Multiple Attributed Parametric Review Study on Mechanical Cotton (Gossypium hirsutum L.) Harvesters

Crop characteristics of cotton are crucial to identify the important crop attributes like plant height, canopy width, sympods and monopods distribution, row spacing which affects the performance of mechanical harvesters. The activity and effectiveness of most harvest aids, including desiccants is reduced by low temperature conditions. Trash content was observed to be lesser in cotton harvested by cotton picker than cotton harvested by cotton stripper. It was found that a maximum cotton yield of 1000 kg acre-1 was obtained for a cotton plant population ranging between 45,000 and 90,000 plants acre-1. Likewise, a minimum of 700 to 740 kg acre-1 was observed for a cotton plant population of 33,000 plants acre-1. In higher yielding cotton, cotton pickers recorded higher picking rate than cotton strippers. Picking/harvesting efficiency of cotton stripper with both finger and brush type mechanism was higher than the spindle type cotton picker. Picking efficiency of pneumatic picker was higher than the other types of picking mechanisms, but with lesser rate of picking capacity. Gin turnout of cotton was higher with cotton picker when compared with cotton stripper due to lesser trash content in picker harvested cotton. The horsepower requirement of cotton stripper ranged from ½ to ¼ horsepower and cost is about two-thirds of the price as compared with cotton picker. The scheduling and monitoring of various activities involved in cotton picking by using a suitable software model can increase the benefits of both growers and harvesting companies. The reduction in uniformity with roller gin-type lint cleaners ranged between 0.2 to 0.8%, which was lesser as compared with saw-type lint cleaners. Introducing mechanical harvesting has always been a decades-long process. In Turkey, it took 20 years and in Greece, this process took place very gradually over a 15-year period. Top cotton producing countries like India, Pakistan, China, Uzbekistan and other developing countries like Iran Paraguay are still not using machine harvesting. The introduction of mechanical cotton picker or stripper can help improve quality and quantity of cotton picking thereby giving more benefit to growers in developing countries and improving their socio-economic status. The most controversial issue raised by the introduction of the mechanical cotton harvester is great migration as the machines eliminated jobs and forced poor families to leave their homes and farms in search for urban jobs. Therefore Government policies towards cotton harvesting mechanization must include the alternative jobs, packages for dependent manual cotton pickers and their families.

Effects of Crop Geometry and Nutrient Management On Nutrient Uptake and Quality Parameters of Potato Under Winter Maize + Potato Intercropping System

Effects of crop geometry and nutrient management on nutrient uptake and quality parameters of potato under winter maize + potato intercropping system were studied during two consecutive years (2015-2016 and 2016-17) at BHU, Varanasi, India. Results revealed that under different crop geometry the nutrient uptake (NPK kg/ha) were obtained significantly higher with 1 : 2 row ratio in additive series as compared to other row ratio due to maximum plant population. The minimum nutrient uptake (NPK kg/ha) were obtained with 1:1 row ratio in replacement series. However, quality parameters (protein and starch) did not vary significantly by different crop geometry during both the years of investigation. Amongst nutrient management, the highest nutrient uptake (NPK kg/ha) and quality parameters (protein and starch) were obtained significantly with the application of 100% RDF + 25% N through poultry manure followed by the application of 100% RDF + 25% N through vermicompost. Thus, the results suggest that 1:2 row ratio (crop geometry) in additive series with 100% RDF + 25% N through poultry manure (nutrient management) followed by 100% RDF + 25 % N through vermicompost were feasible and practicable during both the years of investigations. Bangladesh J. Bot. 50(4): 1011-1019, 2021 (December)

Use of Narrow Rows in Sprinkler-Irrigated Corn Systems to Increase Grain Yields, Aboveground Biomass, and Water and Nitrogen Use Efficiencies

Narrow rows and optimum nitrogen applications are effective best management practices (BMPs) to enhance crop yield in an economically viable way. In a set of four studies, we aimed to compare the traditional method of planting (TMP) in wider rows (76.2 cm) with a lower plant population (84,600 seeds ha−1) against a new BMP of planting in narrow rows (38.1 cm) with a higher plant population (158,000 seeds ha−1). Implementation of the BMP resulted in 29.9 Mg ha−1 of dry matter (DM) silage, which was 42.5% higher than the 21.0 Mg ha−1 observed with the TMP. The p-values for the BMP versus TMP silage comparisons were p < 0.05, p < 0.05 and p < 0.001 for studies 2, 3, and 4, respectively, showing the significantly higher production with the BMP. Silage production water use efficiency (WUE) and agronomic nitrogen use efficiency (AE) were also higher with the BMP in studies 2, 3 and 4. The average harvested grain DM of the three BMP studies (9.9 Mg ha−1) was 9.5% higher than the 9.0 Mg ha−1 harvested grain DM with the TMP. The BMP of narrow rows with higher plant populations increases silage and grain production in sprinkler-irrigated systems.

A Methodology for the Automated Delineation of Crop Tree Crowns from UAV-Based Aerial Imagery by Means of Morphological Image Analysis

The popularisation of aerial remote sensing using unmanned aerial vehicles (UAV), has boosted the capacities of agronomists and researchers to offer farmers valuable data regarding the status of their crops. This paper describes a methodology for the automated detection and individual delineation of tree crowns in aerial representations of crop fields by means of image processing and analysis techniques, providing accurate information about plant population and canopy coverage in intensive-farming orchards with a row-based plant arrangement. To that end, after pre-processing initial aerial captures by means of photogrammetry and morphological image analysis, a resulting binary representation of the land plot surveyed is treated at connected component-level in order to separate overlapping tree crown projections. Then, those components are morphologically transformed into a set of seeds with which tree crowns are finally delineated, establishing the boundaries between them when they appear overlapped. This solution was tested on images from three different orchards, achieving semantic segmentations in which more than 94% of tree canopy-belonging pixels were correctly classified, and more than 98% of trees were successfully detected when assessing the methodology capacities for estimating the overall plant population. According to these results, the methodology represents a promising tool for automating the inventorying of plants and estimating individual tree-canopy coverage in intensive tree-based orchards.

Statistical inference for seed mortality and germination with seed bank experiments

Plant population ecologists regularly study soil seed banks with seed bag burial and seed addition experiments. These experiments contribute crucial data to demographic models, but we lack standard methods to analyze them. Here, we propose statistical models to estimate seed mortality and germination with observations from these experiments. We develop these models following principles of event history analysis, and analyze their identifiability and statistical properties by algebraic methods and simulation. We demonstrate that seed bag burial, but not seed addition experiments, can be used to make inferences about age-dependent mortality and germination. When mortality and germination do not change with seed age, both experiments produce unbiased estimates but seed bag burial experiments are more precise. However, seed mortality and germination estimates may be inaccurate when the statistical model that is fit makes incorrect assumptions about the age-dependence of mortality and germination. The statistical models and simulations that we present can be adopted and modified by plant population ecologists to strengthen inferences about seed mortality and germination in the soil seed bank.

Revisiting the number of self-incompatibility alleles in finite populations: from old models to new results

Under gametophytic self-incompatibility (GSI), plants are heterozygous at the self-incompatibility locus (S-locus) and can only be fertilized by pollen with a different allele at that locus. The last century has seen a heated debate about the correct way of modeling the allele diversity in a GSI population that was never formally resolved. Starting from an individual-based model, we derive the deterministic dynamics as proposed by Fisher (1958), and compute the stationary S-allele frequency distribution. We find that the stationary distribution proposed by Wright (1964) is close to our theoretical prediction, in line with earlier numerical confirmation. Additionally, we approximate the invasion probability of a new S-allele, which scales inversely with the number of resident S-alleles. Lastly, we use the stationary allele frequency distribution to estimate the population size of a plant population from an empirically obtained allele frequency spectrum, which complements the existing estimator of the number of S-alleles. Our expression of the stationary distribution resolves the long-standing debate about the correct approximation of the number of S-alleles and paves the way to new statistical developments for the estimation of the plant population size based on S-allele frequencies.

Managing Density Stress to Close the Maize Yield Gap

Continued yield increases of maize (Zea mays L.) will require higher planting populations, and enhancement of other agronomic inputs could alleviate density-induced stress. Row spacing, plant population, P-S-Zn fertility, K-B fertility, N fertility, and foliar protection were evaluated for their individual and cumulative impacts on the productivity of maize in a maize-soybean [Glycine max (L.) Merr.] rotation. An incomplete factorial design with these agronomic factors in both 0.76 and 0.51 m row widths was implemented for 13 trials in Illinois, United States, from 2014 to 2018. The agronomic treatments were compared to two controls: enhanced and standard, comprising all the factors applied at the enhanced or standard level, respectively. The 0.51 m enhanced management control yielded 3.3 Mg ha–1 (1.8–4.6 Mg ha–1 across the environments) more grain (25%) than the 0.76 m standard management control, demonstrating the apparent yield gap between traditional farm practices and attainable yield through enhanced agronomic management. Narrow rows and the combination of P-S-Zn and K-B fertility were the factors that provided the most significant yield increases over the standard control. Increasing plant population from 79,000 to 109,000 plants ha–1 reduced the yield gap when all other inputs were applied at the enhanced level. However, increasing plant population alone did not increase yield when no other factors were enhanced. Some agronomic factors, such as narrow rows and availability of plant nutrition, become more critical with increasing plant population when density-induced stress is more significant. Changes in yield were dependent upon changes in kernel number. Kernel weight was the heaviest when all the management factors were applied at the enhanced level while only planting 79,000 plants ha–1. Conversely, kernel weight was the lightest when increasing population to 109,000 plants ha–1 while all other factors were applied at the standard level. The yield contribution of each factor was generally greater when applied in combination with all other enhanced factors than when added individually to the standard input system. Additionally, the full value of high-input agronomic management was only realized when matched with greater plant density.

Ecological-Geobotanical Evaluation of Potential of Soil-Vegetation Cover of Pastures in Shirvan (Azerbaijan)

Data on a new method of ecological-geobotanical evaluation of the soil and vegetation cover of Shirvan in Azerbaijan, developed for the first time on the basis of data on soil evaluation, their ecological assessment and the state of natural plant population characteristic of this territory have been shown in the paper. The soil-vegetation cover of Shirvan was grouped according to the ecological-geobotanical evaluative indicators and 4 groups were identified based on the data of the ecological-geobotanical evaluation. Management is carried out in 3 directions: with application in cultivation, with application in animal husbandry and improvement of social policy and agriculture. Thus, the method of ecological-geobotanical evaluation developed for the first time can be applied to territories with similar soil and vegetation cover throughout Azerbaijan.