Row Spacing Research Articles

Review of Matrix Rank Constraint Model for Impulse Interference Image Inpainting

Camera failure or loss of storage components in imaging equipment may result in the loss of important image information or random pulse noise interference. The low-rank prior is one of the most important priors in image optimization processing. This paper reviews and compares some low-rank constraint models for image matrices. Firstly, an overview of image-inpainting models based on nuclear norm, truncated nuclear norm, weighted nuclear norm, and matrix-factorization-based F norm is presented, and corresponding optimization iterative algorithms are provided. Then, we use different image matrix low-order constraint models to recover satellite images from three types of pulse interference and provide our experimental visual and numerical results. Finally, it can be concluded that the method based on the weighted nuclear norm can achieve the best image restoration effect. The F norm method based on matrix factorization has the shortest computational time and can be used for large-scale low-rank matrix calculations. Compared with nuclear norm-based methods, weighted nuclear norm-based methods and truncated nuclear norm-based methods can significantly improve repair performance.

Hyperspectral Image Super-Resolution Based on Feature Diversity Extraction

Deep learning is an important research topic in the field of image super-resolution. Problematically, the performance of existing hyperspectral image super-resolution networks is limited by feature learning for hyperspectral images. Nevertheless, the current algorithms exhibit some limitations in extracting diverse features. In this paper, we address limitations to existing hyperspectral image super-resolution networks, focusing on feature learning challenges. We introduce the Channel-Attention-Based Spatial–Spectral Feature Extraction network (CSSFENet) to enhance hyperspectral image feature diversity and optimize network loss functions. Our contributions include: (a) a convolutional neural network super-resolution algorithm incorporating diverse feature extraction to enhance the network’s diversity feature learning by elevating the matrix rank, (b) a three-dimensional (3D) feature extraction convolution module, the Channel-Attention-Based Spatial–Spectral Feature Extraction Module (CSSFEM), to boost the network’s performance in both the spatial and spectral domains, (c) a feature diversity loss function designed based on the image matrix’s singular value to maximize element independence, and (d) a spatial–spectral gradient loss function introduced based on space and spectrum gradient values to enhance the reconstructed image’s spatial–spectral smoothness. In contrast to existing hyperspectral super-resolution algorithms, we used four evaluation indexes, PSNR, mPSNR, SSIM, and SAM, and our method showed superiority during testing with three common hyperspectral datasets.

Agroeconomic differences among alternative cotton row spacings and row patterns

AbstractCrop growth and development is affected by intraspecies competition. This study was conducted to determine whether cotton productivity and profitability could be manipulated through planting geometry. The effects of row spacing, planting pattern, and variety on cotton fruit distribution, yield, and net returns were investigated near Bella Mina, AL, on a Decatur silt loam (fine, kaolinitic, thermic Rhodic Paleudults); Jackson, TN, on a Calhoun silt loam (fine‐silty, mixed, active, thermic Typic Glossaqualfs); Starkville, MS, on a Leeper silty clay loam (fine, smectitic, nonacid, thermic Vertic Epiaquepts); and Stoneville, MS, on a Bosket very fine sandy loam (fine‐loamy, mixed, active, thermic Mollic Hapludalfs). For both the 76‐ and 97‐cm row spacing, transitioning from a solid to a 2 × 1 skip row pattern reduced cotton lint yield by 19%. Reduced lint yield in the 2 × 1 skip row pattern was attributed primarily to a 7% decrease in the number of Zone 1 and first‐position bolls. Consequently, planting on a solid rather than skip row pattern increased net returns by 21%. Planting cotton in either 76‐ or 97‐cm rows using a solid rather than skip row pattern likely increases crop productivity and profitability across the US cotton belt.

Extraction of Tobacco Planting Information Based on UAV High-Resolution Remote Sensing Images

Tobacco is a critical cash crop in China, so its growing status has received more and more attention. How to acquire accurate plant area, row spacing, and plant spacing at the same time have been key points for its grow status monitoring and yield prediction. However, accurately detecting small and densely arranged tobacco plants during the rosette stage poses a significant challenge. In Sichuan Province, the contours of scattered tobacco fields with different shapes are not well-extracted. Additionally, there is a lack of simultaneous methods for extracting crucial tobacco planting information, including area, row spacing, and plant spacing. In view of the above scientific problems, we proposed a method to extract the planting information of tobacco at the rosette stage with Unmanned Aerial Vehicle (UAV) remote sensing images. A detection model, YOLOv8s-EFF, was constructed for the small and weak tobacco in the rosette stage. We proposed an extraction algorithm for tobacco field area based on extended contours for different-shaped fields. Meanwhile, a planting distance extraction algorithm based on tobacco coordinates was presented. Further, four experimental areas were selected in Sichuan Province, and image processing and sample label production were carried out. Four isolated tobacco fields with different shapes in four experimental areas were used to preliminarily verify the effectiveness of the model and algorithm proposed. The results show that the precision ranges of tobacco field area, row spacing, and plant spacing were 96.51~99.04%, 90.08~99.74%, and 94.69~99.15%, respectively. And another two experimental areas, Jiange County, Guangyuan, and Dazhai County, Gulin County, and Luzhou, were selected to evaluate the accuracy of the method proposed in the research in practical application. The results indicate that the average accuracy of tobacco field area, row spacing, and plant spacing extracted by this method reached 97.99%, 97.98%, and 98.31%, respectively, which proved the extraction method of plant information is valuable.

Root spatial distribution and belowground competition in an apple/ryegrass agroforestry system

CONTEXTForestry and fruit industry is a unique and advantageous industry in Xinjiang, China, and it is an important channel for farmers to increase income. With limited land resources and a shortage of forage in southern Xinjiang, farmers began to establish a fruit-grass interplanting model to improve the comprehensive economic benefits of orchards. OBJECTIVEThe objective of this study was to explore the effects of apple/ryegrass intercropping system on root spatial distribution and competition, and to evaluate the performance of field microclimate, soil physical properties and productivity under intercropping. METHODSIn the study, three different planting patterns were designed: sole-cropped apple (The spacing of the rows of apple trees was 4.0 m, and the plant spacing was 1.0 m), sole-cropped ryegrass (Strip sowing, row spacing was 0.25 m), and apple/ryegrass intercropping (The distance from apple row to ryegrass row was 1.0 m). Two-year field experiments were conducted to measure the root length density (RLD), specific root length (SRL), interspecific competitiveness index, soil moisture content, organic matter content, air temperature, relative humidity, wind speed, yield, land equivalent ratio (LER) and aggressivity. RESULTS AND CONCLUSIONCompared with sole cropping, intercropping reduced the RLD of apple and ryegrass and increased the SRL of ryegrass. The competition space between apple and ryegrass was concentrated in the soil area of 100 cm horizontally and 0–20 cm vertically, and apple was more competitive than ryegrass. Intercropping increased the content of soil moisture and organic matter and improved the microclimate of farmland, decreased the air temperature, increased the relative humidity of an orchard, and decreased wind speed. Although intercropping reduced ryegrass and apple yield, land equivalent ratio (LER) was 1.27–1.30, indicating that intercropping improved land use efficiency. Root competition led to an uneven distribution of root length density (RLD) and specific root length (SRL). The plasticity of root morphology and root spatial distribution was key to adapting to competition and maximizing the absorption of water and nutrients in apple/ryegrass agroforestry systems. SIGNIFICANCEApple/ryegrass intercropping system maximizes resource utilization and reduces interspecies resource competition. It improved land use efficiency, improved the comprehensive benefits of fruit and grass production.

Nitro Indole Derivatives as Novel Dual-Polarity Matrices for MALDI Mass Spectrometry and Imaging with Broad Applications.

A new matrix framework is presented in this study for the improved ionization efficiency of complex mixtures by matrix-assisted laser desorption ionization (MALDI) mass spectrometry/imaging. Five nitro indole (NI) derivatives [3-methyl-4-nitro-1H-indole (3,4-MNI), 3-methyl-6-nitro-1H-indole (3,6-MNI), 2,3-dimethyl-4-nitro-1H-indole (2,3,4-DMNI), 2,3-dimethyl-6-nitro-1H-indole (2,3,6-DMNI), and 4-nitro-1H-indole (4-NI)] were synthesized and shown to produce both positive and negative ions with a broad class of analytes as MALDI matrices. NI matrices were compared to several common matrices, such as 2,5-dihydroxybenzoic acid (DHB), alpha-cyano-4-hydroxylcinnamic acid (CHCA), sinapinic acid (SA), 1,5-diaminonaphthelene (1,5-DAN), and 9-aminoacridine (9-AA), for the analysis of lipid, peptide, protein, glycan, and perfluorooctanesulfonic acid (PFOS) compounds. 3,4-MNI demonstrated the best performance among the NI matrices. This matrix resulted in reduced ion suppression and better detection sensitivity for complex mixtures, for example, egg lipids/milk proteins/PFOS in tap water, while 2,3,6-DMNI was the best matrix for blueberry tissue imaging. Several important aspects of this work are reported: (1) dual-polarity ion production with NI matrices and complex mixtures; (2) quantitative analysis of PFOS with a LOQ of 0.5 ppb in tap water and 0.05 ppb in MQ water (without solid phase extraction enrichment), with accuracy and precision within 5%; (3) MALDI imaging with 2,3,6-DMNI as a matrix for plant metabolite/lipid identification with ionization enhancement in the negative ion mode m/z 600-900 region; and (4) development of a thin film deposition under/above tissue method for MALDI imaging with a vacuum sublimation matrix on a high-vacuum MALDI instrument.

Performance of castor-based intercropping in semi-arid zone of Haryana

To enhance the productivity of castor per unit area and over time, a study was conducted during the kharif 2020-21 season at the Regional Research Station, CCS HAU, Bawal,. The study aimed to evaluate the compatibility, production potential, and optimal row proportions of component crops in intercropping systems involving castor. The field investigation was carried out to identify suitable intercrops for maximizing castor yield and analyse the economic viability of various treatments under two different row spacing for castor: 150 cm and 200 cm. The results indicated that the highest castor seed and stalk yield were achieved in sole castor (3,879 kg/ha and 5,656 kg/ha, respectively) with 200 cm row spacing, a similar performance was observed with a 150 cm row spacing. Further, intercropping of castor (150 cm) + mungbean (1:2) recorded higher seed yield (3,547 kg/ha) and stalk yield (5,248 kg/ha), highest castor equivalent yield (4,220 kg/ha) and land equivalent ratio (1.53) and resulted in higher economic returns with a benefit-cost ratio of 3.78.

Effects of soil physicochemical environment on the plasticity of root growth and land productivity in maize soybean relay strip intercropping system.

Soil is a key foundation of crop root growth. There are interactions between root system and soil in multiple ways. The present study aimed to further explore the response of root distribution and morphology to soil physical and chemical environment under maize (Zea mays L.) soybean (Glycine Max L. Merr.) relay strip intercropping (MS) An experiment was carried out aiming to examine the effects of nitrogen (N) applications and interspecific distances on root system and soil environment in MS. The two N application levels, referred to as no N application (NN) and conventional N application (CN), were paired with different interspecific distances: 30, 45 and 60 cm (MS30, MS45 and MS60) and 100 cm of monoculture maize and soybean (MM/SS100). The results demonstrated that MS45 increased the distribution of soil aggregates (> 2 mm) near the crop roots and maize soil nutrients status, which increased by 20.3% and 15.6%. Meanwhile, MS reduced soil bulk density, increased soil porosity and improved soil oxygen content. Optimization of the soil environment facilitated root growth. The MS45 achieved a better result on root distribution and morphology than the other configuration and also increased land productivity. Relay intercropped soybean with maize in interspecific row spacing of 45 cm, improved soil physicochemical environment, reshaped root architecture and optimized root spatial distribution of crops to achieve greater land productivity. © 2024 Society of Chemical Industry.

RSM and ANN Modeling of Camelina (Camelina sativa L. Crantz) Seed Yield as Affected by Nitrogen, Sulfur, Cow Manure, and Row Spacing

Camelina [Camelina sativa (L.) Crantz] is an annual versatile oilseed crop of the Brassicaceae family, with an increasingly cultivated area. Predicting camelina seed yield response to fertilization and planting density is of great importance in understanding production potential and management planning. Therefore, the current study aimed to estimate the seed yield of camelina by response surface methodology (RSM) and artificial neural network (ANN) as affected by different levels of planting row spacing and nitrogen (N), sulfur (S), and cow manure (CM) fertilization. The experiment was conducted in two growing years of 2019–2020 and 2020–2021, based on a central composite design with four factors including row spacing (15–35 cm), N (0–200 kg ha−1), S (0–100 kg ha−1), and CM (0–40 t ha−1). The RSM models for seed yield versus fertilization and row spacing factors in both years were statistically significant and had an acceptable predictive ability. Camelina seed yield decreased with increasing row spacing but showed a positive response to increasing the amount of N, S, and CM fertilizers. Comparing the performance of the models showed that, although the RSM models were significant and had the necessary efficiency in predicting camelina seed yield, the ANN models were more accurate. The performance criteria of coefficient of determination (R2), root mean square error (RMSE), standard error of prediction (SEP), mean absolute error (MAE), and Akaike information criterion (AICc) averaged over the two years for the RSM model were 0.924, 51.60, 5.51, 41.14, and 394.05, respectively, and for the ANN model were 0.968, 32.62, 3.54, 19.55, and 351.33, respectively. Based on the results, the ANN modeling can be used in predicting camelina seed yield in field conditions with more confidence than the RSM technique.

Glaucoma Detection Based on Texture Feature of Neuro Retinal Rim Area in Retinal Fundus Image

One method for detecting glaucoma is by comparing ratios in the area of neuroretinal rim. Comparing area ratios in the neuroretinal rim is difficult for ophthalmologists since it requires high accuracy and is highly dependent on the patient's retinal condition. In this study, we sought to perform neuro retinal rim feature extraction based on histogram and gray level co-occurrence matrix (GLCM) of normal retinal images and glaucoma, automatically distinguish between normal eyes and eyes with glaucoma, and evaluate the method's validity using the measures of accuracy, sensitivity, and specificity We adopted a machine learning approach in conducting automatic feature extraction of the retinal rim through three main stages: 1) image acquisition, 2) pre-processing, and 3) classification. We used a dataset from RIM-ONE for normal eyes images and DRISTHI-GS for glaucoma images.Classification was carried out on 154 images (80 images for glaucoma images and 74 images for normal images). Regarding true positive, false negative, false positive, and true negative, we examined the sensitivity, specificity, and accuracy of automatic extraction and classification. The highest findings are 96.10%, 98.75%, and 93.24%, respectively. This study showed that automatic texture features and classification are possible, accurate and important in detecting glaucoma.

Sensitivity of littleseed canary grass populations from Punjab, India, to clodinafop‐propargyl and isoproturon

AbstractLittleseed canary grass (Phalaris minor Retz.) is one of the most prevalent and troublesome annual grass weed species in wheat across the Indo‐Gangetic plains (IGP) of India, including Punjab. Littleseed canary grass has evolved resistance to different herbicide sites of action in the IGP region. A targeted field survey was conducted in 2018 and 2019 for seed collection of littleseed canary grass populations (total 94) across different districts of Punjab state prior to wheat harvest. The main objective of this research was to characterize the sensitivity response of collected littleseed canary grass populations to clodinafop‐propargyl (CP) and isoproturon (IPU) herbicides in whole‐plant dose‐response assays. Among all tested populations, 68 were found to be highly sensitive to CP, whereas all 94 populations were sensitive to IPU. Based on a 50% reduction in shoot dry biomass (GR50 values) and estimated sensitivity index (SI), 26 populations exhibited reduced sensitivity (SI of 2.2–4.4) to CP herbicide. The results also revealed that the littleseed canary grass populations with reduced sensitivity (SI ≥ 2.2) to CP had high sensitivity to IPU herbicide. Overall, these results suggested a high prevalence of littleseed canary grass populations with reduced sensitivity to CP herbicide in Punjab state. Diversified weed management strategies, including the use of alternative herbicides (both preemergence and postemergence), cultural (no‐till drill for wheat sowing and narrow row spacing), and mechanical (cutting of littleseed canary grass panicles prior to wheat harvest) practices should be adopted to control littleseed canary grass populations with reduced sensitivity to CP.

Medical image encryption algorithm based on a new five-dimensional multi-band multi-wing chaotic system and QR decomposition

In this study, we propose a medical image encryption algorithm based on a new five-dimensional (5D) multi-band multi-wing chaotic system and QR decomposition. First, we construct a new 5D multi-band multi-wing chaotic system through feedback control, which has a relatively large Lyapunov exponent. Second, we decompose the plaintext image matrix and chaotic sequence into an orthogonal matrix and upper triangular matrix using QR decomposition. We multiply the orthogonal matrix decomposed from the original image by the orthogonal matrix decomposed from the chaotic sequence. In this process, we use the chaotic sequence to control left and right multiplication. Simultaneously, we chaotically rearrange the elements in the upper triangular matrix using the improved Joseph loop and then multiply the two resulting matrices. Finally, we subject the product matrix to bit-level scrambling. From the theoretical analysis and simulation results, we observed that the key space of this method was relatively large, the key sensitivity was relatively strong, it resisted attacks of statistical analysis and gray value analysis well, and it had a good encryption effect for medical images.

Sunflower genotype performance in different spacing in the northeast for Rio Grande do Sul

The sunflower productivity development is conditionate to the harvest period, density, seeding spacing, genotype, soul fertility and hydric availability. This work evaluated the adaptability and stability of 14 sunflower genotypes in the Northwest region of RS, in different row spacing. The experiment was carried in Frederico Westphalen, in the 2019/2020 harvest, with a randomized block design in a 14x2 two-factor scheme, with 14 cultivars and two spacing. Plants were sampled between the useful samples for its evaluations of: Plant height; Chapter diameter; Stem diameter; Thousand weight seeds; Grain production. The spacing of 0.90 meters provided greater chapter size. When analyzed the cultivars production between spacing, is noticeable that for spacing of 0.45 meters, cultivar 1 differed from the others, obtaining the highest productivity 1.93 ton.ha-1, and cultivar 7 the lowest productivity 0 .64 ton.ha-1, a reduction of 66.8%. The variable PMS presented better results in the spacing of 0.90 meters. Cultivar 9 showed the highest values in both spacing. The spacing between rows did not influence the variables of plant height and stem diameter for the different sunflower cultivars.

Effect of Row Spacing and Weed Management Practices on Growth and Yield Components of Tomato (Solanum Lycopersicum L.) in Yola, North-Eastern Nigeria

Field trial was conducted during 2020 and 2021 dry seasons at experimental farm site of the Department of Crop Production and Horticulture, Modibbo Adama University, Yola to study the Effect of row spacing and some weed management practices on growth and yield components of Tomato (Solanum lycopersicum L) in Yola north-eastern Nigeria. The experiment was layout in a split plot arrangement of a Randomize Complete Block Design (RCBD) with (5) treatments Zero weeding (Control), Weedy check (Weeding at 2 and 4 Weeks After Transplanting), Maize straw at 1.0 kg m-1, S-metolachlor at 1.5 kg ha-1 and Pendimethalin at 1.44 kg ha-1) replicated three (3) times. Row spacing of 40x40cm, 60x60cm and 80x80cm was assigned to main plot while the different weed management treatments were assigned to sub-plot. The parameters measured on the crop include tomato plant height, number of branches per tomato plant, number of tomato fruits per plant. And weed parameters measured were number of broadleaf weeds/m2, grasses/m2, sedges/m2, total weed density/m2, weeds dry weight/m2, weed control efficiency (%) and weed index at harvest. The data collected were analyzed statistically using analysis of variance (ANOVA) and Duncan’s Multiple Range Test to separate the means at 5% level of probability. The results shows significant differences on plant height of tomato. Weedy check and 40cm row spacing recorded the tallest tomato plant heights of (18.54) at 2 WAT in 2020 while the tallest plant, was recorded at the interaction between weedy check and 60 cm row spacing of (22.58 cm) in 2021. The highest number of branches for the two experimental years of 2020 and 2021, were recorded at the interaction between 40 cm row spacing and weedy check treatment of (7.17) and (11.50), compared with Pendimethalin that recorded the lowest tomato plant heights, number of branches of (1.00) and (2.00) at 4 & 5 WAT. Similarly, the result for weed parameters also indicated that weedy check and 40cm row spacing has the lowest weed density m-2 of (1.84) at 30 days after application in 2020 and (1.77) in 2021 compared to Zero weeding plot and 80cm row spacing that recorded with the highest weed density of (7.04) & (7.16) for both 2020 and 2021 experimental years, also the percentage of weed dry matter. Weedy check also recorded highest weed control efficiency and weed index compared with remaining treatments. Therefore, the finding of this work said “weedy check treatment and 40 cm x 40cm row spacing were the best among weed management practice and row spacing” and are recommended for use as an alternative to the use of herbicide and 60 cm x 60 cm row spacing for effective weed control and maximum yield output of the tomato production in Yola, Nigerian.

BIOMETRIC PARAMETERS OF SAFFLOWER (CARTHAMUS TINCTORIUS L.) UNDER THE INFLUENCE ON SEEDING RATE AND ROW SPACING

The aim of the present work was to establish the peculiarities of the formation of biometric parameters of safflower varieties depending on the influence of the elements of cultivation technology – the seeding rate and the row spacing in the conditions of the Right Bank Forest Steppe of Ukraine. Methods. This study was conducted in the field of the Agronomic Research Station of the National University of Life and Environmental Sciences of Ukraine in the years 2021-2023 on typical low-humus soils. The scheme of the three-factor field experiment was made to study the influence of the following factors: factor A – varieties “Dobrynia” and “Soniachnyi”, factor B – row spacing: 19, 38 and 57 cm, factor C – seeding rate: 100, 200 and 300 thousand seeds/ha. Results. It is established that the row spacing of 19 cm and a seeding rate of 300 thousand seeds/ha contributed to the formation of a better height of safflower plants than on the variants with a row spacing of 38 and 57 cm, while the plants did not overgrow under such conditions. It was investigated that the number of heads was higher in both varieties with the row spacing of 38 cm, at the same time the average number of heads of the variety “Dobrynia” was made 20,2-22,2, and of the variety “Soniachnyi” – 19,2-22,1. The mass of 1000 seeds was higher with a row spacing of 57 cm, and for “Dodrynia” variety in average it was made 47,7 g, for “Soniachnyi” variety – 49,2 g. For “Dobrynia” variety the number of seeds per plant under the seeding rate of 100 thousand seeds/ha and row spacing of 19 cm was made 450,9 and for “Sonyachnyi” variety the number of seeds per plant under the seeding rate of 100 thousand seeds/ha and row spacing of 38 cm was made 455,4. On the same variants of the experiment, the seed weight per plant was made 20,6 and 21,1 g/plant, which corresponded to the best indicators in context of the variants. Conclusions. It has been studied that the formation of plant height, the number of heads and the mass of 1000 seeds is influenced by the row spacing in the range of 53.2-68.9%, and varietal peculiarities determine the limits of deviations of the characteristics by 13-29.8%. At the same time, the seeding rate had a slight effect on the studied indicators. In contrast to these characteristics, the number of seeds per plant and the weight of seeds per plant significantly depend on the seeding rate of safflower (at the level of 71.3-78.7%), while the row spacing affects only 14.6-22.6 %, and the variety has no significant effect on these parameters.

Effect of Plant Thickness and Cotton Row Spacing on Dry Mass Accumulation

In thi article, the medium-fiber cotton variety “Ravnaq-1” was processed at different 60 cm (control), 70 cm, and 76 cm row spacings in a cultivator adopted (in Uzbekistan) and a milling cultivator with a 76 cm row spacing, along with the theoretical seedling thickness. The analysis results of the scientific research on dry mass accumulation of cotton leaving 90-100 thousand bushels/ha and 120-130 thousand bushels/ha are presented. In the conducted research, the dry mass of one cotton bush in 2020 was 118.1-97.6 grams, in 2021 it was 131. It was 2-107.5 grams. That is, when the number of saplings is large, the dry mass of one plant decreases, when analyzed per hectare, it was found that higher dry mass was accumulated in all variants when the theoretical thickness of seedlings was 90-100 thousand bush/ha, when it was 120-130 thousand bush/ha. The highest rate of dry mass accumulation per bush in different row spacings was observed in both years of the study in the case of milling cultivator with a row spacing of 76 cm and theoretical seedling thickness of 90-100 thousand bush/ha, proportionally 138.9-151 It was .5 grams. It was found that this indicator accumulated more dry mass by 20.8-41.3 grams in the first year of the study than the control variants, and by 20.3-44 grams in the second year.

МЕРЫ БОРЬБЫ С СОРНОЙ РАСТИТЕЛЬНОСТЬЮ НА ПОСЕВАХ СОИ

In the forest-steppe zone of the Republic of North Ossetia-Alania on soybean crops (Iriston varieties), the effect of the soil herbicide Harness and insurance herbicides Galaxy Top, Illoxan, Frontier was studied. The aim of the research was to study the effect of various herbicides on the contamination of crops and the species composition of weed vegetation of promising soybean varieties in the conditions of the forest-steppe zone of the Russian Federation. Scientific novelty of research. The influence of various herbicides on the growth, development and productivity of promising soybean varieties has been studied; the effect of herbicides on the contamination of crops has been shown; The removal of basic nutrients by individual species of weeds has been established. Every year, more and more new herbicides appear on the market, so studying the properties of herbicides and their effect on weeds is an urgent task. The methodology. On the leached chernozems of the forest-steppe zone of the Russian Federation-Alania in 2020-2022, on the experimental fields of the SCNIIGPSH VNC RAS. The sowing method is wide–row (row spacing – 45 cm), with a seeding rate of 400 thousand germinating seeds per 1 hectare. The research area is hot, mostly well-humidified. The sum of temperatures is 3000-3200 °C. The climate of the described territory is continental, the absolute annual amplitude of air temperature fluctuations is 64 ° C. On the territory of the experiment, the soil is represented by medium-sized, heavy-loamy leached chernozem, underlain by pebbles. The soil is mechanically loamy, with a depth that turns into light and medium loamy- rocky. The authors found that chemical protection of crops from weeds in the forest-steppe zone should be carried out with combinations of herbicides Pivot 0.9 + Bazagran 1.1. At the same time, weed death reaches from 79.4 to 92.9%. After harvesting soybeans, the soil is quite suitable for the cultivation of any agricultural crop, since (in specified doses) herbicides do not accumulate in products and are safe for the environment.

Desempenho agronômico do amaranto no semiárido em função do arranjo espacial

ABSTRACT The potential effects of climate change on agricultural yields require a greater understanding of cropping systems that include underutilized agricultural crops with greater adaptive capacity to water and thermal stresses, such as grain amaranth (Amaranthus sp.). The aim of this work was to evaluate how the planting arrangement affects the agronomic performance of grain amaranth BRS Alegria (Amaranthus cruentus L.) grown under semi-arid conditions. One experiment was carried out in a complete randomized block design with five repetitions in a 2 x 3 factorial scheme (two row spacings - 30 and 40 cm; three plant spacings - 20; 30 and 40 cm); in two crop years, 2019 and 2020 in the municipality of Pentecoste, CE, Brazil. The evaluated characteristics were plant height, stem diameter, number of leaves, fresh matter yield, aboveground biomass yield (dry weight), grain yield, thousand-grain weight, lipid content, and harvest and lodging indexes. The evaluated planting arrangements did not affect plant height and number of leaves, but did affect stem diameter and lodging index, as the 40 cm plant spacing resulted in greater stem diameter and lower lodging index. Narrow spacing (30 x 20 cm) resulted in a higher lodging index but also resulted in a higher fresh matter yield, aboveground biomass, grain yield, harvest index and lipid content. Thousand-grain weight was greater at 30 x 40 cm spacing. The 30 x 20 cm arrangement can be recommended for the cultivation of grain amaranth in the study area.

Машина для вычесывания сорняков: эффективность обработки посевов бахчевых

The cultivation of melons and gourds is a rather laborious process and the main costs fall on the treatment of crops from weeds and harvesting. Before the weed damage threshold is reached, three or four row spacing treatments with cultivators are required, which ensures soil compaction. The number of treatments can be reduced by loosening the row spacing 0.1 to 0.12 m with a device capable of affecting the root system of weeds. It is established that weeding out is affected by the gear ratio between the weed extractor rotors. In order to determine the optimal value of the gear ratio on the technological process, the author conducted laboratory and field studies. The distance, on which the root diggers interact with the soil, was determined in the soil channel when varying the gear ratio from 1.0 to 4.0 and the depth of cultivation of 0.05 and 0.1 m. In field conditions, the author measured the length of weed roots removed from the soil at a working depth of 0.05 and 0.1 m, at the gear ratio of 1.0 to 4.5, and with a pitch of 0.5. As a result of research, the author observed the optimum length of traces of the front sections of the digger equaling 0.35 m and that of rear ones equaling 0.08 m at a gear ratio of 4.0. The greatest length of weed roots extracted to the surface with the digger blade of 0.26 to 0.32 m was observed at a gear ratio of 4.0 and a depth of 0.1 m. It is concluded that the efficiency of tillage depends on the gear ratio between front and rear rotors and the depth of tillage. The highest weeding-out efficiency was observed at a gear ratio between the weed extractor rotors of 4.0.

Електросапа – культиватор «Мрія»

In this article, we propose the design of a universal electric hoe - a cultivator with a balancing drive wheel for inter-row cultivation of row crops. Currently, chemical methods and mechanical loosening are widespread in modern agriculture, but concerns about the use of herbicides, especially in "organic farming," leave no choice. We propose a machine that allows for inter-row cultivation of any row crops, even by a child. The proposed device is to be equipped with an electric motor with an electric battery, which will allow for greater mobility, low noise and vibration levels, as well as a set of tools to perform all technological operations when growing row crops. Ninety percent of manual labor in the cultivation of garden crops is spent on sowing and subsequent cultivation of row spacing. Therefore, the device must have a certain set of tools, such as a "hiller paw" for cutting furrows and hilling; a "one-sided paw" for removing weeds from the row spacing; a "lancet paw" for deep loosening and crust destruction. As can be seen from the above, manual weeding is the most effective method of weed control for working on a personal plot. However, due to the high labor intensity of the work, the task of creating a device for processing both inter-row and intra-row weeding is now being addressed. Field tests have shown that this device performs all the tasks in full, and the battery capacity, subject to continuous processing, is enough for 400 m2. The next step in improving the functional characteristics of the proposed design is to equip the electric chopper-cultivator with a device for inter-row cultivation. Inter-row cultivation is a method of weed control that involves removing weeds from the internal space between plants in one row. This process can be an important step in crop care and is aimed at reducing competition between weeds and crops. It is important to perform inter-row weeding in a timely manner, especially in the early stages of crop growth when weeds are just beginning to gain weight. It is economically feasible for the operator to control the machine manually. After a short practice, the control accuracy can reach several centimeters.