Harvest Quality Research Articles

Evaluation of the effectiveness of tobacco leaf harvesting and curing quality improvement measures and study of influencing factors

Promoting the implementation and consolidation of the tobacco harvesting, drying and quality improvement action, continuously improving the level of tobacco harvesting and drying, and promoting the quality and efficiency of tobacco production can contribute to the high-quality development of tobacco production. Based on data from 12 cities and prefectures in Guizhou Province, this article analyzes tobacco harvesting and drying loss rates, team construction, technology, and facility status, and evaluates the effectiveness of the tobacco harvesting and drying quality improvement action from multiple angles, and explores the factors influencing this action. The results show that the tobacco harvesting and drying quality improvement action carried out in Guizhou Province has significantly improved the overall quality of tobacco harvesting and drying. Further analysis shows that the loss rate of harvesting and drying, team construction, and facilities have all improved significantly compared to before. However, the core technology that plays a crucial role in tobacco harvesting and drying has not developed rapidly, providing certain reference for further improving the quality of tobacco harvesting and drying in the future.

Development of an in-house bone marrow collection kit: The Catalan bone marrow transplantation group experience.

Bone marrow (BM) harvesting is one of the essential sources of stem cells for haematopoietic stem cell transplantation. In 2019, commercial BM collection kits became unavailable in Europe. Consequently, we created an in-house BM collection kit as an alternative. We compared two groups of BM collections. The first collections were taken using an in-house kit from June 2022 through February 2023 and the second with a commercial kit from February 2021 through May 2022. These all took place at seven collection centres (CC). We analysed the harvest quality (cell blood count, CD34+ cells, viability, potency and sterility), the incidents occurring with each kit and the time to neutrophil and platelet engraftment in recipients. A total of 23 donors underwent BM harvesting with the in-house kit and 23 with the commercial one. Both cohorts were comparable regarding donor characteristics, CC and time to procedure. No statistical differences were found in harvest quality between the in-house and commercial kits. A new transfusion set was required in three BM harvests (13%) with the in-house kit because of filter clogging. The median time to neutrophil and platelet engraftment was 21 days for both cohorts and 29 days (in-house) and 33 days (commercial), p = 0.284, respectively. The in-house BM collection kit offers a real approach to solve the diminished supply of commercial kits. A higher risk of filter clogging was observed compared with commercial kits due to the lack of 850 and 500 μm filters.

Model description and performance calculation of the cotton harvester with a changed direction of rotation of the spindles

In the field of modern agricultural production, increasing the productivity and quality of machine harvesting, including the completeness of cotton harvesting, clogging, seed damage, and reducing power consumption are important. In this regard, the article provides performance calculation and comparative analysis of serial and vertical-spindle cotton harvesters with epi- and hypo-cyclic spindle units. A mathematical model was developed, on the basis of which the productivity of a cotton harvester was determined depending on its speed and the completeness of the cotton harvest. Theoretical studies were conducted based on classical methods for modeling processes in a harvester using a modern MathCAD 15 computing software environment.

The flesh texture of teleost fish: Characteristics and interventional strategies

AbstractWith the growing demand of consumers for high‐quality aquatic products, controlling the harvest quality of farmed fish is becoming increasingly important in aquaculture industry. The texture is a sensory property that covers a group of attributes, such as firmness, tenderness, chewiness, adhesiveness, resilience, etc., which greatly determine consumers' perception and satisfaction for flesh products. Regarding texture quality, extensive research has been conducted in recent decades based on its related theories, influencing factors, and intervention strategies. However, the information available is largely scattered and disjointed. Essentially, flesh texture is mainly determined by the collective contribution of three major muscle components: muscle fibres, intramuscular connective tissue, and intramuscular fat. Therefore, changing these components in living animals through nutritional and management factors has the potential to modulate texture quality. Here, we briefly introduced the features and development of the three muscle components mentioned above, particularly their potential contributions to texture quality of fish flesh. Exciting promises to manipulate flesh texture through dietary intervention, feed restriction, and exercise training were also discussed. To ensure their applications in large‐scale aquaculture facilities, specific considerations of these regimens should be incorporated in experimental design parameters, including the species and age of fish, research system, experiment duration, and exercise intensity. Finally, the existing challenges and limitations of fish texture studies were presented, along with some viewpoints about current work and future directions of this field.

COMMUNITY EMPOWERMENT THROUGH ORGANIC RICE CULTIVATION: CREATING A SUSTAINABLE AGRICULTURAL ENVIRONMENT

The PSRLB Program in Talang Ubi Utara Village represents a commendable initiative aimed at promoting sustainable and environmentally friendly agriculture practices. This program actively engages local farmers and the community in the pursuit of organic rice cultivation. It achieves this by providing farmers with essential training and guidance in adopting the Sustainable System of Rice Intensification (SRI) method, a sustainable approach that eliminates the need for chemical fertilizers. The results of the PSRLB program's implementation have been promising. It has not only significantly increased the productivity and quality of organic rice harvests but has also mitigated negative environmental impacts associated with conventional farming practices. As such, the PSRLB program stands as a shining example, offering inspiration to other farming communities seeking to embrace sustainable and eco-friendly agricultural methods. Its success underscores the potential for agriculture to harmoniously coexist with nature while fostering healthier, more prosperous farming communities.

Design an Architecture to Measure Effect of Climate Variability on Output and Yields of Selected Crop

Climate variability is the major factor that effect crop production in term of quantity and quality of crop harvesting in specific area. As climate going to change, variability (temperature and rainfall) is also changes due to this the effect of climate variability on output and yields selected crop (wheat and barley) also effect. The architecture is based on methodology, that justify it by using different parameter such as location, agro-ecology, data source, agriculture data sets, climate crop yields relationship etc. Based upon it, a conceptual frame work is design that introduced impact on agriculture based on climate changes.

Bone Marrow Quality Index: A Predictor of Acute Graft-versus-Host Disease in Hematopoietic Stem Cell Transplantation for Thalassemia

Bone marrow continues to be the preferred source of stem cells in allogenic transplantations for non-malignant disorders. Granulocyte-colony stimulating factor (G-CSF)-primed bone marrow (BM) is associated with low rates of acute GVHD and allows reduced collection volumes while ensuring speedy engraftment. However, variability in bone marrow harvest quality is a concern. This report analyses the utility of a novel indicator - Bone Marrow Quality Index (BMQI), which is a ratio of marrow cell count to peripheral blood cell counts, to predict acute GVHD. We analysed 184 consecutive first matched related donor bone marrow transplants for thalassemia using G-CSF-primed bone marrow over 6 years from March-2017 to April-2023 across 2 centres in India. Bone Marrow Quality Index (BMQI) was defined as the ratio of WBC count of G-CSF primed bone marrow to Peripheral WBC count within 24 hours of harvest. EBMT criteria were used for grading GVHD. Log-rank test was used to assess the impact of BMQI on GVHD. Chi-squared test was used to compare categorical data and Wilcoxon test was used to compare the numeric data. Cox proportional-hazards model was used to investigate the association of BMQI vis-à-vis other factors on acute GVHD. Of the 184 patients, 19 had a BMQI <0.9 and 18 between 0.9 and 1. The remaining 147 had BMQI >1. The proportion of patients with acute GVHD grade II-IV was 37%, 22% and 12% respectively for patients who received BMQI <0.9, 0.9-1 and >1 (p= 0.018). Patients who received BMQI <0.9 had a 3.1 times higher chance (95% CI being 0.9 to 10.6) of developing aGVHD II-IV and in those with BMQI 0.9-1 this was 2 times (95% CI being 0.5 to 6.6) higher. BMQI was the significant predictor associated with GVHD hazard (p=0.014). BMQI seems to be the most relevant and controllable predictor of acute GVHD. BMQI is a novel, informative, and very simple indicator which could influence GVHD prophylaxis decision-making. Our indicator is accurately measurable, inexpensive, precise, and timely; further it does not involve any sophisticated equipment, thus may be widely applicable. Prior knowledge of poor marrow quality may help intensify prophylaxis and monitoring for acute GVHD besides triggering review of collection procedures.

HUMIC EXTRACT AS A BIOSTIMULANT IN CROPS SUBJECTED TO ABIOTIC STRESS

Because abiotic stresses pose significant challenges to the growth and productivity of crops, the development of plants with greater survival and growth when exposed to unfavorable situations is an objective of several research groups. Biostimulants are substances or microorganisms that, when applied to crops through the foliar or root pathways, serve to enhance various processes related to growth and development. These processes include nutrient absorption, tolerance to environmental stress, and overall harvest quality. Interestingly, biostimulants can achieve these effects even when they possess a low concentration of nutrient elements in their composition. Among the main and most often used biostimulants are plant hormones, algae extract, mycorrhizal fungi, protein hydrolysates, and humic substances (humic and fulvic acids). This review sheds light on the biostimulant effects of applying humic substances to plants experiencing hydric stress conditions and low rainfed cultivation. Additionally, it aims to identify gaps in the current research and highlights areas that require further investigation. Furthermore, the review provides a concise overview of the origin and progression of research on humic substances (HS), including their extraction and obtaining process, as well as their structural characteristics and the relationship between structure, properties, and functions. The review also presents the research findings that support the potential of humic substances influencing crops affected by abiotic stress. These findings highlight the beneficial effects of humic substances in enhancing the resilience and performance of crops facing challenges such as drought, salinity, temperature extremes, and other non-biological stressors. The evidence underscores the significance of humic substances as a valuable tool in mitigating the detrimental impacts of abiotic stress on crop productivity and overall plant health.

Harvest Quality, Nucleated Cell Dose and Clinical Outcomes in Bone Marrow Transplantation: A Retrospective Study

Higher doses of infused nucleated cells (NCs) are associated with improved clinical outcomes in bone marrow transplantation (BMT) recipients. Most clinicians recommend infusing at least 2.0×108 NCs/kg. BMT clinicians request a target NC dose, but the harvested NC dose may be below the requested NC dose even before cell processing. We conducted this retrospective study to investigate the quality of bone marrow (BM) harvest and factors that influence infused NC doses at our institution. We also correlated infused NC doses with clinical outcomes. The study population included 347 BMT recipients (median age, 11 years; range, <1 to 75 years) at the University of Minnesota between 2009 and 2019. Underlying diagnoses mainly included 39% malignant and 61% nonmalignant diagnoses. Requested, harvested, and infused NC doses, as well as cell processing data, were obtained from the Cell Therapy Laboratory; clinical outcomes data were obtained from the University of Minnesota BMT Database. BM harvests were facilitated either by our institution (61%) or by the National Marrow Donor Program (39%). Associations of infused doses with baseline characteristics were assessed using the general Wilcoxon test/Pearson's correlation coefficient. The association of infused dose with neutrophil engraftment (absolute neutrophil count >500) by day 42, platelet engraftment (>20,000) by 6 months, acute graft-versus-host disease grade II-IV, and overall survival (OS) at 5 years were evaluated using regression and Kaplan-Meier curves. The median requested NC dose was 3.0×108/kg (range, 2 to 8×108/kg), and the median harvested and infused NC doses were 4.0×108/kg and 3.6×108/kg, respectively. Only 7% of donors had a harvested dose below the minimum requested dose. Moreover, the correlation between requested doses and harvested doses was adequate, with a harvested/requested dose ratio <.5 observed in only 5% of harvests. Additionally, the harvest volume and cell processing method were significantly correlated with the infused dose. Harvest volume exceeding the median of 948 mL was related to a significantly lower infused dose (P < .01). Moreover, hydroxyethyl starch (HES)/buffy coat processing (used to reduce RBCs with major ABO incompatibility) led to a significantly lower infused dose (P < .01). Donor age (median, 19 years; range, <1 to-70 years) and sex did not significantly influence the infused dose. Finally, the infused dose was significantly correlated with neutrophil and platelet engraftment (P < .05) but not with 5-year OS (P=.87) or aGVHD (P=.33). In our program's experience, BM harvesting is efficient and meets the requested minimum dose for 93% of recipients. Harvest volume and cell process play significant roles in determining the final infused dose. Minimizing harvest volume and cell processing could lead to increased infused dose and thus improved outcomes. Moreover, a higher infused dose leads to a better rate of neutrophil and platelet engraftment but not to improved OS, which may be linked to the sample size of our study.

Sea grape (Caulerpa lentillifera) aquaculture in Van Phong Bay, Viet Nam: Evaluation of the post-harvest quality

Caulerpa lentillifera, known as `sea grapes´ or `green caviar´, is increasingly in demand as a sea vegetable for human consumption. The seaweed is cultivated in ponds in the Khánh Hòa province in Van Phong Bay, Viet Nam, during the dry season (March-October). The harvested sea grape fronds are graded into different qualities based on their physical characteristics for retail on the local market or for export. Based on systematic observations of sea grape fronds of two different qualities, the frond weight, frond length and rachis coloration were identified as physical characteristics important for grading. Fronds of the best quality had significantly longer (12.59 ± 2.89 vs 10.01 ± 2.51 cm) and heavier (2.37 ± 0.59 vs 1.60 ± 0.5 g) fronds with darker rachis than the other quality group. However, a logistic regression model revealed that frond weight was the best predictor of frond quality. The physiological parameter of Fv/Fm was slightly different between the qualities, but always with means > 0.7, whereas the antioxidant activity and the total phenolic content were similar (98.34 ± 19.22 vs 95.96 ± 24.98 mmol TE (100 g)−1 DW and 163.8 ± 20.14 vs 149.85 ± 15.44 mg GAE (100 g)−1 DW). To the best of our knowledge, this study took a first approach to identify quality characteristics of sea grape fronds from Van Phong Bay, Viet Nam, which can serve as a basis for adjusting cultivation parameters to improve the harvest quality by developing cultivation and post-harvest protocols. However, further research is needed to investigate the effect of certain cultivation parameters on the specific frond characteristics.

Weedy rice: An insight into genetic diversity and population structure for effective weed management

Weedy rice (Oryza sativa f. spontanea) is a conspecific weed that has invaded cultivated rice fields, effectively adapted to modern management practices, leading to substantial yield losses and reduced harvest quality. The understanding of weedy rice genetic diversity and population structure is critical in developing effective control measures. Twenty weedy rice populations were collected around the island and evaluated using 33 SSR markers. Our findings indicated that the genetic diversity (He) in a population of weedy rice was reasonably high (0.305 - 0.560). A high level of within-population (79%) and a low level of among-population (21%) genetic variation were found by analysis of molecular variance (AMOVA). There is no significant correlation across genetic and geographical distances (P&gt;0.05). The unweighted pair group method with arithmetic mean (UPGMA) demonstrated that 20 populations were structured into two well-separated groups. Remarkably, many admixed individuals were evident according to the STRUCTURE. Weedy rice management strategies should focus on micromorphological monitoring to detect, group, and eliminate weedy rice in paddy fields, restricting the exchange of saved paddy seeds among geographical regions, increasing the production and distribution of certified seeds, the varietal recommendation for rice-growing regions to minimize mixing of varieties with different age classes, raising awareness are the recommendations to reduce the emergence of future weeds.

Field Complete Coverage Path Planning Based on Improved Genetic Algorithm for Transplanting Robot

The Complete Coverage Path Planning (CCPP) is a key technology in the field of agricultural robots, and has great significance for improving the efficiency and quality of tillage, fertilization, harvesting, and other agricultural robot operations, as well as reducing the operation energy consumption. The traditional boustrophedon- or heuristic-search-algorithm-based CCPP methods, when coping with the field with irregular boundaries, obstacles, and other complex environments, still face many problems and challenges, such as large repeated work areas, multiple turns or U-turns, low operation efficiency, and prone to local optimum. In order to solve the above problems, an improved-genetic-algorithm-based CCPP method was proposed in this paper, the proposed method innovatively extends the traditional genetic algorithm’s chromosomes and single-point mutation into chromosome pairs and multi-point mutation, and proposed a multi-objective equilibrium fitness function. The simulation and experimental results on simple regular fields showed that the proposed improved-genetic-algorithm-based CCPP method achieved the comparable performance with the traditional boustrophedon-based CCPP method. However, on the complex irregular fields, the proposed CCPP method reduces 38.54% of repeated operation area and 35.00% of number of U-turns, and can save 7.82% of energy consumption on average. This proved that the proposed CCPP method has a strong adaptive capacity to the environment, and has practical application value in improving the efficiency and quality of agricultural machinery operations, and reducing the energy consumption.

Optimisation of Control Strategies for Power Shift Gearboxes

This study is based on the influence of power shift control on the smoothness of cotton picker shifts and proposes an optimization method for the smoothness of power shifts with different control strategies for the gearbox. Through the structural design of the power shift mechanism control module, the hydraulic power distribution of the hydraulic system of the hydraulic travel module and its control mode are analyzed, and a regional cooperative shift control strategy is proposed in conjunction with control theory. A model of cotton picker dynamics was built using AMESim simulation software. In addition, the traditional control strategy was simulated and compared with the Statement component automatic control strategy to analyze and discuss the control deficiencies in power shift smoothness. Then, a particle swarm genetic algorithm (PSGA) was constructed by integrating the PSO algorithm and the genetic algorithm to verify the effectiveness of the algorithm in improving the dynamic performance and shift smoothness of the gearbox. The algorithm was verified using bench tests, and the algorithm improved the harvesting quality and efficiency of the cotton picker.

Prediction of potato dry matter content by FT-NIR spectroscopy: Impact of tuber tissue on model performance

Potato, an important cash crop, is critically affected by supply chain losses that require attention of both research and industry to ensure sustainable production (SDG 12.3). Within potato supply chain management, dry matter (DM) determination is a key factor affecting the harvest quality, storability, food losses, designated user and tuber prices. Even though rapid methods like near-infrared spectroscopy (NIR) enable operators to carry out fast, reliable in situ measurements, the prediction results are often unsatisfactory due to inherent variability of tuber's composition. Thus, this study aims to evaluate Fourier Transformed-NIR based DM prediction in different potato tissues: i) periderm, ii) cortex, iii) outer medulla and iv) inner medulla of 12 different cultivars. The DM prediction models developed using standard chemometrics approaches (i.e., partial least squares, PLS; and interval-PLS, iPLS) showed that features selection by iPLS allowed for better performances. Among the evaluated tissues, the inner medulla had more precise and reliable measurements with RMSE and R2 prediction values of 0.93% and 0.90, respectively. This information can be used to develop more advanced systems inclusive of portable tools and advanced technologies for in situ evaluation to support operators and ensure better pre- and post-harvest management of potatoes.

THE EFFECT OF AN INNOVATIVE FERTILIZER OF DIGESTATE AND WOOD ASH MIXTURES ON WINTER GARLIC PRODUCTIVITY

Garlic (Allium sativum L.) is a widespread crop in vegetable production. The popularity of garlic is due to its bactericidal and antioxidant properties. Digestate and wood ash are the by-products of cogeneration plants. The digestate is rich in nutrients, can provide a large part of the nutrients needed by the plant during the growing season, as well as improves the soil structure. Wood ash contains small amounts of phosphorus and potassium and is strongly alkaline (pH 8–12) due to the oxides in its composition, mostly calcium carbonate. The purpose of the study was to determine the effect of fertilizer rates of the digestate and wood ash mixtures on winter garlic productivity and harvest quality. Field trials with the winter garlic variety 'Lubaša' were established in sod clay, loamy soil. In the garlic plantation, different variants of fertilizer mixtures were used – they contained pig or cattle manure or plant residue digestate, and wood ash. The ratio of digestate and wood ash in the mixtures was 3:1; fertilizer rates for winter garlic were 15 and 30 t ha-1. In the study, the different types of fertilizers showed different effects on the yield and quality of winter garlic.

Optimization of macronutrients application in Terminalia tomentosa (Asan) for sustainable tasar silk production

Aim: The aim of the present study was to optimise the nutrient requirements for Terminalia tomentosa (Asan) plant to increase the quality and quantity of leaves. Methodology: This study used the Mitscherlich-Bray equation to formulate NPK requirements for the Asan plant. Independent experimental setups of N (5 levels), P (5 levels), and K (5 levels) designed in RCBD with three replications were carried out concurrently. Calculations were made to determine the theoretical maximum yield, the NPK constants c and c1, the NPK fertiliser recommendations for the Asan plant at various soil fertility levels, and the ideal fertiliser rates. Results: Fertiliser recommendations were developed for a typical range of soil test values, but they still required additional field verification tests. The theoretical maximum yields determined by the Mitscherlich-Bray equation were 599.79g, 587.49 g, and 562.34 g per 50 leaves of the Asan plant for NPK, respectively. The study demonstrated that it is critical to consider the inherent soil fertility when developing fertiliser recommendations for Asan that will increase both leaf yield and overall productivity. It showed that soil K was less efficiently utilised by the Asan plant compared to the other soil nutrients. The c1/c ratio of the P experiment was lowest compared to the c1/c ratio values of N and K experiments, indicating that the Asan plant was more responsive to P fertilisation than other macronutrient fertilisation Interpretation: The fertiliser recommendation chart serves the farmers to manage the Asan plants and is more beneficial for harvesting quality cocoons without degrading the ecosystem. Key words: Asan, Baripada, Macronutrients, Odisha, Tasar silk

Leaf Disease Detection

Abstract: Early disease identification is crucial for productive crop production in agriculture. illnesses such as bacterial spot, late blight, Septoria leaf spot, and yellow curved leaf the quality of the tomato harvest. Automatic classification techniques of plant diseases also assist in taking action once they are discovered diseased leaf symptoms Presented below is a Convolutional Learning Vector Quantization and Neural Network (CNN) model Method for detecting tomato leaf disease based on the (LVQ) algorithm and categorization. There are 500 tomato photos in the dataset. leaves that display four disease symptoms. We created a model of CNN for feature extraction and categorization automatically. Color Research on plant leaf diseases actively uses information. In our model, three channels based on RGB are subjected to filters.

Bionic Optimization Design and Discrete Element Experimental Design of Carrot Combine Harvester Ripping Shovel

Aiming at the common problems of the high working resistance, low soil disturbance, and high rates of missed extraction in the operation of carrot combine harvesters, a high-efficiency drag-reducing bionic soil-loosening shovel was designed in this study. The physical parameters of the soil and carrots were measured, and the bionic drag-reducing shovel was designed using the badger claw toe as a bionic prototype. The shovel wing structures were designed. Based on the EDEM discrete element simulation technology, a multi-element simulation model of the shovel–soil–carrot contact was established to determine the effects of the operating speed and sliding angle of the shovel handle on the resistance. The effects of the blade inclination angle and blade opening angle on the resistance, carrot extraction force, and soil disturbance rate were also studied. The results show that the resistance increases with an increase in operating speed. With a blade angle (α) and blade inclination angle (β) of 120.27° and 47.37°, respectively, the performance of the high-efficiency drag-reducing soil-loosening shovel is the best, with the resistance and carrot extraction force being 1908.76 N and 55.37 N, respectively. The virtual simulation experiment shows that this efficient drag-reducing shovel can effectively solve the problems of the low soil disturbance, high resistance, and high missing carrot rates of carrot combine harvester shovels, while also improving the harvesting quality and efficiency of carrot combine harvesters and meeting the agronomic requirements of carrot harvesting.

H2S Crosstalk in Rhizobia Modulates Essential Nutrient Allocation and Transport in Soybean

Hydrogen sulfide (H2S), a novel gas signaling molecule, plays a crucial role in plant growth and stress response. However, little attention has been devoted to the regulation of H2S on nutrient transport and utilization in legume–rhizobia symbiosis systems. Although we have previously proven that H2S synergized with rhizobia to considerably enhance nitrogen (N) metabolism and remobilization in N-deficient soybeans, it remains uncertain if changes in nutrient absorption, metabolism, and accumulation occur concurrently. Therefore, employing a synergistic treatment of H2S and rhizobia, we examined the dry matter biomass and carbon (C), N, phosphorous (P), and potassium (K) nutrient content in various organs of soybean from blooming to maturity. Firstly, H2S and rhizobia application obviously improved leaf and plant phenotypes and biomass accumulation in different organs during N-deficient soybean development. Second, from flowering to maturity, the contents and stoichiometric ratios of C, N, P, and K in various organs of soybean were changed to variable degrees by H2S and rhizobia. Furthermore, H2S collaborated with rhizobia to significantly affect grain nutrient harvest across soybean growth as well as overall plant nutrient accumulation. Consequently, H2S synergizes with rhizobia to optimize grain harvest quality and nutrient accumulation across the plant by managing the rational allocation and dynamic balance of nutrients in diverse organs, hence boosting soybean development and production.

An Artificial Intelligence-based Crop Recommendation System using Machine Learning

Agriculture is the backbone of the Indian economy and a source of employment for millions of people across the globe. The perennial problem faced by Indian farmers is that they do not select crops based on environmental conditions, resulting in significant productivity losses. This decision support system assists in resolving this issue. In our study, the AI system helps precision agriculture improve overall crop harvest quality and accuracy. This research feature selection, Industry 4.0, proposes one solution, such as a recommendation system, using AI and a family of machine learning algorithms. The data set used in this research work is downloaded from Kaggle, andlabeled. It contains a total of 08 features with 07 independent variables, including N, P, K, Temperature, Humidity, pH, and rainfall. Then SMOTE data balancing technique is applied to achieve better results. Additionally, authors used optimization techniques to tune the performance further as smart factories. Cat Boosting (C-Boost) performed the best with an accuracy value of 99.5129, F-measure-0.9916, Precision-0.9918, and Kappa-0.8870. GNB, on the other hand, outperformed ROC-0.9569 and MCC-0.9569 in the classification, regression, and boosting family of machine learning algorithms