Digital agriculture has revolutionized the way pest and disease management is approached in
modern farming. This article deals with the pivotal role of decision support systems (DSS) in
this context. Digital tools have enabled the integration of various data sources such as
satellite imagery, weather forecasts, and field sensors, providing real-time insights into pest
and disease dynamics. Decision support systems utilize this wealth of data to assist farmers in
making informed decisions regarding pest and disease control strategies. By leveraging
machine learning algorithms and predictive analytics, DSS can accurately forecast pest and
disease outbreaks, thereby enabling proactive measures to mitigate risks and minimize crop
losses. However, challenges such as data integration complexity, the need for high-quality
datasets, and user accessibility remain. Furthermore, these systems facilitate precision
agriculture practices by optimizing the use of pesticides and other interventions, thus
promoting sustainability and environmental stewardship. Integration of DSS into digital
agriculture frameworks empowers farmers with actionable intelligence tailored to their
specific needs, enhancing overall farm productivity and profitability while reducing reliance
on conventional, blanket approaches to pest and disease management. As technology
continues to advance, the potential for DSS to further revolutionize integrated pest and
disease management in agriculture is immense, promising a more efficient, resilient, and
sustainable future for global food production. This study contributes significantly to
entomology by providing a framework for integrating diverse data sources to better
understand and manage pest populations, ultimately leading to more targeted and effective
pest control strategies.

Cd is recognized as highly toxic to living organisms and humans. It is present in the atmosphere, rocks, sediments, and soils. Cd enters ecosystems via numerous anthropogenic activities and emissions to the environment. Further, development in industries has built up a higher concentration of Cd in soils. Its presence in food in excess amounts may cause severe conditions in humans, therefore prevention of cadmium entering the food chain and its removal from contaminated soils is important. Over the past several years, many chemical and biological approaches for the remediation of Cd have been proposed. Phytoremediation, often called green remediation involves the use of plants (herbaceous, tree species) for the soil clean-up. This review is an attempt to summarize current information on the use of different plants and potential tree species for Cd phytoremediation from contaminated soils and the preferred accumulation of this heavy metal in different plant parts.

Women play an important role in post-harvest operations of millets and being labor-intensive using traditional methods leads to drudgery. The study examines drudgery and the impact of the adoption of selected improved practices based on ergonomic parameters over traditional practices. A purposive random sampling method was followed and a total of 112 women farmers of on millets were selected from Chalki and Gangapur villages in Sangareddy district of Telangana state. Data were collected directly from the farm women using pre-tested interview schedules and analysed using suitable statistical tools. There was a significant correlation found between the drudgery index in traditional practices and with physical profile of the women like age, height, and body mass index. With the increase in the age of the farm women, their strength in performing traditional practices becomes weak. Fifty percent of women felt that it was very easy to prepare flatbread using a power-operated flatbread machine. The drudgery in flatbread making was found to be reduced to moderate (58.51) and minimum (less than 50) levels and the same was in the four operations. Increased work output, reduced drudgery (35-88%) and time (31-90%), and minimized postural discomfort (moderate to very light pain) were recorded while using improved practices by them. Reduction in drudgery and time due to the use of improved practices resulted in postural comfort and reduced health issues concurrently, while leading to an increase in their income, millet consumption, and overall livelihood status. Designing improved tools, equipment, or work methods that should take the ergonomic and physical characteristics of women into account can help to lessen drudgery, especially in traditional millet production areas.

Climate change poses significant challenges that necessitate the development of policies to manage aggregate input and social costs. To formulate such policies, an analysis of the factors and their current trends must be conducted. This study explores the factors influencing climate change and provides insights into their impacts through changes in arable land and greenhouse gas (GHG) emissions in India from 1990 to 2020. Utilizing time series analysis, this study examined trends in GHG emissions from agriculture and developed a simulation model to estimate overall GHG emissions through methane and nitrous oxide emissions. The results indicate that enteric fermentation and agricultural soil are major contributors to methane and nitrous oxide emissions, respectively, with enteric fermentation contributing approximately 69.33% and agricultural soil contributing approximately 97.66% to methane and nitrous oxide emissions, respectively. Additionally, a higher growth rate was observed for nitrous oxide emissions than for methane emissions, with nitrous oxide emissions showing a 161% increase from 1960 to 2010. Furthermore, a positive correlation (r=0.587) between GHG emissions and changes in the annual mean temperature underscores the direct impact of agricultural emissions on climate dynamics in India, with a regression coefficient factor of 0.176. It is estimated that the overall GHG emissions from agriculture through methane and nitrous oxide emissions will be approximately 695.87 to 818.73 MMTCDE in the year 2030, while the change in annual mean temperature is estimated to be approximately 1.65 ± 0.58o C from 1990 to 2030 in India. This study faces challenges such as uncertainties in long-term climate projections and emission estimates, variability in regional agricultural practices, and the need for more granular data. These findings highlight the urgent need for effective mitigation strategies within the agricultural sector to address the growing threat of climate change.

Rasagolla (a sweet syrup cheese ball) most popular in the regions of South Asia, manufactured from Channa (a precipitate obtained by heat and acid coagulation of milk). The shelf life of Rasagolla at ambient temperature, in sugar syrup is 2 days. The mostserious constraint for shelf life enhancement is the activity of microorganisms. A study has been carried out to enhance the shelf life of Rasagolla by microwave treatment. Rasagolla was prepared under aseptic conditions in the laboratory as per the standard procedure. All the samples of Rasagolla were packed in 16 glass containers. Eight samples were tyndallized and others were kept as control. Standard Plate Count, Coliform Count and Yeast and Mould Count analysis were carried out in tyndallized and control Rasagolla. Sensory evaluation on a nine-point Hedonic Scale was done for treated and untreated products stored at ambient conditions (30 ˚C) at 0 day, 7th, 21st, 28th and till they were acceptable based on organoleptic test and consumer acceptance. It was observed that the shelf life of Rasagolla was extended by 28 days and beyond at room temperature. The different microbial counts are also within the permissible limit in microwave products than control. It has been concluded that the microwave treatment process in Rasagolla is suggested to enhance the shelf life of the product up to 15 days in room temperature.

In the dynamic realm of agriculture, where intricate interactions between environmental factors
and human interventions dictate crop outcomes, the pursuit of innovation has long been a driving
force. Within this context, artificial intelligence (AI) has emerged as a catalyst for precision and
efficiency, offering transformative potential in crop production. Among the diverse branches of
AI, artificial neural networks (ANNs) and their adaptive counterparts, particularly the fuzzy
logic/fuzzy inference system (FIS) and adaptive neuro-fuzzy inference system (ANFIS) emerged
as robust tools poised to revolutionize agriculture. Inspired by the complexities of the human
brain, ANNs represent a paradigm shift in understanding and optimizing crop production
systems, offering remarkable abilities to discern patterns, extract insights, and adapt to changing
environmental conditions. This chapter embarks on an illuminating journey into the realm of
artificial and adaptive neural networks, delving deep into their applications and implications in
crop production. Through a meticulous exploration of their architecture, functionality, and real-
world applications, the transformative potential of ANNs in optimizing yields, mitigating risks,
and fostering resilience in agricultural ecosystems is revealed. From predictive modeling and
precision agriculture to resource allocation optimization and decision-making enhancement,
ANNs and ANFISs emerge as catalysts of innovation, propelling the agricultural sector toward a
future defined by sustainability and productivity.

The present investigation entitled “Evaluation of F 1 hybrids of ridge gourd [Luffa
acutangula (L.) Roxb]” was conducted during Kharif 2021 at AICRP on Vegetable Crops,
Department of Horticulture, MPKV, Rahuri, comprising 22 treatments (20 hybrids and 2
check cultivars) with 2 replications using simple RBD. The hybrid COH-1 × Karjat Local
recorded the longest vine length (9.95 m) and the maximum number of primary branches per
vine (8.40). This hybrid also showed the minimum days for the first male flower (33.70 days),
first female flower (36.60 days), and earliest fruit harvest (44.10 days). It had the lowest sex
ratio (4.78) and node at the first female flower (10.80), with minimum days for 50% of plants
to produce flowers in COH-1 × Nidhi (39.50 days). Maximum fruit weight was observed in
COH-1 × Arka Sujata (199.43 g) and maximum fruit length in Arka Sujata × Nidhi (46.95
cm). The hybrid Arka Sujata × Nidhi recorded the maximum fruit diameter at the center (4.53
cm), the fruit diameter at the pedicel was highest in Navin Long × Krishna-51 (1.94 cm), and
the maximum fruit diameter at the stylar end was in Arka Sujata × Krishna-51 (3.67 cm). The
highest number of fruits per vine was in COH-1 × Karjat Local (19.20), resulting in the
highest fruit yield per plant (4.30 kg) and per hectare (24.67 t/ha). All hybrids had elongate
fruit shape with 10 ridges. Hybrids COH-1 × Karjat Local, COH-1 × Banaras Local, and
COH-1 × Arka Sujata were superior for most characters based on mean performance.

An experiment was conducted at the research farm of College of Agriculture, Nagpur to
determine the nature and magnitude of genetic variability in F 2 and BC 1 F 1 crosses in terms of
various genetic parameters for the different characters. In rabi 2022 three BC 1 F 1 crosses (TAM
108-1 x PC-6) x TAM 108-1, (Kranti x PC-6) x Kranti and (ACN-9 x PC-6) x ACN-9 done for
transfer of powdery mildew resistance from B. carinata (PC-6 donor) to B. juncea varieties and
their three F 2 crosses of TAM 108-1 x PC-6, ACN-9 x PC-6 and Kranti x PC-6 along with their
four parents ACN-9, TAM 108-1, Kranti and PC-6 , were evaluated in RBD with 3 replications.
The data were recorded on days to first flower, days to maturity, plant height (cm), number of
branches plant -1 , number of siliquae plant -1 , 1000 seed weight (g) and seed yield plant -1 (g), and
statistically analyzed. In many of the F 2 or BC 1 F 1 crosses seed yield plant -1 was less though their
number of siliquae plant -1 which was more due to the involvement of two species i.e., juncea and
carinata. Wide range was observed for all the seven characters studied among the three F 2 crosses
and the three BC 1 F 1 crosses. Moderate to high per cent of GCV and PCV were exhibited for plant
height, number of branches plant -1 , number of siliquae plant -1 , 1000 seed weight and seed yield
plant -1 in all F 2 and BC 1 F 1 crosses. High to moderate heritability coupled with high moderate
genetic advance as per cent of mean was exhibited in all the F 2 and BC 1 F 1 crosses except BC 1 F 1
cross (ACN-9 x PC-6) x ACN-9. Selection of potential material were done in F 2 and BC 1 F 1
generation. In F 2 generation, 29 single plants were identified based on the characters seed yield
plant -1 , number of siliquae plant -1 and number of branches plant -1 for forwarding to F 3 generation
by plant to row method for their exploitation. In BC 1 F 1 crosses 64 single plants selected on the
basis of resistance to powdery mildew less than 3 score were backcrossed with their respective B.
juncea parents to get seeds of BC 2 F 1 which will be forwarded to next generation with an aim to
transfer the genetic constitution of B. juncea to improve its yield level.

The present study examines the association between students' time management strategies
and their academic achievement, focusing on the roles of socioeconomic status, gender,
location, and education. A sample of seventy students, the research explores goal setting, task
prioritization, planner use, and distraction management. Correlation and regression analyses
were used to understand the impact of demographic characteristics on time management and
academic performance. The study's challenges include a gender imbalance in study time,
affecting the findings' generalizability. Results indicate that 47.1% of students prioritize
tasks, 35.7% set goals and deadlines, and 31.4% use planners. Gender significantly influences
handling distractions (r = -0.411, p < 0.01) and study techniques (r = -0.429, p < 0.01), with
female students showing better practices. Socioeconomic status negatively correlates with
handling distractions (r = -0.337, p < 0.01), and education level positively correlates with
study techniques (r = 0.233, p < 0.05). Regression analysis identifies gender (β = -0.434, p <
0.01) and education (β = 0.220, p < 0.05) as significant predictors of effective study
techniques. Additionally, 75.7% of students are averagely satisfied with their time
management, and 21.4% are very satisfied.

Presently Agricultural marketing system in India suffers from a number of constraints which are either infrastructure or Government regulation related or technology-related or related to poor information on domestic and overseas markets and opportunities or related to unstable and uncertain produce prices or related delayed and late payment to producers and finally related to low producer’s realization. Under these circumstances, a Second Green Revolution is expected to clear the mess and keep the nation on the right path. In order to improve the marketing system encouraging cooperative marketing, establishing regulated markets, and grading, storage, and warehousing are essential. In this connection, the role of Market Led Extension is pivotal in promoting agricultural marketing activities. Market-led Extension is a market market-oriented extension system that informs, stimulates, and guides the farmer’s right from the selection of an enterprise to the marketing of the produce with the purpose of getting an optimum return out of the enterprise. The present study focused on the Managerial ability of stakeholders for Market-led Extension, it was conducted with 245 respondents in seven different districts of Telangana state. For the selection of respondents, a multi-stage random sampling method was used. From each district 20 farmers, 5 APMC office bearers, 5 Agricultural officers, and 5 Traders. A total of 140 farmers, 35 APMC office bearers, 35 Agricultural officers, and 35 Traders were selected as respondents for the current study. From the study, it was concluded that the majority of the farmers had medium (32.86%) to low (27.14%)managerial ability for market-led extension, majority of the APMC office bearers had low (37.14%) to very low (31.43%)managerial ability for market-led extension, majority of the AOs had medium (42.86%) to low (28.57%)managerial ability for market-led extension and a majority (34.29%) of the Traders had low Managerial ability for a market-led extension. It could be improved by giving trainings to the respondents. Government should promote the formation of farm cooperatives including FPOs through the Department of Agriculture and KVKs, and motivate the farmers to link the FPOs to the big traders for easy marketing of crop produce