Nano Zinc-Oxide Enhanced Photosynthetic Apparatus and Photosystem Efficiency of Maize (Zea Mays L.) in Sandy-Acidic Soils

Conventional Zinc (Zn) fertilization (e.g., zinc sulfate) often leads to poor availability in soils. Zinc oxide nanoparticles (nano ZnO) can be a potential solution, but their effect on crop photosynthetic activity isn’t well documented. The effects of nano ZnO (50, 100, 150, 200 mg L-1) and application methods (seed-coating, soil-drench, and foliar-spray) in comparison with ZnSO4 recommended dose were evaluated for plant height, biomass, chlorophyll pigments and photosystem efficiency in a greenhouse pot experiment. 100 mg L-1 of nano ZnO significantly increased the chlorophyll (Chl.) a, b, a+b, carotenoids (x+c), a+b/x+c, SPAD, leaf Chl., total chlorophyll content plant-1, plant height and total biological yield (by 18-30%, 33-67%, 22-38%, 14-21%, 14-27%, 12-19%, 12-23% 58-99%, 6-11% and 16-20%, respectively) and reduced Chl. a/b (by 6-22%) over the other treatments (p<0.01) irrespective of application methods. Nano ZnO applied at 100 mg L-1 significantly increased photochemical quenching (qP) and efficiency of photosystem II (EPSII) compared to 150 and 200 mg L-1 regardless of application methods. The positive correlations between Chl. a and Chl. b (r2 0.90), Chl. a+b and x+c (r2=0.71), SPAD and Chl. a (r2=0.90), SPAD and Chl. b (r2=0.94) and SPAD and Chl. a+b (r2=0.93) indicates a uniform enhancement in chlorophyll pigments; SPAD value, qP, EPSII, and growth and yield parameters. This elucidates that the application of nano ZnO at 100 mg L-1 promotes corn biochemical health and photosynthesis, irrespective of the application method. These findings have a great propounding for improving plant growth through nano ZnO bio-fortification in acidic Spodosols.

Screening of Soybean Genotypes for Waterlogging Stress Tolerance and Understanding the Physiological Mechanisms

Waterlogging is a common form of abiotic stress that severely impedes global soybean production. Targeting this issue, an experiment was carried out at Sher-e-Bangla Agricultural University during August–November 2019 to screen out the waterlogging tolerance and yield performances of selected soybean genotypes. The experiment was laid out in a completely randomized design (CRD) with three replications consisting of 2 water levels (control and waterlogging) and 12 genotypes (Sohag, BARI Soybean-5, BINAsoybean-1, BINAsoybean-2, BINAsoybean-3, BINAsoybean-5, BINAsoybean-6, SGB-1, SGB-3, SGB-4, SGB-5, and GC-840). On the 15th day after sowing, plants were exposed to waterlogging for 12 days. Waterlogging remarkably declined the growth and yield of all the soybean genotypes compared to control. Reduced plant height, relative water content, above-ground fresh and dry weight, SPAD value, leaf area, number of leaves, branches, pods, seeds pod−1, 100-seed weight, and seed yield plant−1 were observed under waterlogging stress. Conversely, mortality rate and electrolyte leakage were increased under the same condition. The waterlogged plants showed delayed flowering and maturity compared with the control plants. However, among the 12 genotypes, Sohag, BARI Soybean-5, GC-840, BINAsoybean-1, and BINAsoybean-2 showed better waterlogging tolerance. These genotypes showed a greater number of adventitious roots in the base of their stem, which probably helped plants to thrive under waterlogging conditions.

Waterlogging tolerance and recovery capability screening in peanut: a comparative analysis of waterlogging effects on physiological traits and yield

Fifteen peanut varieties at the pod filling stage were exposed to waterlogging stress for 7 days, the enzyme activities and fluorescence parameters were measured after 7 days of waterlogging and drainage. The waterlogging tolerance and recovery capability of varieties were identified. After waterlogging, waterlogging tolerance coefficient (WTC) of relative electrolyte linkage (REL), malondialdehyde (MDA) content, superoxide dismutase (SOD) activity, and catalase (CAT) activity, non-photochemical quenching (NPQ) and photochemical quenching (qL) of leaves of most peanut varieties were increased, while the WTC of the soil and plant analysis development (SPAD) value, PS II actual quantum yield (ΦPS II), maximum photochemical efficiency (Fv/Fm) were decreased. After drainage, the WTC of REL, MDA content, SOD and CAT activity of leaves were decreased compared with that of after waterlogging, but these indicators of a few cultivars were increased. ΦPS II, Fv/Fm and qL can be used as important indexes to identify waterlogging recovery capability. There was a significant negative correlation between recovery capability and the proportion of reduction in yield, while no significant correlation was found between waterlogging tolerance and the proportion of reduction in yield. Therefore, it is recommended to select varieties with high recovery capability and less pod number reduction under waterlogging in peanut breeding and cultivation.

Effect of the Biofertilizer (Azolla pinnata) in Combination with Inorganic Fertilizers on Growth and Yield of Rice

This study was conducted at Malaysia Agriculture Research and Development Institute (MARDI), Seberang Perai, Penang (Malaysia), that aims to examine the impacts of the application of Azolla pinnata on the growth and performance of rice of the MR 297 variety. The experiment consisted of five treatments: PK + Azolla (T1); NP + Azolla (T2); NK + Azolla (T3); NPK-Control (T4), and Azolla only (T5). Each treatment had four replicates. The experimental design used was a complete randomized block design (RCBD), and all data collected were analyzed using one-way ANOVA with a statistically significant 0.05% test. For the average soil analysis between the beginning and end, all soil analyses showed decreased soil properties except total N and organic carbon. There is a significant effect on the tiller, panicles, yields, plant height, and SPAD value in crop growth performance. There was no significant effect observed on N and P among plant nutrients. In contrast, there was a significant treatment effect on K. This study concluded that the soil treated with NK + Azolla showed a comparable result with soil treated with inorganic fertilizer only for the total yield.

EVALUATING THE ECOPHYSIOLOGY OF SURVIVAL FOR MAPANIA CUSPIDATA (MIQ.) UITTIEN (CYPERACEAE) TRANSPLANTATION

SHABDIN, Z., NORI, H., MEEKIONG, K. & FAIZ, M. F. M. 2021. Evaluating the ecophysiology of survival for Mapania cuspidata (Miq.) Uittien (Cyperaceae) transplantation. Reinwardtia 20(2): 69–75. — This study aimed to investigate the ecology of the sedge Mapania cuspidata at three different locations in East Malaysia, namely Gunung Gading, Matang and Bengoh, and the survival of M. cuspidata transplanted in pots exposed to different light intensities in Universiti Malaysia Sarawak, East Malaysia. The highest species density was recorded in Matang with a total density of 1.98 individuals/ha followed by Bengoh (1.42) and Gunung Gading (0.96). In these locations, the soil pH ranged from 4.9 in Bengoh to 5.7 in Matang where as soil organic matter content was between 3.47% in Bengoh and 8.68% in Gunung Gading. The highest light intensity was recorded in Matang with 0.94 kLux, and produced plants with the highest chorophyll content (64.8 SPAD value). This study found that the transplanted M. cuspidata had 90% survival over a four month experiment, produced ~ 8 new leaves, took an average of 15.8 days to produce a new leaf and had a chlorophyll content of ~30.3 SPAD value regardless of the intensity of light where the plants were exposed to. The findings of this study suggests that M. cuspidata can grow well in any light conditions and therefore it is also possible to transplant and re-establish other Mapania species in new location. It is hoped that the initiative to relocateother Mapania species of concervation concern will be effective if adequate post-harvest handling methods are practiced.

Study on the Optimization of Hyperspectral Characteristic Bands Combined with Monitoring and Visualization of Pepper Leaf SPAD Value

Chlorophyll content is an important indicator of plant photosynthesis, which directly affects the growth and yield of crops. Using hyperspectral imaging technology to quickly and non-destructively estimate the soil plant analysis development (SPAD) value of pepper leaf and its distribution inversion is of great significance for agricultural monitoring and precise fertilization during pepper growth. In this study, 150 samples of pepper leaves with different leaf positions were selected, and the hyperspectral image data and SPAD value were collected for the sampled leaves. The correlation coefficient, stability competitive adaptive reweighted sampling (sCARS), and iteratively retaining informative variables (IRIV) methods were used to screen characteristic bands. These were combined with partial least-squares regression(PLSR), extreme gradient boosting (XGBoost), random forest regression(RFR), and gradient boosting decision tree(GBDT) to build regression models. The developed model was then used to build the inversion map of pepper leaf chlorophyll distribution. The research results show that: (1) The IRIV-XGBoost model demonstrates the most comprehensive performance in the modeling and inversion stages, and its , , and are 0.81, 2.76, and 2.30, respectively; (2) The IRIV-XGBoost model was used to calculate the SPAD value of each pixel of pepper leaves, and to subsequently invert the chlorophyll distribution map of pepper leaves at different leaf positions, which can provide support for the intuitive monitoring of crop growth and lay the foundation for the development of hyperspectral field dynamic monitoring sensors.

Rice Height Monitoring between Different Estimation Models Using UAV Photogrammetry and Multispectral Technology

Unmanned aerial vehicle (UAV) photogrammetry was used to monitor crop height in a flooded paddy field. Three multi-rotor UAVs were utilized to conduct flight missions in order to capture RGB (RedGreenBlue) and multispectral images, and these images were analyzed using several different models to provide the best results. Two image sets taken by two UAVs, mounted with RGB cameras of the same resolution and Global Navigation Satellite System (GNSS) receivers of different accuracies, were applied to perform photogrammetry. Two methods were then proposed for creating crop height models (CHMs), one of which was denoted as the M1 method and was based on the Digital Surface Point Cloud (DSPC) and the Digital Terrain Point Cloud (DSPT). The other was denoted as the M2 method and was based on the DSPC and a bathymetric sensor. An image set taken by another UAV mounted with a multispectral camera was used for multispectral-based photogrammetry. A Normal Differential Vegetation Index (NDVI) and a Vegetation Fraction (VF) were then extracted. A new method based on multiple linear regression (MLR) combining the NDVI, the VF, and a Soil Plant Analysis Development (SPAD) value for estimating the measured height (MH) of rice was then proposed and denoted as the M3 method. The results show that the M1 method, the UAV with a GNSS receiver with a higher accuracy, obtained more reliable estimations, while the M2 method, the UAV with a GNSS receiver of moderate accuracy, was actually slightly better. The effect on the performance of CHMs created by the M1 and M2 methods is more negligible in different plots with different treatments; however, remarkably, the more uniform the distribution of vegetation over the water surface, the better the performance. The M3 method, which was created using only a SPAD value and a canopy NDVI value, showed the highest coefficient of determination (R2) for overall MH estimation, 0.838, compared with other combinations.

Applying Spectral Fractal Dimension to Predict the SPAD Value of Rice Leaves Under Disease Stress

BackgroundThe chlorophyll content is a vital indicator for reflecting the photosynthesis ability of plants and it plays a significant role in monitoring the general health of plants. Since the chlorophyll content and the soil-plant analysis development (SPAD) value are positively correlated, it is feasible to estimate the SPAD value by calculating the vegetation indices (VIs) through hyperspectral images, thereby estimating the chlorophyll content. However, current indices simply adopted few wavelengths of the hyperspectral information, which may decrease the estimation accuracy. Besides, few researches explored the applicability of VIs over plant leaves under disease stress.MethodsIn this study, the SPAD value was estimated by calculating the fractal dimension of hyperspectral curves, ranging from 420 to 950 nm. The correlation between the SPAD value and wavelengths under disease stress was analyzed. In addition, a SPAD prediction model was built upon the combination of selected indices and 4 machine learning methods, including decision tree (DT), partial least square regression (PLSR), support vector regression (SVR), and back propagation neural network (BPNN). The performance of these models was compared through the correlation of determination, root mean square error, and relative error.ResultsThe results suggested that the SPAD value of rice leaves under different disease levels were sensitive to different wavelengths, meaning that the fixed wavelength selection in current indices may achieve poor estimation results. Compared with current VIs, a stronger positive correlation was detected between the SPAD value and our proposal, reaching an average correlation coefficient of 0.8263. For the prediction model, the one built with our proposal and SVR achieved the best performance, reaching R2, RMSE, and RE at 0.8752, 3.7715, and 7.8614%, respectively.ConclusionsThis work provides an in-depth insight for accurately and robustly estimating the SPAD value of rice leaves under disease stress, and our proposal is of great significance for monitoring the chlorophyll content in large-scale fields non-destructively.

Effects of Environmental Stresses (Heat, Salt, Waterlogging) on Grain Yield and Associated Traits of Wheat under Application of Sulfur-Coated Urea

Abiotic stresses, such as heat, salt, waterlogging, and multiple-stress environments have significantly reduced wheat production in recent decades. There is a need to use effective strategies for overcoming crop losses due to these abiotic stresses. Fertilizer-based approaches are readily available and can be managed in all farming communities. This research revealed the effects of sulfur-coated urea (SCU, 130 kg ha−1, release time of 120 days) on wheat crops under heat, salt, waterlogging, and combined-stress climatic conditions. The research was done using a completely randomized design with three replicates. The results revealed that SCU at a rate of 130 kg of N ha−1 showed a significantly (p ≤ 0.05) high SPAD value (55) in the case of waterlogging stress, while it was the lowest (31) in the case of heat stress; the control had a SPAD value of 58. Stress application significantly (p ≤ 0.05) reduced the leaf area and was the highest in control (1898 cm2), followed by salt stress (1509 cm2), waterlogging (1478 cm2), and heat stress (1298 cm2). A significantly (p ≤ 0.05) lowest crop yield was observed in the case of heat stress (3623.47 kg ha−1) among all stresses, while it was 10,270 kg ha−1 in control and was reduced up to 35% after the application of heat stress. Among all stresses, the salt stress showed the highest crop yield of 5473.16 kg ha−1. A significant correlation was observed among growth rate, spike length, yield, and physiological constraints with N content in the soil. The SCU fertilizer was the least effective against heat stress but could tolerate salt stress in wheat plants. The findings suggested the feasibility of adding SCU as an alternative to normal urea to alleviate salt stresses and improve wheat crop growth and yield traits. For heat stress tolerance, the applicability of SCU with a longer release period of ~180 days is recommended as a future prospect for study.

SEED GERMINATION BEHAVIOUR, SEEDLING GROWTH, MORPHO-PHYSIOLOGICAL AND YIELD ATTRIBUTES OF RICE GROWN IN CADMIUM-ADDED SOIL

An experiment was conducted to investigate the effect of different levels of cadmium (Cd) stress on germination, morphology, physiology and yield of rice. There were five treatments, viz. control (no Cd), 0.5 mM CdCl2, 1 mM CdCl2, 1.5 mM CdCl2 and 2 mM CdCl2, carried out by a randomized complete block design (RCBD) with three replications. Cadmium stress caused a significant reduction of plant height and tillers hill-1 in a dose-dependent manner. The highest decline of relative water content and SPAD value was found at 1.5 mM (11 and 16%) and 2 mM (14 and 19%) Cd stress compared to the control. The number of effective tillers hill-1, filled grains panicle-1, 1000-grain weight, length of panicle, grain yield and straw yield reduced significantly by 44, 32, 15, 24, 37 and 45%, respectively, over the control. Germination and seedling-related parameters were recorded 10 days after germination. The lowest germination percentage (27%), germination index (27%) and seedling vigour index (49%) were observed at the highest level of Cd stress in comparison to the control. Cadmium stress resulted in maximum abnormal seedlings and markedly reduced length of root and shoot as well as their fresh and dry weight. Root shoot ratio showed differential responses to Cd stress. Thus, it can be concluded that a higher level of Cd in soil has a detrimental effect on seed germination, morphology, physiology and yield of rice.