Crop Management Methods Research Articles

Evaluation of Sugarcane Crop Growth Monitoring Using Vegetation Indices Derived from RGB-Based UAV Images and Machine Learning Models

Crop monitoring with unmanned aerial vehicles (UAVs) has the potential to reduce field monitoring costs while increasing monitoring frequency and improving efficiency. However, the utilization of RGB-based UAV imagery for crop-specific monitoring, especially for sugarcane, remains limited. This work proposes a UAV platform with an RGB camera as a low-cost solution to monitor sugarcane fields, complementing the commonly used multi-spectral methods. This new approach optimizes the RGB vegetation indices for accurate prediction of sugarcane growth, providing many improvements in scalable crop-management methods. The images were captured by a DJI Mavic Pro drone. Four RGB vegetation indices (VIs) (GLI, VARI, GRVI, and MGRVI) and the crop surface model plant height (CSM_PH) were derived from the images. The fractional vegetation cover (FVC) values were compared by image classification. Sugarcane plant height predictions were generated using two machine learning (ML) algorithms—multiple linear regression (MLR) and random forest (RF)—which were compared across five predictor combinations (CSM_PH and four VIs). At the early stage, all VIs showed significantly lower values than later stages (p < 0.05), indicating an initial slow progression of crop growth. MGRVI achieved a classification accuracy of over 94% across all growth phases, outperforming traditional indices. Based on the feature rankings, VARI was the least sensitive parameter, showing the lowest correlation (r < 0.5) and mutual information (MI < 0.4). The results showed that the RF and MLR models provided better predictions for plant height. The best estimation results were observed withthe combination of CSM_PH and GLI utilizing RF model (R2 = 0.90, RMSE = 0.37 m, MAE = 0.27 m, and AIC = 21.93). This study revealed that VIs and the CSM_PH derived from RGB images captured by UAVs could be useful in monitoring sugarcane growth to boost crop productivity.

Microcontroller Implementation in Precision Planting: A Review

Precision farming, also known as precision agriculture, is a crop management method that optimizes agricultural production by utilizing technology and data for precise placement of seed, fertilizer and pesticides. It enhances increase crop yields, reduce waste, and reduce environmental impact by applying the appropriate amount of inputs, such as seed, water, fertilizer, and pesticides for each crop. Farmers can reduce expenses by reducing the usage of expensive inputs while increasing yields and crop quality by employing precision farming techniques. Commercially available planters normally use mechanical metering systems which have many limitations including, skidding of the wheel, non-uniform seed rate, wastage of the seed and higher maintenance cost. It is evident from recent researchers that irregularly in seed placement, which is generally caused due to wheel slippage and seed metering systems powered by electric or hydraulic motor can maintain accurate seed placement and can work at higher speeds compared to traditional planters.

Climate Yield Models for Some Arable Crops in Ondo State.

This study looks at the connection between easily observed climate variables and crop production. Selected arable crops’ yield statistics spanning ten years were analyzed, including melon, rice, cassava, yam, and maize. Using multiple linear regression models calibrated for each of the selected crops, the crop yield was the dependent variable in SPSS statistical package version 22.0. The meteorological data, including mean temperature (oC), rainfall (mm), evaporation (mm/yr), and relative humidity (%), were correlated with the crop yield. Standard error of estimates (SE), coefficient of determination (R2), and correlation coefficient (R) are the goodness-of-fit parameters that are used to validate the models. The results demonstrated that the R-value for maize is 0.83 with a SE of 4.4 tons/ha, and the R-value for cassava is 0.85 with a SE of 10.2 tons/ha. R-values for yam and melon are 0.77 and 44.5 tons/ha, respectively; for rice and cocoyam, the values were 0.64 and 16.6 tons/ha, respectively. Melon has an R-value of 0.69 and 18.6 tons/ha. Factors such as crop management methods, diseases, nutrients, and other factors that are challenging to account for in the current statistical modeling approach could be the cause of the difference in the goodness-of-fit. There is a great need for efforts to produce trustworthy data for agricultural productivity forecasting and planning in the study region as well as all over the nation.

Multi-Layer Architecture for Enhancing Crop Quality with AI and IoT: A Structural Modelling Approach

Conventional crop management methods must be improved to address the increasing global food requirements. The exponential growth of the population exacerbates the issue at hand, the impacts of climate change and inadequate farming practices. This study analyzes the key determinants contributing to establishing a comprehensive framework for using Internet of Things (IoT) technology in the agricultural sector. The proposed Multi-Layer Architecture for Crop Quality (MLA-CQ) employs a modified version of the Total Interpretive Structural Modelling (mv-TISM) methodology to achieve this objective. This research used a mv-TISM approach to build and analyze the interrelationships among various factors that influence the adoption of IoT technology in the agriculture industry. This study introduces Artificial Intelligence (AI) by incorporating soft sensors into a remote sensing framework via deep learning. The initial data has undergone pre-processing procedures to identify and address missing values and perform data cleaning and noise reduction on the picture data obtained from farmland. Following the feature representation, a categorization procedure was performed employing an ensemble design. The suggested approach has been used to conduct experimental trials on various crops, resulting in a computing time reduction of 62%, accuracy of 95.2%, precision of 91.3 %, recall of 92.3%, and an F score of 93.1%.

Cropping Pattern, Production Status and Farmer’s Indigenous Practices of Local Crops in Humla District, Nepal

A study was carried out in the Humla district during 2078 B.S. to examine the local cropping pattern, production status, and indigenous practices of crops. To gather information, a semi-structured questionnaire was used to survey 52 households, and two focus group discussions were conducted. The study found that the major indigenous crops were summer crops that were sowed in the months of Baisakh and Jestha and harvested in Ashoj and Kartik. These crops required less water. On the other hand, winter season crops such as naked barley and wheat (pabai) required more than seven months for harvesting. Beans, buckwheat, potato, and finger millet were the major crops produced in the study area. Beans, buckwheat, and barley were cultivated by a higher number of households, while buckwheat, potato, and beans had high crop production. The majority of farmers practices a two-year crop rotation. Additionally, the study found that socio-economic factors such as gender, farmer’s age, caste, family size, and total crop production had a significant relation on maintaining on-farm crop diversity. The study concluded that local farmers in Humla district continue to rely on traditional practices for crop management, which are well-suited to the local agro-climatic conditions. However, it is necessary to give greater emphasis to increasing cropping intensity through the introduction of new technology and innovation, suitable crop management methods, and the protection of indigenous crops to enhance food security and agricultural sustainability in the region.

Effect of Organic and Inorganic Fertilizers on Yield and Yield Components of Common Bean (Phaseolus vulgaris L.) in Badakhshan, Afghanistan

For a high and usable yield of common bean, key challenges include the high expense of inorganic fertilizers and their excessive usage. Concurrently, integrated crop management methods are worldwide needs for agriculture and the environment. Because of this, the present study was carried out at the Research Farm of the Agriculture faculty at Badakhshan University in Afghanistan in order to evaluate the effect of single and combination applications of NPK, chicken manure, and the combine of NPK and chicken manure (NPK + Ch. M) with different concentrations on the growth, yield, and yield components of common bean during the summer season (June to September) of the year 2022. A randomized complete block design (R.C.B.D) was used for the experiment, and there were three replicates of each factor. It was discovered that NPK (15:15:15) at 150 kg per ha produced the highest plant in terms of height (54 cm), number of leaves per plant (63), and branch count per plant (7). These findings were based on the data that were obtained. Also, it was discovered that the optimum performance of common bean with regard to 25gr pod number/plant (PNP) ha-1 and 253g pod weight/plant was achieved with the combination of NPK (15:15:15) at a rate of 150 kg/ha and chicken manure at a rate of 20t/ha above control. This was shown to be superior to the performance of the control. A substantial (p 0.01) influence on grain production was found to be caused by the application of NPK + Ch. M. On the other hand, the NPK fertilizer and a combination of NPK and Ch. M fertilizer had a substantial impact on the grain production. The integrated of NPK + Ch. M fertilizer ha-1 treatment produced the highest grain yield (4.97t/ha-1), followed by Ch. M produced (4.22t/ha-1) seed yield. The control treatment, in which no organic or inorganic fertilizer was applied, produced the lowest grain yield (2.83t/ha-1), making this significantly higher than the control treatment. According to the findings of this study, an integrated application of NPK plus Ch. M is an effective way to get Phosphorus as well as other key elements that are necessary for the development and production of common bean.

A Fertilisation Strategy Combining Mineral Fertiliser and Biosolid Improves Long-Term Yield and Carbon Storage in a Calcareous Soil

At a strategic moment for agricultural soils, which are expected to contribute to climate change mitigation through carbon storage while safely feeding a growing world population, the fertiliser strategies used will be key. In a calcareous soil with extensive rainfed agricultural use and straw removal, different fertiliser strategies were evaluated with the aim of determining their effects on crop yield, nitrogen agronomic efficiency, and the storage of organic carbon and total nitrogen in the soil. Different doses of mineral fertiliser, expressed as kg of mineral nitrogen ha−1 year−1 (0, 60, 120, 180, and 240 nitrogen fertilising units (NFUs)), were applied to plots with and without biosolid amendment. The biosolid, applied at a rate of 40 Mg ha−1 every 3 years for 18 years, complied with national and European regulations to be applied on agricultural soil. The use of combined fertilisation reduced the amount of mineral fertiliser applied between 33 and 67% and the total fertiliser units between 7 and 40%, while maintaining similar yields to the reference mineral fertilisation (180 NFUs). These results could be related to a higher nitrogen agronomic efficiency in the combined fertilisation treatments that do not exceed the total NFUs required by the crop. Combined fertilisation was also an effective fertiliser technique to store total nitrogen and organic carbon in the soil. However, compared to the reference mineral fertilisation (180 NFUs), no significant changes in the soil organic carbon were observed, probably due to the crop management method in which the straw is removed and to higher gas emissions. Our results support the need to assess the efficacy of each agricultural technique at local scales in order not to overestimate or underestimate the potential of each agricultural technique to store soil organic carbon.

RETRACTED ARTICLE: Deep learning-based automated disease detection and classification model for precision agriculture

Plant phenotyping and Precision agriculture are information- and technology-oriented fields with specific challenges and demands for the detection and diagnosis of plant disease. Precision agriculture can be referred as a crop management method related to the spatial and temporal variability in soil and crop factors within a field. Accurate and early diagnosis and detection of plant diseases were major factors in plant production and the reduction in quantitative and qualitative losses in crop yield. Advancement of automatic disease detection and classification system is significantly explored in precision agriculture. In recent times, research workers have investigated numerous cultures leveraging dissimilar parts of a plant. This article develops a new Deep Learning-based Automated Plant Disease Detection and Classification (DL-APDDC) Model for Precision Agriculture. The presented DL-APDDC algorithm concentrates on the recognition and classification of plant diseases in leaf and fruit regions. In the initial stage, the leaf and fruit regions are extracted by the use of U2Net-based background removal. Next, the Adam optimizer with SqueezeNet model is exploited as feature extractor, and the hyperparameters are tuned by Adam optimizer. Finally, the extreme gradient boosting (XGBoost) classifier performs classification of plant diseases. The experimental validation of the DL-APDDC technique is tested on benchmark plant disease dataset. The simulation values indicated the enhanced outcomes of the DL-APDDC approach over other models.

PREBIOTIC, Bacillus subtilis AND POTASSIUM PHOSPHITE ON ANTHRACNOSIS SEVERITY AND POST HARVEST QUALITY IN ‘MÉNDEZ’ AVOCADO

Several factors affect the quality and safety of avocado (Persea americana Mill.) fruit during the production process, such as the agronomic management and climate. The objective of this research was to evaluate how foliar treatments affected postharvest control of anthracnose (Colletotrichum spp.) in two ‘Méndez’ avocado growing areas, Ziracuaretiro (ZI) and Salvador Escalante (SE), Michoacán, Mexico. Foliar sprays were used in the following treatments: 1) conventional management (CM) based on the technician’s experience; 2) integrated management (IM) including Bacillus subtilis, a prebiotic (BioKakimu®), and potassium phosphite; and 3) absolute control without foliar sprays. The effects of the treatments were evaluated on fruit harvested at physiological maturity while taking into account the severity of post-harvest anthracnose and fruit quality up to consumption maturity. During the evaluation period, disease damage was less than 10 % of the fruit surface in all three treatments. However, IM treatment delayed maturation time by 12.4 days in ZI and 10.6 days in SE. Fruits of the IM treatment lost less weight in ZI (7.6 %) than in SE (8.48 %) at eating maturity. Fruit firmness in ZI was higher in the IM and control treatments, while there were no differences in SE. The fruits in ZI and SE showed a decreasing color index profile for the three treatments. It is concluded that the phytopathogenic fungus in ‘Méndez’ was not exposed to weather conditions favorable for its development for an extended period of time, given that the first anthracnose alerts were emitted when the fruits were harvested. The crop management method did not result in an increase in the nutrient concentration of the fruit mesocarp.

Effect of foliar application of glucose and fructose to reduce codling moth (Cydia pomonella [L., 1758]) damages on apple orchard

The apple is a dominant crop in Batna region and codling moth (CM) (Cydia pomonella) pressure is constantly very high. In this study, foliar application of single sugars is proposed as a novel control strategy, in an orchard located in Beni Fedhala (province of Batna-Algeria). The effect of spraying fructose (100 ppm), glucose (100 ppm), and insecticide (Deltamethrin) was tested against CM larval damages on the Royal Gala variety. This research showed that CM own four generations in this region. The spraying of glucose alone, fructose alone strongly reduced the percentage of damaged fruits with a very important value of Abbott’s efficacy. In addition, fructose and insecticide induced a significant decrease in the percentages of fallen and damaged fruits. Besides, the use of fructose, glucose and the insecticide has significantly reduced the number of diapausing larvae in corrugated cardboard banding. Foliar application of sugars is a completely innovative way in the field of plant protection. These results open new crop management methods.

Sustainable improvement strategies for summer maize yield, nitrogen use efficiency and greenhouse gas emission intensity in the North China Plain

In the North China Plain (NCP), the deployment of sub-optimal crop management methods has resulted in low maize grain yields and significant environmental costs arising from a low N partial factor productivity (NPFP) and a rampant greenhouse gas emission intensity (GHGi). We hypothesize that in-situ analysis of the grain yield, NPFP and GHGi at local farms might contribute to improving the crop yield, as well as the environmental sustainability of maize production systems. In this study, we investigated the maize production systems deployed at 1574 local farms in the NCP, and quantified the total yield gap (defined as the difference between the yield potential as simulated by the DSSAT-CERES-Maize model and the actual yield achieved by farmers) and the exploitable yield gap (defined as the difference between the attainable yield as calculated by using the Boundary Line Function (BLF) analysis and the average actual yield achieved by farmers). By combining the results from crop modelling, farmer survey data, and on-farm trials, we were able to identify the dominant factors driving the variability in summer maize yield, NPFP, and GHGi. The results revealed that the average grain yield for summer maize in the NCP was 8.3 t ha−1, and that the total and exploitable yield gaps were 4.9 t ha−1 and 3.0 t ha−1, respectively. The average NPFP was 41 kg kg−1, which amounts to 54% of the attainable NPFP. The average GHGi was 463 kg CO2 eq t−1 grain, which constitutes an increase of 119% over the attainable GHGi. The main factors driving yield include the harvest date and the planting density, and the main factors driving NPFP and GHGi include the N, P and K fertilization rate, where it should be noted that these factors exhibit regional differences. After testing our optimized integrated agronomic management measures in the field experiments, we could confirm that it is possible to narrow the yield gap by 2.7 t ha−1, increase NPFP by 38%, and reduce GHGi by 28%. Obviously, optimizing integrated agronomic management has a great potential for narrowing the yield gap and improving the sustainability of agricultural production.

Co-implementation of tillage, irrigation, and fertilizers in soybean: Impact on crop productivity, soil moisture, and soil microbial dynamics

Due to depleting water supplies and the cultivation of high water-demanding crops like rice, water deficit in crop production has become a major concern, especially in semi-arid regions of South Asia. Soybean has been considered a possible substitution for high-water-demand crops with improved water productivity and nutrient quality. However, due to inefficient and injudicious water and fertilizer management, the overall productivity and profitability of soybean is quite low. Hence, a three-year field investigation was carried out using strip-strip plot design with three replications to study the individual and combined effects of tillage, irrigation, and fertilizer levels on crop yield and quality, soil moisture and soil microbial dynamics. Results revealed that zero tilled-flat beds (ZTFB) and conventional tilled-raised beds (CTRB) reduced the irrigation water requirement by 5.15–5.45 and 3.12–3.49 cm ha −1 , respectively, compared to conventional tilled-flat beds (CTFB). Moreover, CTRB enhanced seed yield by 8.1–31.5 %, biomass yield by 6.5–34.1 %, crop water productivity (CWP) by 27.2–30.9 %, and irrigation water productivity (IWP) by 55.2–57.5 % over CTFB. Similarly, in 2016 and 2017, CTRB had higher SPAD-chlorophyll content (34.3 and 33.2 in the top leaves) and normalized difference vegetation index (NDVI) (0.51 and 0.71) values than CTFB and ZTFB. At 0.0–0.30 m soil depth, ZTFB showed the highest soil moisture content of 11.2 % and 22.5 %, respectively, leading to the highest relative water content (RWC) of 76.7–78.7 % in soybean leaves. As a result, ZTFB took 4–8 days longer to mature than CTFB, delaying the sowing of the following wheat crop. During the 2016–2018 growing seasons, irrigation applied at the depletion of available soil moisture (DASM) by 25 % and 100 % rate of recommended fertilizer (RRF) achieved significantly higher crop, biomass yields, protein yield, SPAD, NDVI, and CWP than irrigation at lower levels. Interaction effects revealed that combinations of CTRB and ZTFB + 25 % DASM + 100 % RRF strategies generated significantly (P ≤ 0.05) higher seed yield, biomass yield, and CWP. At the same time, ZTFB had significantly higher alkaline and acid phosphatase activity than CTRB, whereas the latter had significantly higher soil microbial biomass carbon. In comparison to individual use of these crop management methods, the results of this study showed planning soybean either in CTRB or ZTFB, irrigating at 25 % DASM, and fertilizing crops with 100 % RRF could help achieve higher crop and water productivity, thus sustaining soybean production in India and adjoining regions with similar agro-ecology. • Tillage, irrigation and fertilizer rates on soybean growth were studied in three years. • CTRB+DASM 25 % + 100 % fertilizer rate enhanced soybean yield and resource use efficiency. • Due to higher soil moisture content, a soybean grown in ZT-flat beds matures later.

Saline soils worldwide: Identifying the most promising areas for saline agriculture

Salinization poses a major challenge for modern agriculture with considerable areas being salt-affected worldwide. However, these lands can be cultivated by applying saline agriculture, involving soil, water and salt-tolerant crop management methods. The agricultural use of saline soils helps in addressing food security in times of population growth and climate change. Therefore, there is a need to map saline soils and examine conditions under which saline agriculture can be implemented.The aim of this study is to identify locations and surface area of saline soils. The potential areas for saline agricultural production are mapped using the QGIS software with a focus on the most promising lands for saline agriculture. To identify these most promising areas, we apply criteria of soil salinity, soil fertility, soil pH, water availability, presence of irrigation equipment, as well as depleted water basins.Our results show that the total area of salt-affected soils equals 17 million km2, but the largest potential for saline agriculture lays in saline soils above 4 dS/m ECe in non-depleted water basins totalling to 2 million km2. We conclude that further socio-economic analysis is needed to fully determine countries which should be prioritized in exploring the future potential for sustainable food production.

Climate Warming and Crop Management: A Comprehensive Analysis of Changes on Distribution of Suitable Areas for Double Rice

Understanding the effect of climate warming and technological progress on crop production systems is crucial for developing climate adaptation strategies. This study presents a methodological framework with which to assess the suitability of the double rice cropping system in Southern China and the effects of crop management and climate warming on its distribution. The results indicate that the isolated effects of climate warming have led to the northward and westward expansions of double rice northern limits over the past six decades and an increase in suitable areas by 4.76 Mha. Under the isolated effect of crop management, the northern limits of the medium- and late-maturity double rice changed significantly due to the increased accumulated temperature required caused by varietal replacement and planting date change, which moved an average of 123 and 134 km southward, respectively. A combined scenario analysis indicated that crop management could offset the effects of climate warming and push the northern limits southward, reducing the overall suitable area by 1.31 Mha. Varietal replacement and other crop management methods should also be appropriately considered in addition to climate warming to develop locally adapted agricultural management strategies.

Biochar mitigated more N-related global warming potential in rice season than that in wheat season: An investigation from ten-year biochar-amended rice-wheat cropping system of China

Rice–wheat cropping system (RWCS), the major rice-based cropping system, constitutes a significant source of N-related greenhouse gas (GHG) emission due to the unique wet-dry alternation process. Biochar is often highlighted as a potential solution for reducing fertilizer N losses, hence, understanding its effects on Ngr emissions (mainly NH3 and N2O) under wet-dry conditions is critical to inform strategies for GHG mitigation. This study investigated the responses of NH3 and N2O emissions to biochar amendments during rice and wheat seasons based on in situ measurements under ten-year successive straw biochar application in RWCS. Our results indicated that 43.7% and 89.9% of N2O and NH3 emissions were emitted during rice season and 56.3% and 10.1% during wheat season, respectively. Long-term biochar amendment was found to play significant role in mitigating NH3 emissions (38.6–43.9%), which could be attributed to the disappearance of liming effect of aged-biochar on flooding water and decreased NH4+ concentrations in the soil. However, considerable variation of N2O emissions were observed in RWCS. Biochar showed a significant decreasing effect on the net global warming potential related to N2O and NH3 emissions (GWPN) in rice season (16.1–89.6%), and slight increased tendency in wheat season (1.43–13.1%) primarily due to its positive effects on N2O emission. Biochar amendment mainly BC22.5, significantly increased above-ground yields by 9.22% in rice season. Thus, it is a low carbon-producing and sustainable crop management method that can support crop production, C sequestration, and GHG mitigation in rice season under RWCS from the viewpoint of the Ngr mitigation. Our results suggest that emission patterns of N2O and NH3 varied with wet-dry alternation under the disturbance of long-term biochar amendment in RWCS; moreover, long-term biochar application exhibited significant potential for mitigating soil Ngr losses in rice season for RWCS.

Reaping the Benefits of Microorganisms in Cropping Systems: Is the Regulatory Policy Adequate?

Within food plant cropping systems, microorganisms provide vital functions and ecosystem services, such as biological pest and disease control, promotion of plant growth and crop quality, and biodegradation of organic matter and pollutants. The beneficial effects of microorganisms can be achieved and/or enhanced by agricultural management measures that target the resident microbial biodiversity or by augmentation with domesticated and propagated microbial strains. This study presents a critical review of the current legislation and regulatory policies pertaining to the utilization of plant-beneficial microorganisms in the European Union (EU). For augmentative approaches, the nature of the intended effect and the product claim determine how a microbiological product is categorized and regulated, and pre-market authorization may be mandatory. Typically, microbial products have been incorporated into frameworks that were designed for evaluating non-living substances, and are therefore not well suited to the specific properties of live microorganisms. We suggest that regulatory harmonization across the sector could stimulate technical development and facilitate implementation of crop management methods employing microorganisms. Possible scenarios for regulatory reform in the longer term are discussed, but more investigation into their feasibility is needed. The findings of this study should serve as a catalyst for more efficient future use of plant-beneficial microorganisms, to the benefit of agriculture as well as the environment.

Quantifying the impact of no‐till on sediment yield in southern Brazil at the hillslope and catchment scales

AbstractNo‐till (NT) is a soil management system designed to protect soil resources from water erosion and provide numerous benefits compared to conventional tillage through the increase of organic matter inputs into the soil. However, NT in isolation is not sufficient to control erosion processes caused by an excessive production of surface runoff. This study evaluated soil losses on agricultural hillslopes under no‐till characterized by contrasted water, soil, and crop management conditions. To this end, water and soil losses were monitored between 2014 and 2018 at two scales, including four macroplots (0.6 ha; 27 events) and two paired zero‐order catchments (2.4 ha; 63 events). The resulting dataset covered a wide range of rainfall conditions that occurred in contrasted soil, crop, and runoff management conditions. Hyetographs, hydrographs, and sedigraphs were constructed, and these data were used to evaluate the impact of management on sediment yields, including that of terraces, scarification, and phytomass on sediment yield. The installation of terraces reduced sediment yield by 58.7%, mainly through surface runoff control. Crop management including an increased phytomass input efficiently controlled soil losses (63%), although it did not reduce runoff volume and peak flow. In contrast, scarification had no impact on runoff and soil losses. The current research demonstrated the need to combine the installation of terraces and leaving a high amount of phytomass on the soil to control surface runoff and erosion and reduce sediment yield. The current research therefore reinforces the relevance of the monitoring strategy conducted at the scale of macroplots and zero‐order catchments to evaluate the impact of contrasted water, soil, and crop management methods and select the most effective conservation agriculture practices.

Growth of Alfavaca-Cravo in Response to Different Levels of Shade and Tiririca Density

The species Ocimum gratissimum L. is widely utilized in food, cosmetics, and folk medicine, and is also an important source of essential oils. Understanding its behavior in response to environmental conditions is of paramount importance to improving crop management methods. In this context, the following study aimed to evaluate the effects of shade, and of competition with weeds (Cyperus rotundus L.), on the growth of Ocimum gratissimum L. The experimental design adopted was randomized blocks, in a 5 × 5 factorial scheme, with 5 levels of shading (48%, 75%, 77%, 83% and 90%) and 5 densities of Cyperus rotundus L. (0, 5, 10, 15 and 20 per pot), with 4 repetitions. The variables analyzed were main stem height (MSH), diameter of stem base (DSB), number of leaves on the principal branch (NL), number of ramifications (NR), chlorophyll index of leaves (CIL), foliar area (FA), dry mass of the aerial part of the medicinal species (DMAPm), dry mass of the aerial part of the weed species (DMAPw) and essential oil content (EOC). The results demonstrate that the Ocimum gratissimum L. plants presented compatible tolerance responses to up to 70% shading, and that competition with Cyperus rotundus L. was detrimental in a density above 13 plants per pot in interaction with shading. The highest dry mass production and, consequently, the highest oil yield, were obtained from the 48% shading treatment.

Plant Spacing and Variety of Field Corn (Zea mays L.) Affecting Yield, Yield Components and Silage Quality

The recent increase in dairy and cattle production in Thailand has increased demand for high-quality roughage, particularly corn silage. Although there has been a great deal of research on field corn, far fewer studies have focused on corn intended as silage. This study involved a field experiment that analyzed crop management methods, focusing on plant spacing and 8 of the field corn varieties most commonly used in Thailand. The objectives were to determine which plant spacing and variety produced the best forage yield and silage qualities of corn silage. The plantings were arranged in a split-plot Randomized Complete Block Design (RCBD) with four replications. The main plot contained two spacing (75×20 and 75×25 cm2), each with subplots of 8 field corn varieties (SW5, NS2, NS3, NSX982013, TE1719, WS6437, WS6440, WS6442). All plants received the same crop management care regarding soil conditions, water, fertilization, and weeding. The results showed plant spacing did not significantly affect plant height (cm) and ears per plant, but the narrower 75×20 cm2 spacing produced the highest fresh leaf yield (13 t ha-1) and dry stalk yield (4.5 t ha-1) (p < 0.05). At 75×20 cm2 spacing, the TE1719 varietal had more ears per plant than SW5 (the check variety). TE1719 had the best fresh ear, stalk, and total biomass yield at both spacing of all the varieties. With regard to silage quality, the plant spacing did not significantly affect the CP, ADF, ADL, ash, and pH of the corn silage. The study revealed planting TE1719 varieties at 75×20 cm2 spacing is more economical for farmers because it increases forage yields without negatively affecting the nutritional value of corn silage.

The dynamics in rhizosphere microbial communities under bacterial wilt resistance by mulberry genotypes.

The contribution of crops and soil microbial community structure and functional diversity in soil-borne diseases control mulberry plant production is still inadequately understood. In this work, a comparative study was undertaken on the microbial abundance, community structure, and functional diversity in the soil rhizosphere between the resistant (Kangqing 10) and the susceptible (Guisang 12) mulberry genotypes. The study deployed the use of dilution plate method, micro-ecology technology, and polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) techniques. The study aimed at developing better crop management methods for mulberry cultivation as well as preventing and controlling the occurrence and impacts of bacterial wilt on mulberry productivity. The results indicated that the soil rhizosphere microorganisms were more abundant in the normal resistant mulberry genotype than in the normal susceptible mulberry genotype. Carbon source utilization was better in the normal susceptible mulberry genotype. These properties were lower in the sickly resistant mulberry genotype than in the susceptible sickly mulberry genotype. Through the PCR-DGGE, it was shown that the bacterial and fungal community structures of the resistant genotypes were more stable than those of the susceptible genotypes. Through correlation regression analysis, it was shown that the mulberry bacterial wilt significantly contributes to the loss of soil nutrients, particularly organic matter and nitrogen, a possible cause to disrupted balance between the soil microbial community and the loss of soil organic matter. Resistant genotype plants displayed more resistance to bacterial wilt. Therefore, this study recommends the need to promote the cultivation of resistant genotype mulberry for increased yield.