery pathways through different sides of the leaves affect their ability to deliver active agents into plants and consequently affect the plants' physiological response. That knowledge enables a more efficient use of nanocarriers for agricultural applications.

The Doubly Linked Tree of Singly Linked Rings: Providing Hard Real-Time Database Operations on an FPGA

We present a hardware data structure specifically designed for FPGAs that enables the execution of the hard real-time database CRUD operations using a hybrid data structure that combines trees and rings. While the number of rows and columns has to be limited for hard real-time execution, the actual content can be of any size. Our structure restricts full navigational freedom to every but the leaf layer, thus keeping the memory overhead for the data stored in the leaves low. Although its nodes differ in function, all have exactly the same size and structure, reducing the number of cascaded decisions required in the database operations. This enables fast and efficient hardware implementation on FPGAs. In addition to the usual comparison with known data structures, we also analyze the tradeoff between the memory consumption of our approach and a simplified version that is doubly linked in all layers.

Side Lighting of Red, Blue and Green Spectral Combinations Altered the Growth, Yield and Quality of Lettuce (Lactuca sativa L. cv. "Yidali") in Plant Factory.

A plant factory with artificial lighting (PFAL) usually uses top lighting for cultivation. The light from the upper part of the canopy cannot penetrate the entire lettuce canopy, however, resulting in uneven vertical spatial light in the canopy, and accelerating the senescence of both the bottom and side leaves of the plant canopy. Therefore, in this study, the performance of lettuce in hydroponics was investigated upon supplemental side lighting with different spectral LEDs in a PFAL. A set of short-term side lighting treatments, including no side lamps (CK), red (R), blue (B), red + blue (RB), and red + blue + green (RGB) LED lamps (150 μmol·m-2·s-1, respectively), was employed for an additional 2 h per day after normal top lighting for 6 days before harvest. The results showed that the lettuce canopy was relatively loose and had a large crown size under side lighting compared with CK. Side lighting, irrespective of spectral qualities, significantly increased the fresh weight, and the R, B, RB, and RGB treatments increased the shoot fresh weight of lettuce plants by 34%, 19%, 31%, and 34%, and increased the fresh weight of leaf layer 2 by 50%, 17%, 44%, and 48%, respectively. The side lighting of different spectral qualities had a significant impact on the nutritional quality of the first row of lettuce at the edge of the top lighting illuminated area. Treatment B significantly promoted the chlorophyll content of leaf layer 3; the soluble sugar contents from leaf layer 1, 2, and 3; the starch contents in leaf layers 2 and 3; and the content of phenolics in the leaf layers 3; and significantly reduced the nitrate content in leaf layers 2 and 3. RGB significantly increased soluble sugar content by 91%, and the starch content in leaf layer 1, as well as the leaf chlorophyll and flavonoid content of leaf layer 3, while R had opposite effect completely. RB significantly increased the leaf chlorophyll content of leaf layer 3 and the nitrate content in leaf layer 1, but the overall effect was lower than that of RGB. In summary, side lighting of any type could effectively improve lettuce yield, solve the problem of inconsistent lettuce plant size caused by the edge effect of top lighting, and affect the nutritional quality of lettuce. B and RGB performed best. There was spatial response diversity of lettuce plants to side lighting spectral qualities.

Aphid Resistance Evaluation and Constitutive Resistance Analysis of Eighteen Lilies.

Lilies (Lilium spp.) are famous bulb flowers worldwide, with high ornamental value. Aphid damage has seriously constrained the development of the lily industry. In this study, the aphid resistance of 16 lily cultivars and 2 wild lily species was characterized in the field and greenhouse. Leaf color parameters, stomatal density and size, thickness of leaf layers, leaf waxy content, and leaf water content were determined to explore the constitutive resistance of lilies. The results show that there was a significant positive correlation between the number of aphids in the field and in the greenhouse (p ≤ 0.05, r = 0.47). This indicated that the level of aphid infestation in both the field and the greenhouse is generally consistent across different types of lily plants. Among these 18 lilies, 'Palazzo', 'Nymph', 'Cameleon' and L. lancifolium were resistant to A. gossypii, while 'Black Beauty' and 'Magnefique' had poor resistance. The correlation analysis results showed that the number of aphids was negatively correlated with leaf abaxial surface a*, stomatal size, water content, and thickness of leaf palisade tissue and positively correlated with leaf distal axial surface b*, C*, and waxy content. Among them, the correlation between the number of aphids and the thickness of leaf palisade tissue reached a significant level (p ≤ 0.05, r = -0.521). This indicated that the thickness of the palisade tissue of lily leaves might be an important factor influencing the proliferation of aphids. This study not only screened out aphid-resistant lilies but also established a crucial research foundation for the targeted breeding and molecular breeding of lilies with aphid resistance.

“A novel methodology for developing ultra-low adhesion leaf layers on a full-scale wheel/rail rig”

This paper explores a novel method for creating an ultra-low adhesion leaf layer on a rail using a full-scale wheel/rail rig. Ultra-low adhesion layers were generated using leaf powder for the first time on a linear full-scale rig. The layers are compared chemically and physically to other layers from the laboratory and field. Testing of the adhesion evolution of the leaf contaminated layers over 50 cycles is explored, and compared to dry and wet rails.