Estimating the Production Potential of Major Crops in Pakistan’s Irrigated Agriculture during the 21st Century

Land and irrigation are the basic resources in agriculture. The role and importance of these resources and their contribution towards productivity, in the context of the country’s increasing population, can hardly be exaggerated. Pakistani agriculture is set in a very distinctive situation of an increasing population on the one hand and diminishing resources on the other. The population of Pakistan was reported to be 131.63 million in 1996 and is projected to be 207 million in 2013 [Pakistan (1996) and WSIP (1990)]. The agriculture sector has to face the difficult task of doubling the existing food production by the turn of this century. The situation demands horizontal and vertical growth in the productivity, either by bringing more land under cultivation, or by increasing the cropping intensity of the existing land resources. This can also be accomplished by bringing more land under cultivation from the cultivable uncultivated area (a large proportion of which exists on medium and large farms under waterlogged or saline conditions). In this context, it becomes important to identify the nature of the relationship that exists between farm size and unculturable wastelands and the kinds of changes the green revolution/SCARPs projects introduced to this relationship.

Estimating the Production Potential of Major Crops in Pakistan’s Irrigated Agriculture during the 21st Century

Land and irrigation are the basic resources in agriculture. The role and importance of these resources and their contribution towards productivity, in the context of the country’s increasing population, can hardly be exaggerated. Pakistani agriculture is set in a very distinctive situation of an increasing population on the one hand and diminishing resources on the other. The population of Pakistan was reported to be 131.63 million in 1996 and is projected to be 207 million in 2013 [Pakistan (1996) and WSIP (1990)]. The agriculture sector has to face the difficult task of doubling the existing food production by the turn of this century. The situation demands horizontal and vertical growth in the productivity, either by bringing more land under cultivation, or by increasing the cropping intensity of the existing land resources. This can also be accomplished by bringing more land under cultivation from the cultivable uncultivated area (a large proportion of which exists on medium and large farms under waterlogged or saline conditions). In this context, it becomes important to identify the nature of the relationship that exists between farm size and unculturable wastelands and the kinds of changes the green revolution/SCARPs projects introduced to this relationship

Ruth Meinzen-Dick and Mark Svendsen (eds). Future Directions for Indian Irrigation: (Research and Policy). Washington, D. C.: International Food Policy Research Institute. 1991. xiv + 333 pp.

The editors of the book have divided their subject matter into four broad categories. The first category deals with irrigation development in India, focusing on important issues confronting the use of water resources and on alternate scenarios for future development. The second category examines the improved performance of the existing irrigation system and emphasizes the need for improvement. The third part highlights the issues relating to the process and sustainability of managerial improvement in system management. The last category pinpoints the special problems related to irrigation in Eastern India. The book comprises twenty chapters, with a brief chapter of introduction and four others that present overviews of each of the categories. Fourteen of the remaining chapters cover the main body of the text, with a concluding chapter on a model that promises to resolve the irrigation issues. The overview before each category is quite lucid and often critical, leaving little room for review. However, brief comments are presented for the interested readers

Salinity Damage to Irrigated Crops: Economic Measure from a Farm Survey in Pakistan

Dissolved salts (salnuty) in irrigation water are a sigmficant envhonmental problem in aud regions. Some of the most seriously impacted irrtgated areas are found m Pakistan's Indus Basm. Economic damage measures are essential for evaluating sahmty control programmes. Most damage estuuates are derived from controlled experiments, which may not be applicable to actual field conditions. Data from two JOtntly conducted farm suiveys---one dealing with farm inputs and production and the other with soll and waterchenustry-are analyzed with statistical regression techniques. Damage measures for three winter crops are developed. Whtie the dual suxvey method is expensive, the statistical analysis shows that less elaborate soil sampling procedures can proVIde sufficient information. The tech111que 1s Judged to be a reliable approach to measuring salinity damage functions under actual field condition

Genetic diversity analysis in Buckwheat germplasm for nutritional traits

827-837Feeding the growing global human population is a tough challenge. Researchers look towards lesser known food crops which are nutritionally adequate, if not superior than the common major crops. Buckwheat (Fagopyrum tartaricum L. Gaerth), also called ‘pseudocereal’, is one such multipurpose crop with promising nutritive value. To enhance utilization of buckwheat as supplement food, here, we did genetic diversity analysis for nutritional parameters. Significant genetic diversity was observed in buckwheat germplasm for 24 nutritional parameters including total oil content (0.75-5.45%), oleic acid (36.98-47.87%), linoleic acid (32.75-44.61%), total protein content (5.65-14.17%), lysine (4.19-8.63 g/16 g N), methionine (0.54-2.48 g/16 g N) and half cystine (0.82-3.57 g/16 g N). The entire germplasm was grouped into three clusters. Cluster I comprised accessions promising high oil, stearic acid, oleic acid, least in linoleic acid and essential amino acids. Cluster II had accessions promising quality oil with highest linoleic acid and linolenic acid (PUFA) and highest half-cystine and glycine. Cluster III possesed promising accessions for highest oil percent, total protein, high essential amino acids and highest test weight. The inter-simple sequence repeats (ISSR) analysis using 26 primers indicated significant genetic diversity existed at molecular level. This study includes large number of accessions analyzed for nutridiversity in entire spectrum of germplasm collections of the world. Nutritionally rich promising genotypes identified will be potential genetic stocks for making buckwheat, a prospective supplement food crop

Estimation of Water Balance for Anticipated Land Use in the Potohar Plateau of the Indus Basin Using SWAT

Land Use/Land Cover (LU/LC) change is among the dominant driving factors that directly influence water balance by transforming hydrological responses. Consequently, a thorough comprehension of its impacts is imperative for sustainable water resource planning and development, notably in developing worlds such as Pakistan, where agriculture is a major livelihood. This research intends to assess the continuing changes in LU/LC and evaluate their probable repercussions on the hydrological regime of the Potohar Plateau. The maximum likelihood classification (MLC) algorithm for land use classification of the high-resolution satellite imageries, the Cellular-Automata Markov Chain Model (CA-MCM) for the projection of LU/LC maps, and the Soil and Water Assessment Tool (SWAT) in tandem with SWAT-CUP for hydrological modeling were employed in this research. The high-resolution climatic dataset (10 × 10 km) was used in SWAT. The LU/LC analysis revealed a continual propagation of agricultural and built-up lands at the detriment of forest and barren land during the last three decades, which is anticipated to continue in the future, too. Hydrological model calibrations and validations were performed on multi-basins, and the performance was evaluated using different statistical coefficients, e.g., the coefficient of determination (R2), Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and Percent Bias (PBIAS). The results yielded that the model performed very well and demonstrated the model’s robustness in reproducing the flow regime. The water balance study revealed that the anticipated LU/LC changes are projected to decrease the mean annual surface runoff, water yield, and streamflow due to an increase in percolation, lateral flow, sub-surface flow, and evapotranspiration. More significant variations of the water balance components were observed at the sub-basin level, owing to the heterogeneous spatial distribution of LU/LC, than at the basin level. The outcome of this study will provide pragmatic details to legislative bodies to develop land and water management ameliorative strategies to harness hydrological changes sustainably

Estimation of Water Balance for Anticipated Land Use in the Potohar Plateau of the Indus Basin Using SWAT

Land Use/Land Cover (LU/LC) change is among the dominant driving factors that directly influence water balance by transforming hydrological responses. Consequently, a thorough comprehension of its impacts is imperative for sustainable water resource planning and development, notably in developing worlds such as Pakistan, where agriculture is a major livelihood. This research intends to assess the continuing changes in LU/LC and evaluate their probable repercussions on the hydrological regime of the Potohar Plateau. The maximum likelihood classification (MLC) algorithm for land use classification of the high-resolution satellite imageries, the Cellular-Automata Markov Chain Model (CA-MCM) for the projection of LU/LC maps, and the Soil and Water Assessment Tool (SWAT) in tandem with SWAT-CUP for hydrological modeling were employed in this research. The high-resolution climatic dataset (10 × 10 km) was used in SWAT. The LU/LC analysis revealed a continual propagation of agricultural and built-up lands at the detriment of forest and barren land during the last three decades, which is anticipated to continue in the future, too. Hydrological model calibrations and validations were performed on multi-basins, and the performance was evaluated using different statistical coefficients, e.g., the coefficient of determination (R2), Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and Percent Bias (PBIAS). The results yielded that the model performed very well and demonstrated the model’s robustness in reproducing the flow regime. The water balance study revealed that the anticipated LU/LC changes are projected to decrease the mean annual surface runoff, water yield, and streamflow due to an increase in percolation, lateral flow, sub-surface flow, and evapotranspiration. More significant variations of the water balance components were observed at the sub-basin level, owing to the heterogeneous spatial distribution of LU/LC, than at the basin level. The outcome of this study will provide pragmatic details to legislative bodies to develop land and water management ameliorative strategies to harness hydrological changes sustainably

Developing an NIRS Prediction Model for Oil, Protein, Amino Acids and Fatty Acids in Amaranth and Buckwheat

Amaranth and buckwheat are two pseudo-cereals preferred for their high nutritional value, are gluten free and carry religious importance as fasting food. Germplasm resources are the reservoir of diversity for different traits, including nutritional characteristics. These resources must be evaluated to utilize their potential in crop improvement programs. However, conventional methods are labor-, cost- and time-intensive and prone to handling errors when applied to large samples. NIRS-based machine learning to predict different nutritional traits is applied in different food crops for multiple traits. NIRS prediction models are developed in this study using the mPLS regression technique for oil, protein, fatty acids and essential amino acid estimation in amaranth and buckwheat. Good RSQ external (power of determination) values were obtained for the above traits ranging from 0.72 to 0.929. Ratio performance deviation (RPD) value for most of the traits ranged between 2 and 3, except for valine (1.88) and methionine (3.55), indicating good prediction capabilities in the developed model. These prediction models were utilized in screening the germplasm of amaranth and buckwheat; the results obtained were in good agreement and confirmed the applicability of developed models. It will enable the identification of a trait-specific germplasm as a potential gene source and aid in crop improvement programs