Modeling soil water dynamics in a drip-irrigated intercropping field under plastic mulch

Intercropping, drip irrigation, and the use of plastic mulch are important management practices, which can, when utilized simultaneously, increase crop production and save irrigation water. Investigating soil water dynamics in the root zone of the intercropping field under such conditions is essential in order to understand the combined effects of these practices and to promote their wider use. However, not much work has been done to investigate soil water dynamics in the root zone of drip-irrigated, strip intercropping fields under plastic mulch. Three field experiments with different irrigation treatments (high T1, moderate T2, and low T3) were conducted to evaluate soil water contents (SWC) at different locations, for different irrigation treatments, and with respect to dripper lines and plants (corn and tomatoes). Experimental data were then used to calibrate the HYDRUS (2D/3D) model. Comparison between experimental data and model simulations showed that HYDRUS (2D/3D) described different irrigation events and SWC in the root zone well, with average relative errors of 10.8, 9.5, and 11.6 % for irrigation treatments T1, T2, and T3, respectively, and with corresponding root mean square errors of 0.043, 0.035, and 0.040 cm³ cm^?3, respectively. The results showed that the SWC in the shallow root zone (0–40 cm) was lower under non-mulched locations than under mulched locations, irrespective of the irrigation treatment, while no significant differences in the SWC were observed in the deeper root zone (40–100 cm). The SWC in the shallow root zone was significantly higher for the high irrigation treatment (T1) than for the low irrigation treatment, while, again, no differences were observed in the deeper root zone. Simulations of two-dimensional SWC distributions revealed that the low irrigation treatment (T3) produced serious severe water stress (with SWCs near the wilting point) in the 30–40 cm part of the root zone, and that using separate drip emitter lines for each crop is well suited for producing the optimal soil water distribution pattern in the root zone of the intercropping field. The results of this study can be very useful in designing an optimal irrigation plan for intercropped fields.     

Productivity impacts of the system of rice intensification (SRI): A case study in West Bengal,India

The system of rice intensification (SRI) has generated considerable debate globally, particularly with regard to its potential to raise rice yields. Proponents of SRI have reported that the average rice yield with SRI is double the current average yield and can be increased to the level of three to four times. Opponents say the reported high yields are due to measurement error and that usual information expected in support of these fantastic yields is missing. The number of SRI adopters has increased in India in recent years. We evaluate the impact of adoption of SRI practices on rice yields, the economics of paddy cultivation and labour inputs based on field research conducted in Purulia, West Bengal, India. Paddy yields with SRI were higher than those under conventional paddy cultivation by 32% and net returns were higher by 67%. Labour input was reduced by 8%. SRI adoption enabled farmers consistently to enhance paddy yields, increase returns and save labour; and enhance productivity with respect to the key inputs in terms of paddy output per unit of seed, fertilizer and labour-day. SRI promises to be a significant alternative for not only raising paddy yields, but also for managing paddy based farming in resource-starved regions.     

Surface drainage requirement of crops: Application of a piecewise linear model for evaluating submergence tolerance

Crop tolerance to land submergence is an important criterion for designing a surface drainage system for agricultural lands. This paper collates the available data from various places in India related to the studies on the submergence tolerance of crops. The paper hypothesizes that a piecewise linear model could be used to describe crop response to land submergence. According to this hypothesis, there would be no yield decline for a few initial days of submergence. If submergence continues beyond this period then there would be linear decline in yield. The unknown parameters in the model are: optimum yield, threshold time and the slope which represents the per cent yield reduction per day of additional submergence beyond the threshold.Data in respect of wheat, pigeon peas, cowpeas, pearlmillet, maize and groundnuts indicate that the model describes the data well, although in many cases the threshold is 0.0. The yield reduction varies from 5.3 to 23.2% for each day of submergence beyond the threshold. It appears that to allow for more than 1–2 days of submergence will result in more than 10% reducation in yield of dryfoot crops. For the maize crop, the seedling stage is the most sensitive stage followed by the silking stage. The grain formation stage is the least sensitive, although even at this stage the threshold is 0.0 and yield reduction is 9.3% for each day of submergence beyond the threshold. The data for 9 test crops from Texas and Venezuela were well described by the model. It is concluded that the piecewise linear model is a useful tool for describing submergence tolerance of crops and for working out surface drainage requirements for a given level of yield reduction. Frequency analysis of the daily rainfall data from some selected locations indicates that there is every likelihood of submergence at most of the stations. It is suggested that there is an urgent need for developing wet farming techniques analogous to dry farming techniques.     

Sensitivity analysis of optimal operation of irrigation supply systems with water quality considerations

A model for optimal operation of water supply/irrigation systems of various water quality sources, with treatment plants, multiple water quality conservative factors, and dilution junctions is presented. The objective function includes water cost at the sources, water conveyance costs which account for the hydraulics of the network indirectly, water treatment cost, and yield reduction costs of irrigated crops due to irrigation with poor quality water. The model can be used for systems with supply by canals as well as pipes, which serve both drinking water demands of urban/rural consumers and field irrigation requirements. The general nonlinear optimization problem has been simplified by decomposing it to a problem with linear constraints and nonlinear objective function. This problem is solved using the projected gradient method. The method is demonstrated for a regional water supply system in southern Israel that contains 39 pipes, 37 nodes, 11 sources, 10 agricultural consumers, and 4 domestic consumers. The optimal operation solution is described by discharge and salinity values for all pipes of the network. Sensitivity of the optimal solution to changes in the parameters is examined. The solution was found to be sensitive to the upper limit on drinking water quality, with total cost being reduced by 5% as the upper limit increases from 260 to 600 mg Cl l^–1. The effect of income from unit crop yield is more pronounced. An increase of income by a factor of 20 results in an increase of the total cost by a factor of 3, thus encouraging more use of fresh water as long as the marginal cost of water supply is smaller than the marginal decrease in yield loss. The effect of conveyance cost becomes more pronounced as its cost increases. An increase by a factor of 100 results in an increase of the total cost by about 14%. The network studied has a long pipe that connects two distinct parts of the network and permits the supply of fresh water from one part to the other. Increasing the maximum permitted discharge in this pipe from 0 to 200 m³ h^–1 reduces the total cost by 11%. Increasing the maximum discharge at one of the sources from 90 to 300 m³ h^–1 reduces the total cost by about 8%.     

“WaterMan”: an on-farm water management game with heuristic capabilities

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game.     

Genetic Analysis of Some Chemotypes in Ocimum basilicum var. glabratum

Screening of a population of Ocimum basilicum var. glabratum Benth., raised from seeds collected from France, West Africa and Kerala (India) was carried out for chemical composition of its essential oils. In all three collections, plants were found to be comprised of 3 chemotypes which were morphologically indistinguishable, but each chemotype was found to be capable of intercrossing freely with the other two. Selfing was carried out during 4 consecutive generations, after which three pure lines were established. Study of the selfed progeny of each collection exhibited an interesting segregation in S₂ and S₃ generations. Along with segregation in F₂ and F₃ generations of various hybrids the results can be explained by assuming a gene ‘M’ existing in 3 (or more) allelic forms: The allele M₀ for biosynthesis of estragole (methyl chavicol) is dominant to allelcs M₁ , for eugenol and M₂ for camphor. Also, allele M₁ is dominant to allele M₂ . The assumption was further confirmed by testcrosses of F₁ hybrids of each cross with their recessive parent.     

Evaluation of Various Drying Methods on Bioactives,Ascorbic Acid and Antioxidant Potentials of Talinum triangulare L., foliage

Plant Foods for Human Nutrition - The aim of this study was to assess the efficiency of different drying methods (room, sun, oven, microwave, cross-flow, infra-red, dehumidifier, and freeze-drying)...     

Adoption and Impact of Modern Rice Varieties on Poverty in Eastern India

The factors affecting the adoption of modern varieties(MVs) of rice and impact on poverty in Odisha, India were discussed. A total of 363 households from Cuttack and Sambalpur districts of Odisha via multistage sampling technique participated in the survey. The Cragg's Double hurdle model was used to model the determinants of adoption and intensity of adoption of MVs of rice, and the propensity score matching was used to analyze the impact of adoption on poverty. The results showed that age, education, risk aversion, land size, yield, perception of MVs as high yielding, resistant to diseases and availability of MVs positively influenced the decision to adopt. However, variables such as household size, experience of a farmer, off-farm job participation, amount of credit received, cost of seeds, insecticides and fertilizers negatively influenced the adoption of MVs. Intensity of adoption of MVs was negatively influenced by experience of a farmer, cost of fertilizer and marketability of MVs, and positively affected by household size, risk aversion, land size, cost of insecticides, perception of MVs as high yielding and availability of MV seeds. Poverty incidence, gap and severity were high among non-adopters to adopters of MVs. After matching adopters and non-adopters of MV groups using four different algorithms of nearest neighbour matching, stratification matching, radius matching and kernel matching, the impact of MV adoption resulted in higher per capita monthly household expenditure by about US$ 52.82 to US$ 63.17.     

Genome-wide association study for spot blotch resistance in Afghan wheat germplasm

Spot blotch (SB), caused by Bipolaris sorokiniana, is a devastating disease of wheat globally, especially in South Asia and South America. Understanding the genetics of resistance to SB is important for developing breeding strategies to improve resistance. A panel of 301 genotypes from Afghanistan was phenotyped over two crop seasons using a mixture of virulent B. sorokiniana isolates and genotyped using DArTSeq to obtain genome-wide markers. Fifty genotypes (16.6%) showed disease scores less than the resistant control. Principal component analysis using the genotypic data clustered the genotypes into five different groups. Among models used for genome-wide association mapping, the multilocus mixed model, and fixed and random model circulating probability unification algorithms were most effective in identifying significant marker-trait associations (MTA). Twenty-five MTAs at p ≤ .001 were identified on chromosomes 1A, 1B, 1D, 2B, 2D, 3A, 3B, 4A, 5A, 5B, 6A, 7A, and 7D, indicating the quantitative nature of resistance to SB. Phenotypic variation explained by these markers ranged from 2.0% to 17.7%, and genomic regions on the chromosomes 1D, 2D, 3A, 3B, 4A, 5A, and 5B coincided with loci identified in previous studies. Three single nucleotide polymorphism (SNP) markers on chromosomes 1B (SNP 1113207) and 5A (SNPs 5411867 and 998276) were significant in both crop seasons as well as in the combined analysis across seasons. Marker 5411867 is close to Vrn-A1, shown to be associated with SB in previous studies. Furthermore, among known SB resistance genes, Sb2 on chromosome 5B was predicted to be significant in this panel.