Crop improvement aims at substantial enhancements in the quality, yield and stress resistance of crops to meet the increasing food demand of growing world population. Targeted genome modification of crop plants is one of the ways to achieve this. This technology supersedes conventional methods limited by the inefficiencies of random mutation, accuracy and stability. It employs site-directed nucleases to create breaks at specific points in the target genome for desired alteration with high-precision. There are four nucleases namely, LAGLIDADG homing endonucleases (LHEs), zinc finger nucleases (ZFNs), &nbsp;transcription activator-like effector nucleases (TALENs) and clustered regularly interspaced short palindromic repeats (CRISPR) nucleases out of which three, ZFNs, TALENs and CRISPR have been highly studied and evaluated in various crop systems for economic trait. Potency of engineered nucleases lies in their efficacy to bring desired modification in diploid as well as in polyploid plant genomes. Modifications using genome editing are similar to natural or conventional method like induced mutations and are foreseen to waive regulatory actions as applicable to genetically modified organisms. This review seeks to emphasize on the employment of engineered nucleases in various crops plants till date.

Genome modifications in crops employing engineered nucleases

<div style="text-align: justify;">Myxomatous mitral valve degeneration is the most acquired heart disease in dogs. To reduce the clinical progression of mitral valve degeneration and achieve the hemodynamic outcomes, many medical or surgical treatments have been motivated. The objectives of this study is to investigate the suitability of puppy deciduous teeth stem cells as a cell source for tissue engineered heart valves in dog with degenerative valve disease. Puppy deciduous teeth stem cells (pDSCs) were seeded on the scaffolds which made from polylactic acid (PLA), polycaprolactone (PLC) and silicone. The mechanical properties of the tissue engineered heart valves leaflets were characterized by biaxial tensile tests. Results showed that, deciduous teeth stem cells capable of differentiating into a variety of cell types. However, the ability of puppy deciduous teeth stem cells to differentiate declined with increasing passage number which correspond to the number of protein surface marker detection have been shown to decrease substantially by the fifth passage. PLA scaffold is significantly higher tensile strength than other materials. However, silicone showed the highest flaccidity. The results from this study may provide high regenerative capability and the essential information for future directions of heart valve tissue engineering.</div>

<div style="text-align: justify;">Dental Pulp Stem Cells for Tissue Engineered Heart Valve</div>

In recent years, the use of cutting-edge statistical techniques has significantly enhanced the precision and effectiveness of agricultural practices. The auto-regressive integrated moving average (ARIMA) model has emerged as a highly effective and potent tool for the time series analysis and prediction of various subsets of agricultural engineering viz. prediction of agricultural yield, weather forecasting, water management, pest and disease outbreak prediction, livestock production forecasting, soil health monitoring and market analysis and price prediction. Due to its capacity to identify and evaluate temporal patterns, seasonality and trends in agricultural data, ARIMA was identified as a useful model for tackling complicated problems in agricultural engineering. This paper demonstrates the adaptability of ARIMA in offering precise forecasts and insightful information for agricultural systems decision-making processes through an extensive examination of the literature and case studies. The primary objectives of this review are to: (1) Analyze the use of ARIMA models in forecasting agricultural indicators such as crop yields, irrigation water needs and pest population dynamics; (2) Explore the integration of ARIMA with climatic and environmental datasets to support precision agriculture and (3) Evaluate its role in optimizing resource use and improving strategies for managing agricultural risks. The findings suggest that ARIMA models are effective tools for accurate short-to medium-term forecasting of key variables like irrigation needs, crop yields, soil moisture and climate conditions in the field of agricultural engineering. These forecasts foster decision-making, efficient resource use and reduced environmental impact. Additionally, hybrid approaches that combine ARIMA with machine learning techniques have shown further improvement in their performance, underscoring their adaptability and value in data-driven agricultural practices. ARIMA is combined with other models like LSTM, ANN, or clustering methods to capture nonlinearities and enhance prediction accuracy. Overall, ARIMA remains a foundational tool in agricultural forecasting, offering robust support for data-driven agricultural engineering practices. 
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Applications of Auto-regressive Integrated Moving Average (ARIMA) Model in Agricultural Engineering: A Review

<div>Background: Rice is one of the predominant cereal crop grown in Dharmapuri district of Tamil Nadu state, India in approximately 4000 hectares with a average productivity of 4500 kg/ha. Hoppers, stem borer, leaf folder, gall midge and ear head bugs are the major insect pests for which farmers resort management practices. Instead of curative management, farmers mostly use the insecticide as prophylactic management which leads to unwarranted problems. Though integrated pest management has been advocated as an alternate strategy, farmers are reluctant to use all the components of IPM and rely on mostly on insecticides. In this context, the ecological engineering pest management can form a better alternative, which also coincides with the age old practice of growing border crops in this region. 
 
Methods: The potential of Ecological Engineering Pest Management (EEPM) was assessed in comparison with Integrated Pest Management (IPM) and Farmers Practice (FP) in five farmer&rsquo;s fields. Based on the results, ten and twenty front line demonstrations were conducted during consecutive years to study the performance of EEPM in Dharmapuri district. 
 
Result: The number of hopper/hill, per cent dead heart, per cent white ears in the EEPM was 10.65, 7.07 and 9.65 and in the IPM module 10.18, 8.40 and 11.55 and in the farmers practice 6.73, 10.73 and 12.75 respectively. The natural enemies viz., coccinellids/hill and spiders/hill were more in EEPM (2.00 and 3.15) and least in the farmers practice (0.40 and 0.86). The number of hoppers/hill, per cent dead heart, number of coccinellids/hill and number of spiders per hill was 8.40, 6.00, 3.00 and 1.40 in EEPM and 6.20, 5.40, 1.20 and 0.60 in farmers practice respectively in the 2016-17 front line demonstrations. The EEPM module recorded 8.1, 8.65,&nbsp;3.5 and 1.75 hopper/hill, per cent dead heart, coccinellids/hill and spiders/hill in 2017-18 front line demonstrations. The farmers were able to save Rs. 5000/- from the plant protection cost apart from getting additional revenue in EEPM. The combination of border crops, influence of border crop on rodent damage in rice ecosystem and benefits of providing separate niche area than border crop are the researchable areas. In spite of above constraints the EEPM can be followed in rice ecosystem with the locally available crop combination to reduce the insecticide usage and increase the beneficials.</div>

​Demonstration of Ecological Engineering based Pest Management in Rice Oryza sativa L. through Farmers Participatory Approach

<div>Background: Green gram is a popular pulse crop in India (with 2.02 MT production over a cultivated area of 4.26 Mha) and Odisha (20.8 lakh ha area with a yield of 10.60 lakh tonnes). The information on the engineering properties and its behavioural changes with moisture content is vital for handling and designing of different agricultural processing equipment.&nbsp; 
 
Methods: This work mainly focused on studying green gram variety&rsquo;s (Sujata) engineering properties at five different moisture levels (within a moisture range of 10.58 to 45.45% (d.b.). Standard methods and procedures were followed in the study and the output results were compared with previous research work to justify the variation or anomaly in some cases. The curve estimation method (regression analysis) was followed to find the best-fit curve and equation for the parameters studied. 
 
Result: The geometric mean diameter (GMD) of grain increased from 3.75 to 4.12 mm within the moisture content (MC) range and the variation was statistically significant (p&lt;0.05). Sphericity and surface area varied significantly from 0.83 to 0.82 and 44.13 to 53.45 mm2, respectively, within the range of moisture contents studied with a high correlation among the data. Mass of thousand grains augmented (44.13 to 53.45 g) with a rise in MC and the data followed logarithmic and inverse curves. Bulk and true densities of green gram declined significantly from 860 to 670 kg m-3 and 1330 to 1240 kg m-3 with an increase in the moisture content. The porosity of green gram increased significantly from 35.75% to 46.38% and the terminal velocity raised from 9.20 m s-1 to 11.10 m s-1 with an increase in MC. The dynamic angle of repose increased significantly from 30.95 to 46.57o with MC. A significant variation in the coefficient of internal friction (0.78 to 0.90) was observed for the grains. The coefficient of static friction of grain increased significantly for different surfaces (MS, SS, Plywood and GI) with a rise in MC. The MS surface produced the highest coefficient of static friction and SS had the least. The results confirmed significant effect of MC on all engineering properties of green gram.</div>

​Effect of Moisture Content on Engineering Properties of Green Gram for Designing of Agricultural Equipment

<div>Background: Punjab (India) an agricultural state with twelve major crops sown round the year, produces 14.53 MT as crop residue. This huge quantity of crop residue poses a serious problem of stubble burning in the fields, leading to an alarming level of air pollution across the state, along with a potential loss of fuel usable for power generation. About 1000 MW of electricity can be generated from this crop residue by the proper utilization (Singh et al., 2015).&nbsp; 
 
Methods: Characteristics of various crop residues were evaluated experimentally and further investigations have been carried out to study the performance of producer gas derived from mustard stalk using a downdraft gasifier in combination with diesel oil in dual fuel diesel engine, where effect of various input parameters such as type of fuel, equivalence ratio and load on engine were studied on emission component SO2. Results were modeled and optimized through central composite design (CCD) of response surface methodology (RSM) using design of experiments technique to determine the most desirable mode of utilization.&nbsp; 
 
Result: It has been found that&nbsp; fixed carbon (40.55%), sulphur (0.367%), moisture contents (6.88%) and nitrogen contents (1.314%) in mustard stalk is almost same as in coal, where as hydrogen (6.124%), oxygen (43.965%), volatile matter (68.93%), gross calorific values (3933 kcal/kg) of mustard stalk are more and ash content (6.65%) is less as compared to corresponding values for coal. In all the three modes of operations, SO2 increases with increase in load on the engine. ER has no effect in diesel alone mode but in dual modes with increase in ER further increases SO2 as high temperature producer gas and air along with sulphur enters the engine which further increases the value of SO2.</div>

​Mathematical Modeling and Optimization for Emission Parameter SO﻿2 of Dual Fuel CI Engine using Mustard Stalk

This study was conducted to determine if adding the acid-tolerant engineered bacterial strain M. elsdenii H6F32 to the rumen of sheep would reduce the risk of lactic acidosis. Lactic acidosis were induced by feed challenges in three groups of six sheep intraruminally dosed with wheat. In each group, sheep were not supplemented(C) or supplemented with the original bacterial strain M.elsdenii H6(H6) or the acid-tolerant engineered bacterial strain M.elsdenii H6F32(H6F32). Compared with C, the concentrations of ruminal lactic acid were decreased and the pH were increased both in H6 and H6H32(P&lt;0.05). Moreover, the engineered strain H6H32 had the much better ability to decrease lactic acid and increase pH. Meanwhile, a greater concentrations of total VFA were in H6F32. The concentrations of ruminal acetate and butyrate in H6F32 were lower than that in C and H6. However, the propionate was much higher in H6F32. Conclusions about protection against lactic acidosis by the acid-tolerant bacterial strain M. elsdenii H6F32 could be reached. It may be that the engineered strain H6F32 could grow well and increases the microbial fermentative activity and increased VFAs production in the rumen at the expense of lactate during the lactic acidosis challenge.&nbsp;

Evaluation of the protective effect of the acid-tolerant engineered bacterial strain M. elsdenii H6F32 as a probiotic fed to sheep during&nbsp;the lactic acidosis challenge

<div style="text-align:justify">Background: Artificial Intelligence (AI) operations have evolved over the last two decades in improvising the operations for an agriculture-based economy. The operations in this area face many challenges in maximizing their crop yield while facing the challenges like deficient soil treatment, problems from pests and crop-based diseases. Technical challenges for the requirements of real-time data which can be further transformed to big data. Its impact is fetching low yield, because of the knowledge gap between farmers and technology. These points are the key motivators of introducing an ecosystem with artificial intelligence to agriculture in this research work. IoT devices are capable to generate large amounts of data that could be transformed into information about environmental parameters like the temperature of the field, which acts as an engine to provide data. All the data shall be collected, stored and further analyzed for better decision-making. One way the business uses the data collected is by nourishing it into the AI systems, which grasp the IoT data and further use it to make predictions. 
Methods: This research work enables to cater the solution for supporting the farmers with IT as an enabler using data analytics on the collected information. It uses a web application that would help to monitor the soil fertility and suggest the producers to select the best crop(s) that can be grown in that geographical region. 
Result: The result from our crop recommender engine successfully predicted which crop(s) we could choose to grow in our gardens or farm fields. An extensive soil study along with meteorological models helped us to launch a smart agricultural system in a much smarter way. This has further helped to bridge the gap between production and quantity yield.</div>

IoT-based Recommender Engine for Yielding Better Crops

<div style="text-align: justify;">Information on the physico-chemical, engineering and functional properties of soybean is pertinent to design equipment for the grading, pretreatments and processing. It will also help to decide the right end-use of the valuable crop as it has various diverse applications. This study evaluated these properties of two popular cultivars of soybean grown in Punjab, India viz. SL-744 and SL-958 and the investigations revealed that the grains of SL-958 are bolder and heavier than SL-744 with lighter color, greater hydration capacity, swelling capacity and volume making it more suitable for applications which require soaking and heat processing. SL-744 exhibits higher water absorption and oil absorption capacities as well as foaming capacity hence it can be used in baking industry where these properties are desirable for improving the texture, consistency and flavor of the prepared products.&nbsp;</div>

Physico-chemical, engineering and functional properties of two soybean cultivars

Engineered biochar (EngBC), a modified form of traditional biochar, offers a promising solution for agricultural sustainability. Tailored through physical, chemical, or biological treatments, EngBC is optimized for specific applications to improve soil health and function. This review synthesizes research on its key benefits, including enhanced soil fertility, water retention and pH moderation. EngBC also acts as an effective slow-release fertilizer, improving nutrient use efficiency while reducing leaching and contributes to climate mitigation through carbon sequestration. Despite these advantages, the transition to widespread practice faces considerable hurdles. High production costs, a lack of standardized protocols and potential environmental risks from contaminants or nanoparticles currently limit its adoption. A critical knowledge gap exists due to the scarcity of long-term field studies needed to validate its efficacy and safety under real-world conditions. Future research must prioritize systematic field investigations, robust risk assessments and a deeper understanding of its ecological impacts. Addressing these areas is essential for developing guidelines to enable the safe, effective and sustainable integration of EngBC into modern farming systems. 
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Genome modifications in crops employing engineered nucleases

Dental Pulp Stem Cells for Tissue Engineered Heart Valve

Applications of Auto-regressive Integrated Moving Average (ARIMA) Model in Agricultural Engineering: A Review

Demonstration of Ecological Engineering based Pest Management in Rice Oryza sativa L. through Farmers Participatory Approach

Effect of Moisture Content on Engineering Properties of Green Gram for Designing of Agricultural Equipment

Mathematical Modeling and Optimization for Emission Parameter SO₂ of Dual Fuel CI Engine using Mustard Stalk

Evaluation of the protective effect of the acid-tolerant engineered bacterial strain M. elsdenii H6F32 as a probiotic fed to sheep during the lactic acidosis challenge

IoT-based Recommender Engine for Yielding Better Crops

Physico-chemical, engineering and functional properties of two soybean cultivars

Engineered Biochar: Bridging the Gap between Promise and Practice in Agriculture: A Review