Soil Plant Analysis Development Research Articles

Combining features selection strategy and features fusion strategy for SPAD estimation of winter wheat based on UAV multispectral imagery

The Soil Plant Analysis Development (SPAD) is a vital index for evaluating crop nutritional status and serves as an essential parameter characterizing the reproductive growth status of winter wheat. Non-destructive and accurate monitorin3g of winter wheat SPAD plays a crucial role in guiding precise management of crop nutrition. In recent years, the spectral saturation problem occurring in the later stage of crop growth has become a major factor restricting the accuracy of SPAD estimation. Therefore, the purpose of this study is to use features selection strategy to optimize sensitive remote sensing information, combined with features fusion strategy to integrate multiple characteristic features, in order to improve the accuracy of estimating wheat SPAD. This study conducted field experiments of winter wheat with different varieties and nitrogen treatments, utilized UAV multispectral sensors to obtain canopy images of winter wheat during the heading, flowering, and late filling stages, extracted spectral features and texture features from multispectral images, and employed features selection strategy (Boruta and Recursive Feature Elimination) to prioritize sensitive remote sensing features. The features fusion strategy and the Support Vector Machine Regression algorithm are applied to construct the SPAD estimation model for winter wheat. The results showed that the spectral features of NIR band combined with other bands can fully capture the spectral differences of winter wheat SPAD during the reproductive growth stage, and texture features of the red and NIR band are more sensitive to SPAD. During the heading, flowering, and late filling stages, the stability and estimation accuracy of the SPAD model constructed using both features selection strategy and features fusion strategy are superior to models using only a single feature strategy or no strategy. The enhancement of model accuracy by this method becomes more significant, with the greatest improvement observed during the late filling stage, with R2 increasing by 0.092-0.202, root mean squared error (RMSE) decreasing by 0.076-4.916, and ratio of performance to deviation (RPD) increasing by 0.237-0.960. In conclusion, this method has excellent application potential in estimating SPAD during the later stages of crop growth, providing theoretical basis and technical support for precision nutrient management of field crops.

Effect of crop geometry and nitrogen levels on leaf chlorophyll content of cotton (Gossypium hirsutum) at different growth stages under rainfed Vertisols

A field experiment was conducted during the rainy (kharif) season of 2018–19 at the Regional Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Lam, Gunter, Andhra Pradesh on Vertisols under rainfed conditions. To study the effect of crop geometry and nitrogen levels on compact cotton (Gossypium hirsutum L.). Leaf chlorophyll content was measured with the Soil Plant Analysis Development meter (SPAD 502 Plus Chlorophyll Meter) at different crop growth stages. Among the various crop geometry studied, maximum chlorophyll (SPAD index) content, functional leaves per square meter and leaf area index (LAI) were recorded with close crop geometry 60 cm × 10 cm. Among nitrogen levels application of 180 kg N/ha recorded maximum chlorophyll content, functional leaves per square meter and LAI. Combined effect on crop geometry and nitrogen levels on chlorophyll content was recorded significant with closer geometry 60cm x10cm along with an application of 180kg N ha-1 at 90 days after sowing. Dry matter accumulation (kg/ha) at 30 DAS, 60 DAS, 90 DAS and at harvest was significantly affected by crop geometry and levels of nitrogen but not by their interaction.

Morphological and Physiological Responses of Two Penstemon Species to Saline Water Irrigation

Penstemon, with more than 250 species native to North America, holds significant aesthetic and ecological value in Utah, supporting diverse pollinators. Despite their significance, the survival of penstemon is threatened by challenges such as habitat loss, climate change, and Utah’s naturally high soil salinity. To address these challenges and understand their adaptability, this study evaluated the salt tolerance of two penstemon species [Penstemon davidsonii (Davidson’s penstemon) and Penstemon heterophyllus (foothill penstemon)] under controlled greenhouse conditions. The aim was to develop baseline information for nursery production and landscape use that utilize reclaimed water for irrigation. Plants were irrigated weekly with a nutrient solution at an electrical conductivity (EC) of 1.0 dS·m−1 as control or a saline solution at an EC of 2.5, 5.0, 7.5, or 10.0 dS·m−1 for 8 weeks. Half of the plants were harvested after four irrigation events, and the remaining plants were harvested after eight irrigation events. At harvest, visual rating (0 = dead and 5 = excellent without foliage salt damage), plant width, number of shoots, leaf area, shoot dry weight, leaf greenness [Soil Plant Analysis Development (SPAD)], stomatal conductance, and canopy temperature were collected to assess the impact of salinity stress. In both species, salt damage was dependent on the salinity levels and length of exposure. After four irrigation events, both species exhibited foliage damage that increased in severity with rising EC. The most severe damage was observed in plants receiving saline solution at an EC of 10.0 dS·m−1. After eight irrigation events, P. davidsonii exposed to a saline solution with an EC of 10.0 dS·m−1 received a visual rating of 0, whereas P. heterophyllus had a visual rating of 0.4. Both species exhibited salinity-induced effects, with variations observed in the specific parameters and the degree of response. Penstemon davidsonii exhibited significant salinity stress, as indicated by reduced leaf area, shoot dry weight, SPAD reading, and stomatal conductance with increasing EC of the saline solution. In addition, in both species, at both harvests, canopy temperatures increased either linearly or quadratically by 8% to 36% as the EC levels of the saline solution increased. These results indicate that P. davidsonii was more sensitive to salinity stress than P. heterophyllus.

Optimal Timing of Carrot Crop Monitoring and Yield Assessment Using Sentinel-2 Images: A Machine-Learning Approach

Remotely sensed images provide effective sources for monitoring crop growth and the early prediction of crop productivity. To monitor carrot crop growth and yield estimation, three 27 ha center-pivot irrigated fields were studied to develop yield prediction models using crop biophysical parameters and vegetation indices (VIs) extracted from Sentinel-2A (S2) multi-temporal satellite data. A machine learning (ML)-based image classification technique, the random forest (RF) algorithm, was used for carrot crop monitoring and yield analysis. The VIs (NDVI, RDVI, GNDVI, SIPI, and GLI), extracted from S2 satellite data for the crop ages of 30, 45, 60, 75, 90, 105, and 120 days after plantation (DAP), and the chlorophyll content, SPAD (Soil Plant Analysis Development) meter readings, were incorporated as predictors for the RF algorithm. The RMSE of the five RF scenarios studied ranged from 7.8 t ha−1 (R2 ≥ 0.82 with Scenario 5) to 26.2 t ha−1 (R2 ≤ 0.46 with Scenario 1). The optimal window for monitoring the carrot crop for yield prediction with the use of S2 images could be achieved between the 60 DAP and 75 DAP with an RMSE of 8.6 t ha−1 (i.e., 12.4%) and 11.4 t ha−1 (16.2%), respectively. The developed RF algorithm can be utilized in carrot crop yield monitoring and decision-making processes for the self-sustainability of carrot production.

Different Management of Nitrogen Application Affected Growth Characteristic of Maize (Zea mays L)

A field study was conducted during Kharif 2019-20 at Professor Jayashankar Telangana State Agricultural University (PJTSAU), Rajendranagar, Hyderabad, Telangana, India to evaluate different handheld decision support tools for precision nitrogen management in rainfed maize (Zea mays L.). The study utilized a randomized block design and was replicated three times. The eight treatments included applying nitrogen through the State-recommended dose of 200 kg ha-1 in three splits (RDN), using a leaf color chart (LCC) based on N at thresholds 3 and 4, using a soil plant analysis development (SPAD) chlorophyll meter based on N at thresholds 35 and 40, and using a Green Seeker based on N at NDVI 0.6 and 0.8 in comparison with RDN and absolute control. Based on Green Seeker NDVI at threshold 0.8, the results showed that applying nitrogen resulted in considerably greater yields for maize grain (8408 kg ha-1), stover (9923 kg ha-1), and harvest index (45.8%). with higher yield and growth parameter viz., test weight (36.3 g ), No. of grain rows  row-1 (36.7), cob length (18.9 cm), plant height (223.7 cm), leaf area (6385.75 cm2) and dry matter accumulation (18193 kg ha-1) as compared to RDN. Similarly, Green Seeker based N at NDVI 0.8 also registered higher net returns (Rs. 118961 ha-1) and B: C ratio (4.05).

Maximization of brackish water productivity for the sustainable production of striped catfish (Pangasianodon hypophthalmus) and grain sorghum (Sorghum bicolor (L.) Moench) cultivated under an integrated aquaculture-agriculture system.

Freshwater scarcity, salinity, and poor soil fertility are the major challenges affecting both food and feed productions in arid and semi-arid regions of the world. Utilization of brackish water in the production of saline-tolerant fish and valuable field crops under an integrated system is promising in the maximization of yield per crop. The aim of this study, therefore, was to (1) assess the effect of saline aquaculture wastewater on the growth, yield, forage quality, and nutritive composition of sorghum seeds and (2) assess the effect of different water qualities on the survival, growth performance, and health status of Pangasianodon hypophthalmus. The experiment was conducted in a randomized completely block design of four salinity treatments with three replicates, i.e., control (freshwater mixed with inorganic fertilizers), 5000ppm, 10,000ppm, and 15,000ppm. Our results indicated that although the control exhibited the highest growth (plant height, leaf number, internode number, leaf area, and soil-plant analysis development), grain, and forage yield, no significant differences were noted among the treatments. Likewise, no significant difference in the grain nutrient composition was noted among all the treatments. Assessment of the forage quality revealed improved crude protein content in the control compared to the saline treatments. However, no significant differences in the leaves and stalks fiber fractions were noted among all the treatments. Furthermore, rumen fermentation in terms of in vitro digestibility indicated no significant differences in the in vitro digestible dry matter, digestible organic matter, metabolic energy, net energy, microbial protein, short-chain fatty acids, and total dissolved nutrients among the treatments. However, rearing P. hypophthalmus in water salinities exceeding 10,000ppm reduced the growth performance and health status of fish. Therefore, the integration of sorghum and P. hypophthalmus production in water salinities not exceeding 5000ppm is a viable alternative to maximize brackish water productivity in freshwater-scarce regions.

Curd, seed yield and disease resistance of cauliflower are enhanced by oligosaccharides.

Oligosaccharides have been demonstrated as promoters for enhancing plant growth across several crops by elevating their secondary metabolites. However, the exploration of employing diverse oligosaccharides for qualitative trait improvements in cauliflower largely unknown. This study was intended to uncover the unexplored potential, evaluating the stimulatory effects of three oligosaccharides on cauliflower's curd and seed production. Two experiments were initiated in the early (15 September) and mid-season (15 October). Four treatments were implemented, encompassing a control (water) alongside chitosan oligosaccharide (COS 50 mg.L-1) with a degree of polymerization (DP) 2-10, oligo galacturonic acid (OGA 50 mg.L-1) with DP 2-10 and alginate oligosaccharide (AOS 50 mg.L-1) with DP 2-7. Oligosaccharides accelerated plant height (4-17.6%), leaf number (17-43%), curd (5-14.55%), and seed yield (17.8-64.5%) in both early and mid-season compared to control. These enhancements were even more pronounced in the mid-season (7.6-17.6%, 21.37-43%, 7.27-14.55%, 25.89-64.5%) than in the early season. Additionally, three oligosaccharides demonstrated significant disease resistance against black rot in both seasons, outperforming the control. As a surprise, the early season experienced better growth parameters than the mid-season. However, performance patterns remained more or less consistent in both seasons under the same treatments. COS and OGA promoted plant biomass and curd yield by promoting Soil Plant Analysis Development (SPAD) value and phenol content. Meanwhile, AOS increased seed yield (56.8-64.5%) and elevated levels of chlorophyll, ascorbic acid, flavonoids, while decreasing levels of hydrogen per oxide (H2O2), malondialdehyde (MDA), half maximal inhibitory concentration (IC50), and disease index. The correlation matrix and principal component analysis (PCA) supported these relations and findings. Therefore, COS and OGA could be suggested for curd production and AOS for seed production in the early season, offering resistance to both biotic and abiotic stresses for cauliflower cultivation under field conditions.

Better estimation of evapotranspiration and transpiration using an improved modified Priestly-Taylor model based on a new parameter of leaf senescence in a rice field

Evapotranspiration (ET) is at the heart of the global water, energy, and carbon cycles. As ET is difficult and expensive to measure, it is crucial to develop estimation models that can be widely applied. Currently, an improved Priestley-Taylor (PT) model considers soil moisture stress, temperature constraints, and leaf senescence; however, its parameter (fs) for simulating crop senescence is based on empirical values, making it difficult to apply to different varieties and complex external conditions and thus challenging to generalize. We improved the parameters fs in the original model based on the chlorophyll decomposition that accompanies crop senescence through easily observable SPAD values (Soil-Plant Analysis Development readings) in the field. We validated the improved model by obtaining ET of different rice varieties in 2022 and 2023 using the energy balance residual method at the Free Air Concentration Enrichment Experimental (FACE) Facility located in Yangzhou City, China. The results showed that the simulation of leaf senescence using SPAD values was feasible and could be extended to different varieties. The new model using improved leaf senescence parameter for estimating ET and transpiration (T) in three plots (2022 and 2023) exhibited slightly enhanced accuracy, particularly at the later stages of crop growth. Moreover, the higher the T/ET ratio of the cropland, the more significant the improvement. This new development enhances the ability of PT models to estimate ET and T using readily available field observations and provides some suggestions for wider application in the field for other crop species.

Effects of different healing agents on acclimatization success of in vitro rooted Garnem (Prunus dulcis × Prunus persica) rootstock

AbstractContinuing productivity of the acclimatization stage of plantlets means successful micropropagation. Due to the free water and high humidity in the culture container environment, poorly developed cuticle results in rapid water loss and drying of plantlets with watery stems and leaves, incomplete stomata, and large intercellular space. When plantlets are exposed to an environmental condition different from the culture medium, problems, such as rapid water loss and drying, may be encountered, and the survival rate of plantlets in vitro may be reduced. The aim of this study was to reduce the stress factors that occur during the acclimatization phase. For this reason, various healing agents have been used. Some of these compounds are ascorbic acid (AsA), salicylic acid (SA), and sodium nitroprusside (SNP). In the study, the response of AsA (100.0 and 200.0 mg L−1), SA (100.0 and 200.0 mg L−1), and SNP (100.0 and 200.0 µM) applications on growth parameters (survival rate (%), node count (pieces per plant), count of leaves (pieces per plant), shoot length (mm), and shoot diameter (mm)) and physiological variable (Soil Plant Analysis Development (SPAD)) were examined. The AsA100 (100.0 mg L−1 ascorbic acid), AsA200 (200.0 mg L−1 ascorbic acid), and SNP100 (100.0 µM sodium nitroprusside) applications resulted in an improvement in node count, leaf count per plant, shoot length, and shoot diameter parameters. The highest shoot length (60.50 ± 7.81 mm) and node count (16.83 ± 1.15 pieces per plantlet) were achieved with the AsA100 application. The maximum stem diameter (2.31 ± 0.37 mm) was determined with the SNP100 application. There were no statistically significant differences found in the survival rate, leaf count, and SPAD parameter. The current study determined that AsA, SA, and SNP applications were effective in regulating several growth parameters in Garnem plantlets and in reducing acclimation stress thereby facilitating adaptation to external conditions.

Genome-wide association studies of salinity tolerance in local aman rice.

The present study aimed to identify and characterize new sources of salt tolerance among 94 rice varieties from varied geographic origins. The genotypes were divided into five groups based on their morphological characteristics at both vegetative and reproductive stages using salinity scores from the Standard Evaluation System (SES). The experiment was designed as per CRD (Completely Randomized Design) with 2 sets of salinity treatments for 8 dS/meter and 12 dS/meter, respectively compared with one non-salinized control set. Using a Soil Plant Analysis Development (SPAD) meter, assessments of the apparent chlorophyll content (greenness) of the genotypes were done to comprehend the mechanism underlying their salt tolerance. To evaluate molecular genetic diversity, a panel of 1 K RiCA SNP markers was employed. Utilizing TASSEL 5.0 software, 598 filtered SNPs were used for molecular analysis. Whole-genome association studies (GWAS) were also used to investigate panicle number per plant (pn, tiller number per plant (till), SPAD value (spad), sterility (percent) (str), plant height (ph) and panicle length (pl. It is noteworthy that these characteristics oversee conveying the visible signs of salt damage in rice. Based on genotype data, diversity analysis divided the germplasm groups into four distinct clusters (I, II, III and IV). For the traits studied, thirteen significant marker-trait associations were discovered. According to the phenotypic screening, seven germplasm genotypes namely Koijuri, Asha, Kajal, Kaliboro, Hanumanjata, Akundi and Dular, are highly tolerant to salinity stress. The greenness of these genotypes was found to be more stable over time, indicating that these genotypes are more resistant to stress. Regarding their tolerance levels, the GWAS analysis produced comparable results, supporting that salinity-tolerant genotypes having minor alleles in significant SNP positions showed more greenness during the stress period. The Manhattan plot demonstrated that at the designated significant SNP position, the highly tolerant genotypes shared common alleles. These genotypes could therefore be seen as important genomic resources for accelerating the development and release of rice varieties that are tolerant to salinity.

The Application of Cyanobacteria as a Biofertilizer for Okra (Abelmoschus esculentus) Production with a Focus on Environmental and Ecological Sustainability

Cyanobacteria, an important addition to biofertilizers, are gaining popularity for their multifaceted benefits in sustainable agriculture and ecosystem restoration. However, harmful algal blooms (HABs) in freshwater, predominantly caused by cyanobacteria, prevent sunlight penetration into the water and develop hypoxic and anoxic conditions. We collected cyanobacteria slurry from Lake Jesup (Central Florida, USA), repurposed it as a biofertilizer, and incorporated it in a typical South Florida calcite soil for high-value okra (Abelmoschus esculentus; var: Clemson spineless) production. Experiments were conducted at the Organic Garden Shade House and Greenhouse located inside the main campus of the Florida International University (FIU), FL, USA. A two-year experiment with four different treatments was conducted, namely, (a) control (C; no fertilizer applied), (b) total synthetic (TS), (c) total biofertilizer (TB; only cyanobacteria biofertilizer was applied), and (d) half and half (HH; 50% biofertilizer + 50% synthetic fertilizer), which were arranged in a randomized complete block design (RCBD) with six replications for each treatment. Our results indicate that TB and TS produced about 29 to 33% higher SPAD (soil plant analytical development) readings than the control. The absence of interveinal chlorosis (yellowing of leaves) in the TB and HH treatments suggests that the cyanobacteria-based biofertilizer had a role in supplying one of the critical micronutrients, iron (Fe). Analysis of the biofertilizer indicated 2000 ppm Fe content, which directly supports our observation. Similarly, average plant height (61 cm), yield (130 gm per pot), and crop biomass (67 gm) productions were significantly higher in TB than in the control. Overall, this study documents the potential of cyanobacteria biofertilizers as a viable option compared to synthetic fertilizers for sustainable crop production and soil health improvement.

GmGLU1 and GmRR4 contribute to iron deficiency tolerance in soybean.

Iron deficiency chlorosis (IDC) is a form of abiotic stress that negatively impacts soybean yield. In a previous study, we demonstrated that the historical IDC quantitative trait locus (QTL) on soybean chromosome Gm03 was composed of four distinct linkage blocks, each containing candidate genes for IDC tolerance. Here, we take advantage of virus-induced gene silencing (VIGS) to validate the function of three high-priority candidate genes, each corresponding to a different linkage block in the Gm03 IDC QTL. We built three single-gene constructs to target GmGLU1 (GLUTAMATE SYNTHASE 1, Glyma.03G128300), GmRR4 (RESPONSE REGULATOR 4, Glyma.03G130000), and GmbHLH38 (beta Helix Loop Helix 38, Glyma.03G130400 and Glyma.03G130600). Given the polygenic nature of the iron stress tolerance trait, we also silenced the genes in combination. We built two constructs targeting GmRR4+GmGLU1 and GmbHLH38+GmGLU1. All constructs were tested on the iron-efficient soybean genotype Clark grown in iron-sufficient conditions. We observed significant decreases in soil plant analysis development (SPAD) measurements using the GmGLU1 construct and both double constructs, with potential additive effects in the GmRR4+GmGLU1 construct. Whole genome expression analyses (RNA-seq) revealed a wide range of affected processes including known iron stress responses, defense and hormone signaling, photosynthesis, and cell wall structure. These findings highlight the importance of GmGLU1 in soybean iron stress responses and provide evidence that IDC is truly a polygenic trait, with multiple genes within the QTL contributing to IDC tolerance. Finally, we conducted BLAST analyses to demonstrate that the Gm03 IDC QTL is syntenic across a broad range of plant species.

Integration of Unmanned Aerial Vehicle and Multispectral Sensor for Paddy Growth Monitoring Application: A Review

Using a conventional approach via visual observation on the ground, farmers encounter difficulties monitoring the entire paddy field area, and it is time-consuming to do manually. The application of unmanned aerial vehicles (UAVs) could help farmers optimise inputs such as water and fertiliser to increase yield, productivity, and quality, allowing them to manage their operations at lower costs and with minimum environmental impact. Therefore, this article aims to provide an overview of the integration of UAV and multispectral sensors in monitoring paddy growth applications based on vegetation indices and soil plant analysis development (SPAD) data. The article briefly describes current rice production in Malaysia and a general concept of precision agriculture technologies. The application of multispectral sensors integrated with UAVs in monitoring paddy growth is highlighted. Previous research on aerial imagery derived from the multispectral sensor using the normalised difference vegetation index (NDVI) is explored to provide information regarding the health condition of the paddy. Validation of the paddy growth map using SPAD data in determining the leaf’s relative chlorophyll and nitrogen content is also being discussed. Implementation of precision agriculture among low-income farmers could provide valuable insights into the practical implications of this review. With ongoing education, training and experience, farmers can eventually manage the UAV independently in the field. This article concludes with a future research direction regarding the production of growth maps for other crops using a variety of vegetation indices and map validation using the SPAD metre values.

Identification of quantitative trait loci (QTLs) regulating leaf SPAD value and trichome density in mungbean (Vigna radiata L.) using genotyping-by-sequencing (GBS) approach.

Quantitative trait loci (QTL) mapping is used for the precise localization of genomic regions regulating various traits in plants. Two major QTLs regulating Soil Plant Analysis Development (SPAD) value (qSPAD-7-1) and trichome density (qTric-7-2) in mungbean were identified using recombinant inbred line (RIL) populations (PMR-1×Pusa Baisakhi) on chromosome 7. Functional analysis of QTL region identified 35 candidate genes for SPAD value (16 No) and trichome (19 No) traits. The candidate genes regulating trichome density on the dorsal leaf surface of the mungbean include VRADI07G24840, VRADI07G17780, and VRADI07G15650, which encodes for ZFP6, TFs bHLH DNA-binding superfamily protein, and MYB102, respectively. Also, candidate genes having vital roles in chlorophyll biosynthesis are VRADIO7G29860, VRADIO7G29450, and VRADIO7G28520, which encodes for s-adenosyl-L-methionine, FTSHI1 protein, and CRS2-associated factor, respectively. The findings unfolded the opportunity for the development of customized genotypes having high SPAD value and high trichome density having a possible role in yield and mungbean yellow vein mosaic India virus (MYMIV) resistance in mungbean.

Evaluation of Heat Tolerance in Foliar Tissue ofAcerGenotypes

Abstract Background Extreme summer heat events in which temperatures exceed 40 °C are expected to increase in duration and intensity worldwide. Consequently, selecting heat-tolerant trees for future predicted climatic conditions will be one of the significant challenges for urban landscape managers. Method The effect of heat stress (44 °C for 4 hours) on chlorophyll variable:maximum fluorescence (Fv/Fm) ratios and Soil Plant Analysis Development (SPAD) values as measures of damage to the leaf photosynthetic system and leaf chlorophyll content was quantified in 8Acergenotypes (Acer pseudoplatanus‘Negenia’,A. pseudoplatanus‘Spaethii’,A. platanoides‘Royal Red’,A. platanoides‘Princeton Gold’,A. platanoides‘Emerald Queen’,A. platanoides‘Drummondii’,A. campestre,A. campestre‘Louisa Red Shine’). Results Fv/Fm ratios proved to be a sensitive indicator of heat damage and positively identified marked differences in tolerance to and recovery from heat damage between the 8Acergenotypes. Estimated leaf chlorophyll content (SPAD) was not sufficiently sensitive to distinguish differences in tolerance and recovery between genotypes. Conclusions Chlorophyll fluorescence Fv/Fm ratios, but not estimated leaf chlorophyll content (SPAD), offers a rapid screening technique for assessing the tolerance to and recovery from heat stress in leaf tissue of trees.

Growth, Yield and Quality of Rabi Groundnut (Arachis hypogaea L.) as Influenced by Sources of Calcium and Sulphur under Different Site - Specific Nitrogen Management in Rice-Groundnut Cropping System

The injudicious and imbalanced fertilizer use under the existing farming system necessitates the adoption of amelioration methods and balanced use of nutrients especially nitrogen (N). There is lack of information on effects of various sources of calcium and sulphur in groundnut along with balanced nitrogen management which needs to be addressed. A field experiment was carried out during 2020-21 and 2021-22 at Odisha University of Agriculture and Technology, Bhubaneswar, Odisha, India to study the growth, yield and quality parameters of groundnut as affected by site specific nitrogen management in rice and various sources of calcium and sulphur in groundnut. The experiment was laid out in split plot design with six main plot treatments i.e. Soil test based nitrogen (STBN) (100 kg N/ha), 75% N through STBN + 25% N through farmyard manure (FYM), 75% N through STBN + 25% N through vermicompost, N @ 20kg at basal and at leaf colour chart (LCC) < 3, N @ 20kg at basal and at chlorophyll value determined by soil plant analysis development (SPAD) < 35 and no nitrogen to rice during Kharif and three sub plot treatments i.e. lime @ 0.2 LR, gypsum @ 250 kg/ha and lime @ 0.2 LR + gypsum @ 250 kg/ha to groundnut during Rabi each in three replications. Application of 75% N through STBN + 25% N through vermicompost to preceding rice and lime @ 0.2 LR+ gypsum @ 250 kg/ha to groundnut crop resulted in highest plant height at harvest, number of nodules per plant and dry matter accumulation at harvest. Yield attributing characters like pods/plant, kernel/pod and 100 - pod weight of groundnut were highest due to application of 75% N through STBN + 25% N through vermicompost to preceding rice (17.86, 1.87 and 67.2 g, respectively) followed by 75% N through STBN + 25% N through FYM. Application of lime @ 0.2 LR + gypsum @ 250 kg/ha to groundnut recorded more pods/plant (16.86), kernels/pod (1.78) and 100 - pod weight (66.39 g). The treatment receiving 75% N through STBN + 25 % N through vermicompost in rice and application of lime @ 0.2 LR + gypsum @ 250 kg/ha to groundnut resulted significantly maximum pod yield (2,596 kg/ha and 2,291 kg/ha), haulm yield (4,554 kg/ha and 4,343 kg/ha) and harvest index (36.30% and 34.38%) in groundnut. Oil yield (682.2 kg/ha) in groundnut was recorded highest in the treatment lime @ 0.2 LR + gypsum @ 250 kg/ha followed by only gypsum @ 250 kg/ha application to groundnut. Similarly, application of lime @ 0.2 LR + gypsum @ 250 kg/ha to groundnut recorded highest protein yield (424.6 kg/ha).

Genome-wide association studies for earliness, MYMIV resistance, and other associated traits in mungbean (Vigna radiata L. Wilczek) using genotyping by sequencing approach.

Yellow mosaic disease (YMD) remains a major constraint in mungbean (Vigna radiata (L.)) production; while short-duration genotypes offer multiple crop cycles per year and help in escaping terminal heat stress, especially during summer cultivation. A comprehensive genotyping by sequencing (GBS)-based genome-wide association studies (GWAS) analysis was conducted using 132 diverse mungbean genotypes for traits like flowering time, YMD resistance, soil plant analysis development (SPAD) value, trichome density, and leaf area. The frequency distribution revealed a wide range of values for all the traits. GBS studies identified 31,953 high-quality single nucleotide polymorphism (SNPs) across all 11 mungbean chromosomes and were used for GWAS. Structure analysis revealed the presence of two genetically distinct populations based on ΔK. The linkage disequilibrium (LD) varied throughout the chromosomes and at r2 = 0.2, the mean LD decay was estimated as 39.59 kb. Two statistical models, mixed linear model (MLM) and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) identified 44 shared SNPs linked with various candidate genes. Notable candidate genes identified include FPA for flowering time (VRADI10G01470; chr. 10), TIR-NBS-LRR for mungbean yellow mosaic India virus (MYMIV) resistance (VRADI09G06940; chr. 9), E3 ubiquitin-protein ligase RIE1 for SPAD value (VRADI07G28100; chr. 11), WRKY family transcription factor for leaf area (VRADI03G06560; chr. 3), and LOB domain-containing protein 21 for trichomes (VRADI06G04290; chr. 6). In-silico validation of candidate genes was done through digital gene expression analysis using Arabidopsis orthologous (compared with Vigna radiata genome). The findings provided valuable insight for marker-assisted breeding aiming for the development of YMD-resistant and early-maturing mungbean varieties.

Stratified diagnosis of cotton canopy spectral characteristics based on CWT-SPA and its relationship with moisture, nitrogen, and SPAD values

ABSTRACT Cotton is an economically valuable crop worldwide, and accurate and rapid leaf moisture content, nitrogen content, and soil plant analysis development (SPAD) value estimations are crucial for cotton growth. In this study, high-resolution spectral data were collected for the Tahe 2 cotton variety in Alar City, Xinjiang. The raw spectra were preprocessed using four methods: first derivative, standard normal variate transformation, second derivative, and multiplicative scatter correction. Wavelet coefficients at multiple scales were generated from the raw spectra using a continuous wavelet transform (CWT) and CWT with first derivative (CWT-FD). A quantitative detection model combining CWT and CWT-FD with successive projection algorithm – partial least squares (SPA-PLS) was developed to estimate the leaf moisture content, nitrogen content, and SPAD values. The performances of the different scales and methods for estimating these parameters were compared. Six stratification methods were employed to determine the optimal modelling results and decomposition scales for the parameters under various stratification schemes. The results demonstrated that the CWT and CWT-FD methods significantly improved the accuracy of estimating cotton canopy spectral characteristics related to the parameters, surpassing that of conventional spectral processing methods. The mexh, db5, and db5 wavelet basis functions, along with scale 3, were identified as the optimal modelling choices for moisture content, nitrogen content, and SPAD values throughout the cotton plant growth period. Among the six vertical stratification structures of cotton, the CWT and CWT-FD methods, along with the three wavelet basis functions, achieved the best results for the three parameters in the upper layer. The optimal relative percent deviation values for the three parameters of typical leaves ranged from 1.603 to 2.016, indicating satisfactory modelling performance. These findings provide a theoretical foundation for accurately estimating leaf moisture content, nitrogen content, and SPAD values using spectral technology, enabling the simultaneous extraction and monitoring of multiple physiological indicators.

Response of Winter Wheat to Delayed Sowing and Varied Nitrogen Fertilization

Common wheat is one of the most important cereal crops in the world. In cultivation, winter, spring, and facultative varieties of this species are known. In wheat agronomy, timely sowing and optimal nitrogen fertilization are particularly crucial practices, as both significantly impact yield and grain quality. In a three-year field experiment, the response of the winter wheat variety RGT Kilimanjaro to two sowing dates (recommended and delayed by 30 days) and varied nitrogen fertilization levels (100 kg ha−1, 150 kg ha−1, and 200 kg ha−1) was investigated. It was shown that the difference in grain yield between 2021 and 2023 amounted to 0.74 kg ha−1. The application of 200 N kg ha−1 significantly increased the Soil Plant Analysis Development (SPAD) index and Leaf Area Index (LAI) compared to the variant with a delayed sowing date and a nitrogen dose of 100 kg ha−1. Yield components (number of spikes per square meter, thousand grain weight) and grain yield were highest when wheat was sown at the recommended date and with the application of either 150 or 200 N kg ha−1. The number of grains per spike significantly varied between the variant with the recommended sowing date and a dose of 200 N kg ha−1 and the variant with a delayed sowing date and a dose of 100 N kg ha−1. The lowest grain yield was obtained at a 30-day late wheat sowing date when applying 100 N kg ha−1. The protein content in the grain was primarily influenced by nitrogen fertilization. Therefore, it can be concluded that delaying the sowing date of winter wheat by 30 days results in a decrease in grain yield but can be compensated by increased nitrogen fertilization. The most favorable economic effects were achieved with the application of 150 N kg ha−1 at the recommended sowing date. Considering that high doses of nitrogen fertilization can have adverse effects on the natural environment, research in this area should be continued.

Precision agricultural technology for advanced monitoring of maize yield under different fertilization and irrigation regimes: A case study in Eastern Hungary (Debrecen)

Precision agricultural (PrA) technology relies on the utilization of special equipment to access real time observations on plant health status, chlorophyll, nitrogen content, and soil moisture content. In this research new PrA technology (i.e., SPAD (Soil Plant Analysis Development), and UAV-based NDVI (Unmanned Aerial Vehicle-based Normalized Difference Vegetation Index) were used to monitor maize yield based on different filed trials in eastern part of Hungary. Our study aimed to examine the utilization of PrA technology specifically SPAD and UAV-based NDVI measurements for monitoring maize GY under irrigated and rainfed experimental setups in Hungary with varied nitrogen treatment for the year 2022. The results showed that the SPAD increased in all treatments (14.7 %; p < 0.05) from V6–V8 in the rainfed treatments, decreased significantly (p < 0.05) by 13.9 % (R1) and 30.6 % (R3). However, implementation of irrigation significantly increased the SPAD values in majority of treatments. Also, results reveal that, under irrigated and rainfed conditions the highest UAV-based NDVI value (0.703, 0.642) was obtained in V12 (A120 treatment) and highest NDVI value (0.728, 0.662) was obtained in Vn (A120 treatment). Remarekedly, irrigation led to significant differences (p < 0.05) of UAV-based NDVI values compared with none irrigated. On the other hand, implementation of 120 kg N ha−1 before sowing led to highest GY, especially under irrigated conditions (8.649 Mg ha−1). The overall mean GY under rainfed treatment was 6.256 Mg ha−1, while under irrigated treatment it increased by 37.2 % and reached 8.581 Mg ha−1 (p < 0.05). In conclusion, PrA technology will support farmers in making informed decisions regarding fertilization strategies and timing, which will in turn maximize yield and minimize risk.