Spatial Distribution Patterns for Identifying Risk Areas Associated with False Smut Disease of Rice in Southern India

False smut disease (FSD) of rice incited by Ustilaginoidea virens is an emerging threat to paddy cultivation worldwide. We investigated the spatial distribution of FSD in different paddy ecosystems of South Indian states, viz., Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana, by considering the exploratory data from 111 sampling sites. Point pattern and surface interpolation analyses were carried out to identify the spatial patterns of FSD across the studied areas. The spatial clusters of FSD were confirmed by employing spatial autocorrelation and Ripley’s K function. Further, ordinary kriging (OK), indicator kriging (IK), and inverse distance weighting (IDW) were used to create spatial maps by predicting the values at unvisited locations. The agglomerative hierarchical cluster analysis using the average linkage method identified four main clusters of FSD. From the Local Moran’s I statistic, most of the areas of Andhra Pradesh and Tamil Nadu were clustered together (at I > 0), except the coastal and interior districts of Karnataka (at I < 0). Spatial patterns of FSD severity were determined by semi-variogram experimental models, and the spherical model was the best fit. Results from the interpolation technique, the potential FSD hot spots/risk areas were majorly identified in Tamil Nadu and a few traditional rice-growing ecosystems of Northern Karnataka. This is the first intensive study that attempted to understand the spatial patterns of FSD using geostatistical approaches in India. The findings from this study would help in setting up ecosystem-specific management strategies to reduce the spread of FSD in India

Timing of oomycete-specific fungicide application impacts the efficacy against fruit rot disease in arecanut

Fungicidal application has been the common and prime option to combat fruit rot disease (FRD) of arecanut (Areca catechu L.) under field conditions. However, the existence of virulent pathotypes, rapid spreading ability, and improper time of fungicide application has become a serious challenge. In the present investigation, we assessed the efficacy of oomycete-specific fungicides under two approaches: (i) three fixed timings of fungicidal applications, i.e., pre-, mid-, and post-monsoon periods (EXPT1), and (ii) predefined different fruit stages, i.e., button, marble, and premature stages (EXPT2). Fungicidal efficacy in managing FRD was determined from evaluations of FRD severity, FRD incidence, and cumulative fallen nut rate (CFNR) by employing generalized linear mixed models (GLMMs). In EXPT1, all the tested fungicides reduced FRD disease levels by &gt;65% when applied at pre- or mid-monsoon compared with untreated control, with statistical differences among fungicides and timings of application relative to infection. In EXPT2, the efficacy of fungicides was comparatively reduced when applied at predefined fruit/nut stages, with statistically non-significant differences among tested fungicides and fruit stages. A comprehensive analysis of both experiments recommends that the fungicidal application can be performed before the onset of monsoon for effective management of arecanut FRD. In conclusion, the timing of fungicidal application based on the monsoon period provides better control of FRD of arecanut than an application based on the developmental stages of fruit under field conditions

Biomass Quantity and Quality from Different Year-Round Cereal–Legume Cropping Systems as Forage or Fodder for Livestock

The quantity and quality of forage and fodder crops is the major drawback of the livestock sector in the country. There is a need to bridge the gap between the supply and demand of fodder through the adoption of specific sustainable fodder production strategies. The field experiments were conducted during kharif (rainy, June–October), rabi (post-rainy, October–February), and summer (March–May) seasons of 2018–19 and 2019–20 to identify a sustainable fodder cropping system module in randomized complete block design with fifteen fodder cropping systems in three replications. The main objective of this research was to identify the most productive cereal–legume cropping system, both in terms of quantity and quality of biomass, to reduce the gap between supply and demand of quality livestock feed around the year. Among cropping systems, Bajra–Napier hybrid intercropped with lucerne, cowpea, and sesbania recorded significantly higher green fodder (163.6, 155.2, and 144.0 t/ha/year, respectively) and dry matter yields (32.1, 30.8, and 31.3 t/ha/year, respectively). Similarly, the same perennial systems also recorded higher quality yield and ash content. However, higher crude protein content was noticed in monocrop legumes, with the highest in sesbania (22.32%), while higher ether extractable fat was found in monocrop sesbania (3.78%). The monocrop oats recorded higher non-fiber carbohydrates (36.90%) while a monocrop of pearl millet recorded higher total carbohydrates (80.75%), however they were on par with other monocrop cereal cropping systems. Cultivation of legumes as a monocrop, and their inclusion as an intercrop with cereals resulted in lower fiber fractions and improved crude protein in intercropping systems. Furthermore, this improved the dry matter intake and digestibility of fodder. With higher sustainable yield index values and land-use efficiency, perennial intercropping systems were also found to be sustainable. Thus, cultivation of the Bajra–Napier hybrid with either lucerne, cowpea, or sesbania as an intercrop will help livestock farmers to achieve higher productivity in terms of quantity and quality, and forms a viable option for overcoming livestock feed scarcity

Assessment of the Spatial Distribution and Risk Associated with Fruit Rot Disease in Areca catechu L.

Phytophthora meadii (McRae) is a hemibiotrophic oomycete fungus that infects tender nuts, growing buds, and crown regions, resulting in fruit, bud, and crown rot diseases in arecanut (Areca catechu L.), respectively. Among them, fruit rot disease (FRD) causes serious economic losses that are borne by the growers, making it the greatest yield-limiting factor in arecanut crops. FRD has been known to occur in traditional growing areas since 1910, particularly in Malnad and coastal tracts of Karnataka. Systemic surveys were conducted on the disease several decades ago. The design of appropriate management approaches to curtail the impacts of the disease requires information on the spatial distribution of the risks posed by the disease. In this study, we used exploratory survey data to determine areas that are most at risk. Point pattern (spatial autocorrelation and Ripley’s K function) analyses confirmed the existence of moderate clustering across sampling points and optimized hotspots of FRD were determined. Geospatial techniques such as inverse distance weighting (IDW), ordinary kriging (OK), and indicator kriging (IK) were performed to predict the percent severity rates at unsampled sites. IDW and OK generated identical maps, whereby the FRD severity rates were higher in areas adjacent to the Western Ghats and the seashore. Additionally, IK was used to identify both disease-prone and disease-free areas in Karnataka. After fitting the semivariograms with different models, the exponential model showed the best fit with the semivariogram. Using this model information, OK and IK maps were generated. The identified FRD risk areas in our study, which showed higher disease probability rates (&gt;20%) exceeding the threshold level, need to be monitored with the utmost care to contain and reduce the further spread of the disease in Karnataka

Carbon Footprint Assessment and Energy Budgeting of Different Annual and Perennial Forage Cropping Systems: A Study from the Semi-Arid Region of Karnataka, India

Efficient use of available resources in agricultural production is important to minimize carbon footprint considering the state of climate change. In this context, the current research was conducted to identify carbon and energy-efficient fodder cropping systems for sustainable livestock production. Annual monocropping, perennial monocropping, annual cereal + legume intercropping and perennial cereal + legume intercropping systems were evaluated by employing a randomized complete block design with three replications under field conditions. The lucerne (Medicago sativa L.) monocropping system recorded significantly lower carbon input (274 kg-CE ha&minus;1 year&minus;1) and showed higher carbon indices viz., carbon sustainability index (165.8), the carbon efficiency ratio (166.8) and carbon efficiency (347.5 kg kg-CE&minus;1) over other systems. However, higher green fodder biomass led to statistically higher carbon output (78,542 kg-CE ha&minus;1 year&minus;1) in the Bajra&ndash;Napier hybrid (Pennisetum glaucum &times; Pennisetum purpureum) + lucerne perennial system. Similar to carbon input, lower input energy requirement (16,106 MJ ha&minus;1 year&minus;1) and nutrient energy ratio (25.7) were estimated with the lucerne perennial system. However, significantly higher energy output (376,345 and 357,011 MJ ha&minus;1 year&minus;1) and energy indices viz., energy use efficiency (13.3 and 12.2), energy productivity (5.8 and 5.3 kg MJ&minus;1), net energy (327,811 and 347,961 MJ ha&minus;1 year&minus;1) and energy use efficiency (12.3 and 11.2) were recorded with Bajra&ndash;Napier hybrid + legume [lucerne and cowpea (Vigna unguiculata (L.) Walp.)] cropping systems, respectively. However, these systems were on par with the lucerne monocropping system. Additionally, Bajra&ndash;Napier hybrid + legume [cowpea, sesbania (Sesbania grandiflora (L.) Pers.) and lucerne] cropping systems also showed higher human energy profitability. Concerning various inputs&rsquo; contribution to total carbon and energy input, chemical fertilizers were identified as the major contributors (73 and 47%), followed by farmyard manure (20 and 22%) used to cultivate crops, respectively, across the cropping systems. Extensive use of indirect (82%) and non-renewable energy sources (69%) was noticed compared to direct (18%) and renewable energy sources (31%). Overall, perennial monocropping and cereal + legume cropping systems performed well in terms of carbon and energy efficiency. However, in green biomass production and carbon and energy efficiency, Bajra&ndash;Napier hybrid + legume (lucerne and cowpea) cropping systems were identified as the best systems for climate-smart livestock feed production

Farmers’ Perception and Efficacy of Adaptation Decisions to Climate Change

Climate change is viewed as the main obstacle to agricultural development in developing countries. The high dependence on agriculture and allied sectors makes many countries vulnerable to the climate change phenomenon. There is a gap in macro and micro-level understanding of climate change. Thoughtful farmers’ perceptions and impacts of climate change on farming are fundamental for developing various mitigation and adaptation strategies. Therefore, the main aim of the present study was to understand the pattern of climate variability, farmers’ perceptions about climate change, and farmers’ adaptation strategies based on their socio-cultural background in the villages of Goa, on the west coast of India. The results reveal that about 62% of the sampled farmers have experienced climate change in terms of meteorological indicators such as increased average temperature, decreased total rainfall, delayed onset of monsoon, and an increase in the length of the summer season. The temperature trend analysis (0.009 °C/year) validated farmers’ perceptions, while the perception of rainfall differed (−1.49 mm/year). Farmers are convinced that climate change has affected their farming (declining crop and livestock productivity, water depletion, and other related farm operations). They strive to adapt to climate change through crop diversification, an integrated crop-livestock system, contingency crop planning, and the adaptation of new crops and varieties. This study could be helpful for policymakers to establish a climate-resilient agriculture system by ensuring timely availability of farm inputs, accurate weather forecasting, and encouraging insurance products for crop and livestock enterprises, which will help farmers cope with the changing climate to enhance their income and economic wellbeing. Further, adaption of integrated farming, agroforestry, and indigenous technical knowledge is imperative to combat the ill effects of climate change