Background: Cattle husbandry in India is a cornerstone of the agricultural sector, supporting the livelihoods of millions of farmers. However, the industry grapples with challenges such as disease outbreaks, low productivity and limited access to veterinary services. The TNAU Cattle Expert System Application represents a digital innovation aimed at addressing these challenges by providing farmers with real-time guidance on various aspects of cattle management.&nbsp; 
 
Methods: The study was meticulously conducted in Tamil Nadu over the years of both 2022 and 2023.&nbsp; Feedback was systematically collected from 523 users of the TNAU Cattle Expert System Application. Text analysis tools were employed to categorize sentiments as positive, negative or neutral using Azure machine learing sotware in MS Excel. Log Regression was carried out to identify the variance of feedback sentiments followed by cluster analysis through jamovi further classified feedback into distinct groups, revealing patterns in user engagement. 
 
Result: Positive feedback praised the application&rsquo;s detailed information on cattle protection and disease precautions, particularly for FMD, BRD, Mastitis, Johne&rsquo;s disease, Brucellosis, Clostridia diseases and BVD. &ldquo;Delicate&rdquo; users (38.54%) gave appreciative feedback, &ldquo;Arbitrator&rdquo; users (26.04%) offered diverse opinions, &ldquo;Eloquent&rdquo; users (18.75%) expressed positive sentiments, while &ldquo;Criticizer&rdquo; (12.50%) and &ldquo;Harsh stringer&rdquo; users (4.17%) provided critical insights.

Digital Revolution in Livestock Farming: Empowering Indian Farmers with TNAU Cattle Expert System and User Feedback Insights

<div>Background: Over the centuries many revolutions have happened, lot of innovations took place, several discoveries changed the way the world would have been, these may be credited to discovery of paper, compass, steel, steam engine, anti-biotics, lenses, transistors, electricity, or computer. Civilizations have evolved but, in every era, agriculture played a major role in fueling the prosperity of the nation and establishing its growth. Agriculture in India provides livelihood to almost about 60% of India&rsquo;s population. Percentage contribution of agriculture and allied sectors in gross value added for India at present prices stood at 17.8% in 2020. Investment through consumer in India should grow in 2021, post losses due to COVID-19 contraction. Food sector in India is set for huge growth owing to its immense potential for diversity and value addition. Food processing sectors contributes approximately 32% of total market share, supposedly one of biggest sectors and stands fifth in terms of production, consumption, export and expected growth. 
 
Methods: Farming as a sector is a vulnerable investment owing to dependency on diversified geographical locations, environmental conditions and pest attacks, it is of prime importance to devise technological assisted methods to monitor and provide early remedial actions for the damage and infections to the crop. Work proposed is an effort to increase the yield a farmer would otherwise have; system implements the recommender system assisted by sensor data and weather conditions prevailing to suggest ideal crops to be sown for the region. Model acquires data: moisture content, rainfall estimated, NPK content of soil, temperature conditions and Ph value of the soil in addition to climatic conditions of the region for recommending the suitable crop. 
 
Result: Model proposed estimated the required parameters employing calibrated sensors from a maize farm and climatic conditions from government weather prediction platform, crop gave us a small window of six months from June to November to conduct the experiment, site selected was at Safedabad, Lucknow (U.P.) and classification was achieved through random forest algorithm trained on labeled dataset which achieved an accuracy of 96%, the testing data when fed to the model gave output with an accuracy of 93%.</div>

Expert Recommender System for Mapping Optimum Crop Type

<div>Background: The main objective of this research is to apply fuzzy logic to four Solonchaks, in order to determine their degree of remoteness or rapprochement with their central taxonomic concept. Therefore, we identify their possible seasonal taxonomic variation on the criteria established by World Reference Base (WRB).&nbsp; 
 
Methods: We have studied the seasonal evolution of salinity in a region of Algeria (Case of R&eacute;lizane), during two years 2012 and 2013 by applying fuzzy logic on the four soils. 
 
Result: The results reveal that the salinity increased during the dry period for all soils and it decreased during the wet period. On the taxonomic level, the application of fuzzy logic on the four soils revealed that the Solonchaks indices (Is) are always significantly higher than those of Calcisols indices (Ic). The four profiles have a similar behavior regarding the variation of Is. Indeed, when the salinity increases the soils come closer to the central taxonomic concept of the Solonchaks. Likewise, when the salinity decreases the soils move away from their central taxonomic concept. Consequently, they approach the central taxonomic concept of Calcisols. Thus, the variation of Isis closely related to the seasonal variation of salinity.&nbsp;Fuzzy logic, exhibited high precision concerning the membership value between soils over time. The application of fuzzy logic for other soil classifications in the world is possible.</div>

​Fuzzy Logic Expert System for Taxonomic Variation of Solonchaks

<div>Background: A suitable cropping system seem to be the possible solution to meet the continuous increase in demand for food, stability of income and diverse requirement of food grains. Selection of suitable cropping system for conservation of resources has prime importance now a day. The cropping systems selected in study have higher potential of production along with incorporable residues during winter. The residues of cotton, castor and mustard crops (Crops in selected cropping systems) have more potential to feed nutrients to soil as compared to burning. So incorporation of such crop residues in to soil helps to recycle the nutrients to correct their deficiencies. Farmyard manure is being used as major source of organic manure in field crops. Thus to maintain the soil health, integrated nutrient management approaches involving FYM and mineral source need to be standardized. So there is need to find out agronomically efficient and economically viable cropping system which can perform better for increasing productivity and profitability with association of conservation of natural resources. 
 
Methods: The experiment was laid out in split plot design with three replications. Sixteen treatment combinations comprising of four cropping system treatments viz, C1 : Cotton- Summer Pearlmillet, C2 : Greengram + Kharif &nbsp;Castor (Relay), C3 : Greengram - Mustard - Summer Pearlmillet and C4 : Greengram - Rabi Castor and two residue incorporation treatments viz, R0 : No residue incorporation and R1 : Residue incorporation as well as two fertilizer doses viz, F1 : 100% RDN through inorganic fertilizer and F2 : 75% RDN through inorganic fertilizer + 25% RDN through FYM were evaluated in the study. 
 
Result: Cotton - summer pearlmillet cropping system found significantly superior by recording higher pearlmillet equivalent yield, system productivity and system profitability while, total weed count/m2 and total weed dry weight were found the lowest under greengram- kharif castor (relay) cropping system. Residue incorporation secured top position by recording significantly the highest pearlmillet equivalent yield, system productivity and system profitability as well as lowest total weed count/m2 and total weed dry weight. Application of 75% RDN through inorganic fertilizer + 25% RDN through FYM recorded significantly highest pearlmillet equivalent yield, system productivity and system profitability. In case of weed count and weed dry weight, 100% RDN through inorganic fertilizer found significantly superior by recording lowest total weed count/m2 and total weed dry weight. &nbsp;</div>

<div>Impact of Cropping Systems and Resource Conservation Techniques on Productivity and Profitability of Systems</div>

<div>Background: The purpose of this work consists of doing a comparative study of three Land Capability Classification (LCC), Storie, National Institute of Irrigation and Drainage Institute (INSID) by applying them to the region of the Oriental Mitidja (Rouiba-Algeria).&nbsp; 
 
Methods: A geographic information system for the region in question was carried out, with a view to developing different thematic maps and allowing the comparison of these three evaluation systems, thanks to a database that has been created for this purpose. 
 
Result:&nbsp;The system adapted by INSID has given rise to lower evaluation results compared to the two other systems, because 99.99% of the total agricultural ability by the LCC, 97% Apt for agriculture. By Storie while only 48% of the total area is fit for agriculture according to INSID. Statistical results have shown the existence of a significant difference between the three land evaluation systems. However, the correlation is significant between the INSID and STORIE system.</div>

Comparative Study of Three Land Evaluation Systems by using a Geographic Information System (GIS) under Mediterranean Condition

Background: The rise in unprecedented pressure of producing enough food for an ever-growing human population resulted in the use of considerable amounts of agrochemicals in crop production. To overcome this, inclusion of annual pulse crops such as cluster beans (Cyamopsis tetragonoloba L.) in cropping systems is an alternative technique for enhancing output while minimising environmental impact. Therefore, to assess the influence of different crop production systems on yield, quality and soil fertility attributes of fennel (Foeniculum vulgare L.)-cluster bean (Cyamopsis tetragonoloba L.) crop sequence, a long term field experiment was conducted.&nbsp;&nbsp; 
 
Methods: A field experiment was conducted on fennel (Foeniculum vulgare L.) cluster bean (Cyamopsis tetragonoloba L.) crop sequence under AI-NPOF Project during 2016-17 to 2020-21 at ICAR-National Research Centre on Seed Spices, Ajmer (Rajasthan), India. The experiment was laid out as a factorial design based on randomized complete blocks (RCBD) with three replications. The first factor consisted of six production systems viz., (PS1) - 100% organic, (PS2) - 75% organic + 25% innovative practice (Compost extract, cattle urine), (PS3) - Integrated (50% organic + 50% inorganic), (PS4) - Integrated (75% organic + 25% inorganic), (PS5) -100% inorganic nutrient sources and (PS6) - State recommendation] including fennel (Rabi season) - cluster bean (Kharif season) cropping sequence, whereas the second factor included the environment over the period.&nbsp; 
 
Result: The outcomes of study revealed that production system (PS4) - Integrated (75% organic + 25% inorganic) resulted in the maximum seed yields and yield attributes of cluster bean (1501.87 kg ha-1) and fennel (1970.19 kg ha-1). The study shows that the production system (PS4) had a 17.29 and 30.75% increment of protein as compared to PS5 and PS1 in fennel and cluster beans, respectively. Under production system PS1, the per cent increment of soil organic carbon (~25.2%) and readily available N (~9%), P (~38.5%) and K (~Non-significant) were noted over the years respectively, compared with production system (PS5). A significant positive association was observed between fennel and cluster bean grain yield and soil organic carbon (P&lt;0.01) and the Shannon-Wiener indexes (R2 = 0.75, R2 = 0.69), respectively. The combined assessment of yield, quality, soil organic carbon and soil sustainability shows that rotations based on legume crops performed better and provided a model of sustainable crop intensification. Thus, adding legume to the cropping system and implementing integrated nutrient management (INM) could gradually improve soil quality in agro-ecologies where fennel predominates.

Long-term Experiment on Fennel-cluster Bean Cropping System as Affected by Production Systems: A Strategy for Improving Yield, Quality and Soil Fertility

<div>The present study was conducted to determine the effect of different cooling systems; Fan Fogger (FF) and Fan Pad (FP) on micro environment of poultry house, thermal comfort, welfare, egg production and egg quality parameters of laying hens. This experiment was conducted on 210, White Leghorn laying pullets (32 weeks old) during hot-dry summer months (May - July) under deep litter system of housing. The FP and FF cooling systems significantly dropped the mean shed temperature and increased the relative humidity. Thus, better THI resulted in increase in egg production by 4.66 % and 3.32 % under FP and FF systems over the control group. However, specific gravity, H.U, egg shell thickness, yolk index and yolk color were not significantly influenced by cooling treatments. Significantly lower levels of antioxidant enzymes viz. LPO, Catalase, G6PD, GPx and SOD was registered in cooling groups. Both the cooling devices contributed towards bird welfare by altering the behavioral expression from agonistic to non-agonistic activities.</div>

<div>Effectiveness of various cooling systems during high environmental temperature on production and welfare indices of laying pullets in deep litter system of rearing</div>

<div>A field experiment was conducted during rainy (kharif) and winter (rabi) seasons of 2014-15, 2015-16 and 2016-17 at Imphal, Manipur, to study the performance of intercropping chickpea (Cicer arietinum L.) and lentil (Lens culinaris Medik.) with linseed (Linum usitatissimum L.) and Indian mustard [Brassica juncea (L.) czernj. &amp; cosson] under 2 varying preceding kharif lowland rice (Oryza sativa L) crop durations and also to evaluate the system productivity and profitability. Planting of medium duration rice variety enhanced growth and yield of rabi crops resulting in increase in system productivity in terms of rice equivalent yield (REY) and production efficiency (PE) &nbsp;by 5.4 %, and 14.5%, respectively over planting of late duration rice variety. Seed and biological yields of chickpea, lentil, Indian mustard and linseed were higher in sole cropping than in intercropping systems. Indian mustard and linseed were found dominant and aggressive as compared to chickpea and lentil. Chickpea and Indian mustard intercropping under 4:2 ratio proved more remunerative and recorded higher yield advantage than either of chickpea and linseed or lentil and Indian mustard intercropping as judged by REY (9.7 tonnes/ha), crop productivity (39.9 kg/ha/ day) and &nbsp;net return (` 81,168/ha). Land equivalent ratio (LER) of chickpea with Indian mustard (1.10) remained at par with intercropping chickpea with linseed (1.17), however, lentil intercropped with Indian mustard had less than unity LER of 0.87.</div>

<div>Enhancing Pulse Productivity under Rice Based Production System Through Chickpea and Lentil Based Intercropping Systems in North East India</div>

Background: This research aims to determine the effectiveness of varying planting patterns and nutrient application on maize biomass, yields and light capture in a maize-soybean intercrop production. Its goal is to enhance resource efficiency, increase yields, as well as facilitate sustainable management by analysing effects of planting geometry, nutrient supply and light encoded for the two crops. 
&nbsp; 
Methods: The experiment was conducted during kharif season 2023, The treatment consists of four cropping systems in main plots (sole maize (M1), maize + soybean 1:1(M3), maize + soybean 1:2 (M4), maize + soybean 2:3 (M5)) and five nutrient sources in sub plot ((S1) control, (S2) 100% RDF, (S3)70% RDF with two foliar application of Nano NPK, (S4) 70% RDF with two foliar application of Homemade NPK, (S5) 70% RDF&nbsp; with two foliar application Plant extracts) with three replication under split plot design. 
&nbsp; 
Result: The experimental results revealed that, sole maize (M1) recorded significantly highest growth attributes i.e. no. of leaves (12.66 plant-1), LAI at maturity (3.85), specific leaf weight (6.12 g cm-2) and leaf area duration (140.91 days), compared to rest of cropping systems. Similarly, 70% RDF with two foliar application of plant extract produced biomass yield by 18% and 48.03% more light transmission ratio over the control. Hence, application of 70% RDF with two foliar sprays of plant extract enhanced crop growth and biomass of sole maize, it can be recommended to the farmer.

Influence of Planting Systems and Nutrient Management on Maize Growth, Yield and Light Interception in a Maize-soybean Intercropping System

Background: The process of marketing agricultural produce is a labyrinth of complexities. Indian farmers encounter numerous challenges in their quest for a fair price for their produce. The need for a robust marketing system to reward their efforts is not just pressing but urgent. This study was undertaken to identify the challenges various agriculture marketing models face in the region and propose a new, more efficient model.&nbsp; 
 
Methods: The present study is explorative research in nature and primary data is collected from 1086 farmers, 11 APMCs, 25 FPCs, 2 retailers and 10 farmers&rsquo; markets in the Pune district.&nbsp; 
 
Result: This study unveiled the challenges faced by farmers in adopting non-conventional marketing models. However, these challenges can be overcome with the right encouragement and training. The study&rsquo;s findings confirmed that combining conventional and non-conventional marketing models can empower farmers in the evolving landscape. They also presented an opportunity to understand the emerging challenges in Indian agriculture and offer a promising path toward doubling farmers&rsquo; income in India.